In some aspects, the CU 110 may host one or more higher layer control functions. Such control functions can include radio resource control (RRC), packet data convergence protocol (PDCP), service data adaptation protocol (SDAP), or the like. Each control function can be implemented with an interface configured to communicate signals with other control functions hosted by the CU 110. The CU 110 may be configured to handle user plane functionality (i.e., Central Unit-User Plane (CU-UP)), control plane functionality (i.e., Central Unit-Control Plane (CU-CP)), or a combination thereof. In some implementations, the CU 110 can be logically split into one or more CU-UP units and one or more CU-CP units. The CU-UP unit can communicate bidirectionally with the CU-CP unit via an interface, such as an E1 interface when implemented in an O-RAN configuration. The CU 110 can be implemented to communicate with the DU 130, as necessary, for network control and signaling.

The DU 130 may correspond to a logical unit that includes one or more base station functions to control the operation of one or more RUs 140. In some aspects, the DU 130 may host one or more of a radio link control (RLC) layer, a medium access control (MAC) layer, and one or more high physical (PHY) layers (such as modules for forward error correction (FEC) encoding and decoding, scrambling, modulation, demodulation, or the like) depending, at least in part, on a functional split, such as those defined by 3GPP. In some aspects, the DU 130 may further host one or more low PHY layers. Each layer (or module) can be implemented with an interface configured to communicate signals with other layers (and modules) hosted by the DU 130, or with the control functions hosted by the CU 110.

Lower-layer functionality can be implemented by one or more RUs 140. In some deployments, an RU 140, controlled by a DU 130, may correspond to a logical node that hosts RF processing functions, or low-PHY layer functions (such as performing fast Fourier transform (FFT), inverse FFT (IFFT), digital beamforming, physical random access channel (PRACH) extraction and filtering, or the like), or both, based at least in part on the functional split, such as a lower layer functional split. In such an architecture, the RU(s) 140 can be implemented to handle over the air (OTA) communication with one or more UEs 104. In some implementations, real-time and non-real-time aspects of control and user plane communication with the RU(s) 140 can be controlled by the corresponding DU 130. In some scenarios, this configuration can enable the DU(s) 130 and the CU 110 to be implemented in a cloud-based RAN architecture, such as a vRAN architecture.

The SMO Framework 105 may be configured to support RAN deployment and provisioning of non-virtualized and virtualized network elements. For non-virtualized network elements, the SMO Framework 105 may be configured to support the deployment of dedicated physical resources for RAN coverage requirements that may be managed via an operations and maintenance interface (such as an O1 interface). For virtualized network elements, the SMO Framework 105 may be configured to interact with a cloud computing platform (such as an open cloud (O-Cloud) 190) to perform network element life cycle management (such as to instantiate virtualized network elements) via a cloud computing platform interface (such as an O2 interface). Such virtualized network elements can include, but are not limited to, CUs 110, DUs 130, RUs 140 and Near-RT RICs 125. In some implementations, the SMO Framework 105 can communicate with a hardware aspect of a 4G RAN, such as an open eNB (O-eNB) 111, via an O1 interface. Additionally, in some implementations, the SMO Framework 105 can communicate directly with one or more RUs 140 via an O1 interface. The SMO Framework 105 also may include a Non-RT RIC 115 configured to support functionality of the SMO Framework 105.

The Non-RT RIC 115 may be configured to include a logical function that enables non-real-time control and optimization of RAN elements and resources, artificial intelligence (AI)/machine learning (ML) (AI/ML) workflows including model training and updates, or policy-based guidance of applications/features in the Near-RT RIC 125. The Non-RT RIC 115 may be coupled to or communicate with (such as via an A1 interface) the Near-RT RIC 125. The Near-RT RIC 125 may be configured to include a logical function that enables near-real-time control and optimization of RAN elements and resources via data collection and actions over an interface (such as via an E2 interface) connecting one or more CUs 110, one or more DUs 130, or both, as well as an O-eNB, with the Near-RT RIC 125.

In some implementations, to generate AI/ML models to be deployed in the Near-RT RIC 125, the Non-RT RIC 115 may receive parameters or external enrichment information from external servers. Such information may be utilized by the Near-RT RIC 125 and may be received at the SMO Framework 105 or the Non-RT RIC 115 from non-network data sources or from network functions. In some examples, the Non-RT RIC 115 or the Near-RT RIC 125 may be configured to tune RAN behavior or performance. For example, the Non-RT RIC 115 may monitor long-term trends and patterns for performance and employ AI/ML models to perform corrective actions through the SMO Framework 105 (such as reconfiguration via O1) or via creation of RAN management policies (such as A1 policies).

At least one of the CU 110, the DU 130, and the RU 140 may be referred to as a base station 102. Accordingly, a base station 102 may include one or more of the CU 110, the DU 130, and the RU 140 (each component indicated with dotted lines to signify that each component may or may not be included in the base station 102). The base station 102 provides an access point to the core network 120 for a UE 104. The base station 102 may include macrocells (high power cellular base station) and/or small cells (low power cellular base station). The small cells include femtocells, picocells, and microcells. A network that includes both small cell and macrocells may be known as a heterogeneous network. A heterogeneous network may also include Home Evolved Node Bs (eNBs) (HeNBs), which may provide service to a restricted group known as a closed subscriber group (CSG). The communication links between the RUs 140 and the UEs 104 may include uplink (UL) (also referred to as reverse link) transmissions from a UE 104 to an RU 140 and/or downlink (DL) (also referred to as forward link) transmissions from an RU 140 to a UE 104. The communication links may use multiple-input and multiple-output (MIMO) antenna technology, including spatial multiplexing, beamforming, and/or transmit diversity. The communication links may be through one or more carriers. The base station 102/UEs 104 may use spectrum up to Y MHz (e.g., 5, 10, 15, 20, 100, 400, etc. MHz) bandwidth per carrier allocated in a carrier aggregation of up to a total of Yx MHz (x component carriers) used for transmission in each direction. The carriers may or may not be adjacent to each other. Allocation of carriers may be asymmetric with respect to DL and UL (e.g., more or fewer carriers may be allocated for DL than for UL). The component carriers may include a primary component carrier and one or more secondary component carriers. A primary component carrier may be referred to as a primary cell (PCell) and a secondary component carrier may be referred to as a secondary cell (SCell).

Certain UEs 104 may communicate with each other using device-to-device (D2D) communication link 158. The D2D communication link 158 may use the DL/UL wireless wide area network (WWAN) spectrum. The D2D communication link 158 may use one or more sidelink channels, such as a physical sidelink broadcast channel (PSBCH), a physical sidelink discovery channel (PSDCH), a physical sidelink shared channel (PSSCH), and a physical sidelink control channel (PSCCH). D2D communication may be through a variety of wireless D2D communications systems, such as for example, Bluetooth™ (Bluetooth is a trademark of the Bluetooth Special Interest Group (SIG)), Wi-Fi™ (Wi-Fi is a trademark of the Wi-Fi Alliance) based on the Institute of Electrical and Electronics Engineers (IEEE) 802.11 standard, LTE, or NR.

The wireless communications system may further include a Wi-Fi AP 150 in communication with UEs 104 (also referred to as Wi-Fi stations (STAs)) via communication link 154, e.g., in a 5 GHz unlicensed frequency spectrum or the like. When communicating in an unlicensed frequency spectrum, the UEs 104/AP 150 may perform a clear channel assessment (CCA) prior to communicating in order to determine whether the channel is available.

The electromagnetic spectrum is often subdivided, based on frequency/wavelength, into various classes, bands, channels, etc. In 5G NR, two initial operating bands have been identified as frequency range designations FR1 (410 MHZ-7.125 GHZ) and FR2 (24.25 GHz-52.6 GHZ). Although a portion of FR1 is greater than 6 GHZ, FR1 is often referred to (interchangeably) as a “sub-6 GHz” band in various documents and articles. A similar nomenclature issue sometimes occurs with regard to FR2, which is often referred to (interchangeably) as a “millimeter wave” band in documents and articles, despite being different from the extremely high frequency (EHF) band (30 GHz-300 GHz) which is identified by the International Telecommunications Union (ITU) as a “millimeter wave” band.

The frequencies between FR1 and FR2 are often referred to as mid-band frequencies. Recent 5G NR studies have identified an operating band for these mid-band frequencies as frequency range designation FR3 (7.125 GHZ-24.25 GHZ). Frequency bands falling within FR3 may inherit FR1 characteristics and/or FR2 characteristics, and thus may effectively extend features of FR1 and/or FR2 into mid-band frequencies. In addition, higher frequency bands are currently being explored to extend 5G NR operation beyond 52.6 GHz. For example, three higher operating bands have been identified as frequency range designations FR2-2 (52.6 GHz-71 GHZ), FR4 (71 GHz-114.25 GHZ), and FR5 (114.25 GHZ-300 GHZ). Each of these higher frequency bands falls within the EHF band.

With the above aspects in mind, unless specifically stated otherwise, the term “sub-6 GHz” or the like if used herein may broadly represent frequencies that may be less than 6 GHz, may be within FR1, or may include mid-band frequencies. Further, unless specifically stated otherwise, the term “millimeter wave” or the like if used herein may broadly represent frequencies that may include mid-band frequencies, may be within FR2, FR4, FR2-2, and/or FR5, or may be within the EHF band.

The base station 102 and the UE 104 may each include a plurality of antennas, such as antenna elements, antenna panels, and/or antenna arrays to facilitate beamforming. The base station 102 may transmit a beamformed signal 182 to the UE 104 in one or more transmit directions. The UE 104 may receive the beamformed signal from the base station 102 in one or more receive directions. The UE 104 may also transmit a beamformed signal 184 to the base station 102 in one or more transmit directions. The base station 102 may receive the beamformed signal from the UE 104 in one or more receive directions. The base station 102/UE 104 may perform beam training to determine the best receive and transmit directions for each of the base station 102/UE 104. The transmit and receive directions for the base station 102 may or may not be the same. The transmit and receive directions for the UE 104 may or may not be the same.

The base station 102 may include and/or be referred to as a gNB, Node B, cNB, an access point, a base transceiver station, a radio base station, a radio transceiver, a transceiver function, a basic service set (BSS), an extended service set (ESS), a TRP, network node, network entity, network equipment, or some other suitable terminology. The base station 102 can be implemented as an integrated access and backhaul (IAB) node, a relay node, a sidelink node, an aggregated (monolithic) base station with a baseband unit (BBU) (including a CU and a DU) and an RU, or as a disaggregated base station including one or more of a CU, a DU, and/or an RU. The set of base stations, which may include disaggregated base stations and/or aggregated base stations, may be referred to as next generation (NG) RAN (NG-RAN).

The core network 120 may include an Access and Mobility Management Function (AMF) 161, a Session Management Function (SMF) 162, a User Plane Function (UPF) 163, a Unified Data Management (UDM) 164, one or more location servers 168, and other functional entities. The AMF 161 is the control node that processes the signaling between the UEs 104 and the core network 120. The AMF 161 supports registration management, connection management, mobility management, and other functions. The SMF 162 supports session management and other functions. The UPF 163 supports packet routing, packet forwarding, and other functions. The UDM 164 supports the generation of authentication and key agreement (AKA) credentials, user identification handling, access authorization, and subscription management. The one or more location servers 168 are illustrated as including a Gateway Mobile Location Center (GMLC) 165 and a Location Management Function (LMF) 166. However, generally, the one or more location servers 168 may include one or more location/positioning servers, which may include one or more of the GMLC 165, the LMF 166, a position determination entity (PDE), a serving mobile location center (SMLC), a mobile positioning center (MPC), or the like. The GMLC 165 and the LMF 166 support UE location services. The GMLC 165 provides an interface for clients/applications (e.g., emergency services) for accessing UE positioning information. The LMF 166 receives measurements and assistance information from the NG-RAN and the UE 104 via the AMF 161 to compute the position of the UE 104. The NG-RAN may utilize one or more positioning methods in order to determine the position of the UE 104. Positioning the UE 104 may involve signal measurements, a position estimate, and an optional velocity computation based on the measurements. The signal measurements may be made by the UE 104 and/or the base station 102 serving the UE 104. The signals measured may be based on one or more of a satellite positioning system (SPS) 170 (e.g., one or more of a Global Navigation Satellite System (GNSS), global position system (GPS), non-terrestrial network (NTN), or other satellite position/location system), LTE signals, wireless local area network (WLAN) signals, Bluetooth signals, a terrestrial beacon system (TBS), sensor-based information (e.g., barometric pressure sensor, motion sensor), NR enhanced cell ID (NR E-CID) methods, NR signals (e.g., multi-round trip time (Multi-RTT), DL angle-of-departure (DL-AoD), DL time difference of arrival (DL-TDOA), UL time difference of arrival (UL-TDOA), and UL angle-of-arrival (UL-AoA) positioning), and/or other systems/signals/sensors.

Examples of UEs 104 include a cellular phone, a smart phone, a session initiation protocol (SIP) phone, a laptop, a personal digital assistant (PDA), a satellite radio, a global positioning system, a multimedia device, a video device, a digital audio player (e.g., MP3 player), a camera, a game console, a tablet, a smart device, a wearable device, a vehicle, an electric meter, a gas pump, a large or small kitchen appliance, a healthcare device, an implant, a sensor/actuator, a display, or any other similar functioning device. Some of the UEs 104 may be referred to as IoT devices (e.g., parking meter, gas pump, toaster, vehicles, heart monitor, etc.). The UE 104 may also be referred to as a station, a mobile station, a subscriber station, a mobile unit, a subscriber unit, a wireless unit, a remote unit, a mobile device, a wireless device, a wireless communications device, a remote device, a mobile subscriber station, an access terminal, a mobile terminal, a wireless terminal, a remote terminal, a handset, a user agent, a mobile client, a client, or some other suitable terminology. In some scenarios, the term UE may also apply to one or more companion devices such as in a device constellation arrangement. One or more of these devices may collectively access the network and/or individually access the network.

Referring again to FIG. 1, in certain aspects, the UE 104 may have a detection component 198 that may be configured to obtain an indication of a set of parameters associated with the vehicle. Detection component 198 may also be configured to measure the at least one parameter in the set of parameters to determine whether the at least one parameter in the set of parameters is greater than or equal to the threshold level. Detection component 198 may also be configured to determine that at least one parameter in the set of parameters is greater than or equal to a threshold level. Detection component 198 may also be configured to output an indication of the determination that the at least one parameter is greater than or equal to the threshold level. Detection component 198 may also be configured to output an indication to perform a safe harbor maneuver for the vehicle based on the determination that the at least one parameter is greater than or equal to the threshold level. Detection component 198 may also be configured to reduce, based on the indication to perform the safe harbor maneuver, a functionality of a portion of at least one of a system-on-chip (SoC) of the vehicle or an electronic control unit (ECU) of the vehicle. Detection component 198 may also be configured to initiate the safe harbor maneuver for the vehicle based on the determination that the at least one parameter is greater than or equal to the threshold level.

FIG. 2A is a diagram 200 illustrating an example of a first subframe within a 5G NR frame structure. FIG. 2B is a diagram 230 illustrating an example of DL channels within a 5G NR subframe. FIG. 2C is a diagram 250 illustrating an example of a second subframe within a 5G NR frame structure. FIG. 2D is a diagram 280 illustrating an example of UL channels within a 5G NR subframe. The 5G NR frame structure may be frequency division duplexed (FDD) in which for a particular set of subcarriers (carrier system bandwidth), subframes within the set of subcarriers are dedicated for either DL or UL, or may be time division duplexed (TDD) in which for a particular set of subcarriers (carrier system bandwidth), subframes within the set of subcarriers are dedicated for both DL and UL. In the examples provided by FIGS. 2A, 2C, the 5G NR frame structure is assumed to be TDD, with subframe 4 being configured with slot format 28 (with mostly DL), where D is DL, U is UL, and F is flexible for use between DL/UL, and subframe 3 being configured with slot format 1 (with all UL). While subframes 3, 4 are shown with slot formats 1, 28, respectively, any particular subframe may be configured with any of the various available slot formats 0-61. Slot formats 0, 1 are all DL, UL, respectively. Other slot formats 2-61 include a mix of DL, UL, and flexible symbols. UEs are configured with the slot format (dynamically through DL control information (DCI), or semi-statically/statically through radio resource control (RRC) signaling) through a received slot format indicator (SFI). Note that the description infra applies also to a 5G NR frame structure that is TDD.

FIGS. 2A-2D illustrate a frame structure, and the aspects of the present disclosure may be applicable to other wireless communication technologies, which may have a different frame structure and/or different channels. A frame (10 ms) may be divided into 10 equally sized subframes (1 ms). Each subframe may include one or more time slots. Subframes may also include mini-slots, which may include 7, 4, or 2 symbols. Each slot may include 14 or 12 symbols, depending on whether the cyclic prefix (CP) is normal or extended. For normal CP, each slot may include 14 symbols, and for extended CP, each slot may include 12 symbols. The symbols on DL may be CP orthogonal frequency division multiplexing (OFDM) (CP-OFDM) symbols. The symbols on UL may be CP-OFDM symbols (for high throughput scenarios) or discrete Fourier transform (DFT) spread OFDM (DFT-s-OFDM) symbols (for power limited scenarios; limited to a single stream transmission). The number of slots within a subframe is based on the CP and the numerology. The numerology defines the subcarrier spacing (SCS) (see Table 1). The symbol length/duration may scale with 1/SCS.

TABLE 1

Numerology, SCS, and CP

SCS

μ
Δf = 2^μ · 15[kHz]
Cyclic prefix

0
15
Normal

1
30
Normal

2
60
Normal, Extended

3
120
Normal

4
240
Normal

5
480
Normal

6
960
Normal

For normal CP (14 symbols/slot), different numerologies μ 0 to 4 allow for 1, 2, 4, 8, and 16 slots, respectively, per subframe. For extended CP, the numerology 2 allows for 4 slots per subframe. Accordingly, for normal CP and numerology μ, there are 14 symbols/slot and 2^μ slots/subframe. The subcarrier spacing may be equal to 2^μ*15 kHz, where μ is the numerology 0 to 4. As such, the numerology u=0 has a subcarrier spacing of 15 kHz and the numerology μ=4 has a subcarrier spacing of 240 kHz. The symbol length/duration is inversely related to the subcarrier spacing. FIGS. 2A-2D provide an example of normal CP with 14 symbols per slot and numerology μ=2 with 4 slots per subframe. The slot duration is 0.25 ms, the subcarrier spacing is 60 kHz, and the symbol duration is approximately 16.67 μs. Within a set of frames, there may be one or more different bandwidth parts (BWPs) (see FIG. 2B) that are frequency division multiplexed. Each BWP may have a particular numerology and CP (normal or extended).

A resource grid may be used to represent the frame structure. Each time slot includes a resource block (RB) (also referred to as physical RBs (PRBs)) that extends 12 consecutive subcarriers. The resource grid is divided into multiple resource elements (REs). The number of bits carried by each RE depends on the modulation scheme.

As illustrated in FIG. 2A, some of the REs carry reference (pilot) signals (RS) for the UE. The RS may include demodulation RS (DM-RS) (indicated as R for one particular configuration, but other DM-RS configurations are possible) and channel state information reference signals (CSI-RS) for channel estimation at the UE. The RS may also include beam measurement RS (BRS), beam refinement RS (BRRS), and phase tracking RS (PT-RS).

FIG. 2B illustrates an example of various DL channels within a subframe of a frame. The physical downlink control channel (PDCCH) carries DCI within one or more control channel elements (CCEs) (e.g., 1, 2, 4, 8, or 16 CCEs), each CCE including six RE groups (REGs), each REG including 12 consecutive REs in an OFDM symbol of an RB. A PDCCH within one BWP may be referred to as a control resource set (CORESET). A UE is configured to monitor PDCCH candidates in a PDCCH search space (e.g., common search space, UE-specific search space) during PDCCH monitoring occasions on the CORESET, where the PDCCH candidates have different DCI formats and different aggregation levels. Additional BWPs may be located at greater and/or lower frequencies across the channel bandwidth. A primary synchronization signal (PSS) may be within symbol 2 of particular subframes of a frame. The PSS is used by a UE 104 to determine subframe/symbol timing and a physical layer identity. A secondary synchronization signal (SSS) may be within symbol 4 of particular subframes of a frame. The SSS is used by a UE to determine a physical layer cell identity group number and radio frame timing. Based on the physical layer identity and the physical layer cell identity group number, the UE can determine a physical cell identifier (PCI). Based on the PCI, the UE can determine the locations of the DM-RS. The physical broadcast channel (PBCH), which carries a master information block (MIB), may be logically grouped with the PSS and SSS to form a synchronization signal (SS)/PBCH block (also referred to as SS block (SSB)). The MIB provides a number of RBs in the system bandwidth and a system frame number (SFN). The physical downlink shared channel (PDSCH) carries user data, broadcast system information not transmitted through the PBCH such as system information blocks (SIBs), and paging messages.

As illustrated in FIG. 2C, some of the REs carry DM-RS (indicated as R for one particular configuration, but other DM-RS configurations are possible) for channel estimation at the base station. The UE may transmit DM-RS for the physical uplink control channel (PUCCH) and DM-RS for the physical uplink shared channel (PUSCH). The PUSCH DM-RS may be transmitted in the first one or two symbols of the PUSCH. The PUCCH DM-RS may be transmitted in different configurations depending on whether short or long PUCCHs are transmitted and depending on the particular PUCCH format used. The UE may transmit sounding reference signals (SRS). The SRS may be transmitted in the last symbol of a subframe. The SRS may have a comb structure, and a UE may transmit SRS on one of the combs. The SRS may be used by a base station for channel quality estimation to enable frequency-dependent scheduling on the UL.

FIG. 2D illustrates an example of various UL channels within a subframe of a frame. The PUCCH may be located as indicated in one configuration. The PUCCH carries uplink control information (UCI), such as scheduling requests, a channel quality indicator (CQI), a precoding matrix indicator (PMI), a rank indicator (RI), and hybrid automatic repeat request (HARQ) acknowledgment (ACK) (HARQ-ACK) feedback (i.e., one or more HARQ ACK bits indicating one or more ACK and/or negative ACK (NACK)). The PUSCH carries data, and may additionally be used to carry a buffer status report (BSR), a power headroom report (PHR), and/or UCI.

FIG. 3 is a block diagram of a base station 310 in communication with a UE 350 in an access network. In the DL, Internet protocol (IP) packets may be provided to a controller/processor 375. The controller/processor 375 implements layer 3 and layer 2 functionality. Layer 3 includes a radio resource control (RRC) layer, and layer 2 includes a service data adaptation protocol (SDAP) layer, a packet data convergence protocol (PDCP) layer, a radio link control (RLC) layer, and a medium access control (MAC) layer. The controller/processor 375 provides RRC layer functionality associated with broadcasting of system information (e.g., MIB, SIBs), RRC connection control (e.g., RRC connection paging, RRC connection establishment, RRC connection modification, and RRC connection release), inter radio access technology (RAT) mobility, and measurement configuration for UE measurement reporting; PDCP layer functionality associated with header compression/decompression, security (ciphering, deciphering, integrity protection, integrity verification), and handover support functions; RLC layer functionality associated with the transfer of upper layer packet data units (PDUs), error correction through ARQ, concatenation, segmentation, and reassembly of RLC service data units (SDUs), re-segmentation of RLC data PDUs, and reordering of RLC data PDUs; and MAC layer functionality associated with mapping between logical channels and transport channels, multiplexing of MAC SDUs onto transport blocks (TBs), demultiplexing of MAC SDUs from TBs, scheduling information reporting, error correction through HARQ, priority handling, and logical channel prioritization.

The transmit (TX) processor 316 and the receive (RX) processor 370 implement layer 1 functionality associated with various signal processing functions. Layer 1, which includes a physical (PHY) layer, may include error detection on the transport channels, forward error correction (FEC) coding/decoding of the transport channels, interleaving, rate matching, mapping onto physical channels, modulation/demodulation of physical channels, and MIMO antenna processing. The TX processor 316 handles mapping to signal constellations based on various modulation schemes (e.g., binary phase-shift keying (BPSK), quadrature phase-shift keying (QPSK), M-phase-shift keying (M-PSK), M-quadrature amplitude modulation (M-QAM)). The coded and modulated symbols may then be split into parallel streams. Each stream may then be mapped to an OFDM subcarrier, multiplexed with a reference signal (e.g., pilot) in the time and/or frequency domain, and then combined together using an Inverse Fast Fourier Transform (IFFT) to produce a physical channel carrying a time domain OFDM symbol stream. The OFDM stream is spatially precoded to produce multiple spatial streams. Channel estimates from a channel estimator 374 may be used to determine the coding and modulation scheme, as well as for spatial processing. The channel estimate may be derived from a reference signal and/or channel condition feedback transmitted by the UE 350. Each spatial stream may then be provided to a different antenna 320 via a separate transmitter 318Tx. Each transmitter 318Tx may modulate a radio frequency (RF) carrier with a respective spatial stream for transmission.

At the UE 350, each receiver 354Rx receives a signal through its respective antenna 352. Each receiver 354Rx recovers information modulated onto an RF carrier and provides the information to the receive (RX) processor 356. The TX processor 368 and the RX processor 356 implement layer 1 functionality associated with various signal processing functions. The RX processor 356 may perform spatial processing on the information to recover any spatial streams destined for the UE 350. If multiple spatial streams are destined for the UE 350, they may be combined by the RX processor 356 into a single OFDM symbol stream. The RX processor 356 then converts the OFDM symbol stream from the time-domain to the frequency domain using a Fast Fourier Transform (FFT). The frequency domain signal includes a separate OFDM symbol stream for each subcarrier of the OFDM signal. The symbols on each subcarrier, and the reference signal, are recovered and demodulated by determining the most likely signal constellation points transmitted by the base station 310. These soft decisions may be based on channel estimates computed by the channel estimator 358. The soft decisions are then decoded and deinterleaved to recover the data and control signals that were originally transmitted by the base station 310 on the physical channel. The data and control signals are then provided to the controller/processor 359, which implements layer 3 and layer 2 functionality.

The controller/processor 359 can be associated with at least one memory 360 that stores program codes and data. The at least one memory 360 may be referred to as a computer-readable medium. In the UL, the controller/processor 359 provides demultiplexing between transport and logical channels, packet reassembly, deciphering, header decompression, and control signal processing to recover IP packets. The controller/processor 359 is also responsible for error detection using an ACK and/or NACK protocol to support HARQ operations.

Similar to the functionality described in connection with the DL transmission by the base station 310, the controller/processor 359 provides RRC layer functionality associated with system information (e.g., MIB, SIBs) acquisition, RRC connections, and measurement reporting; PDCP layer functionality associated with header compression/decompression, and security (ciphering, deciphering, integrity protection, integrity verification); RLC layer functionality associated with the transfer of upper layer PDUs, error correction through ARQ, concatenation, segmentation, and reassembly of RLC SDUs, re-segmentation of RLC data PDUs, and reordering of RLC data PDUs; and MAC layer functionality associated with mapping between logical channels and transport channels, multiplexing of MAC SDUs onto TBs, demultiplexing of MAC SDUs from TBs, scheduling information reporting, error correction through HARQ, priority handling, and logical channel prioritization.

Channel estimates derived by a channel estimator 358 from a reference signal or feedback transmitted by the base station 310 may be used by the TX processor 368 to select the appropriate coding and modulation schemes, and to facilitate spatial processing. The spatial streams generated by the TX processor 368 may be provided to different antenna 352 via separate transmitters 354Tx. Each transmitter 354Tx may modulate an RF carrier with a respective spatial stream for transmission.

The UL transmission is processed at the base station 310 in a manner similar to that described in connection with the receiver function at the UE 350. Each receiver 318Rx receives a signal through its respective antenna 320. Each receiver 318Rx recovers information modulated onto an RF carrier and provides the information to a RX processor 370.

The controller/processor 375 can be associated with at least one memory 376 that stores program codes and data. The at least one memory 376 may be referred to as a computer-readable medium. In the UL, the controller/processor 375 provides demultiplexing between transport and logical channels, packet reassembly, deciphering, header decompression, control signal processing to recover IP packets. The controller/processor 375 is also responsible for error detection using an ACK and/or NACK protocol to support HARQ operations.

At least one of the TX processor 368, the RX processor 356, and the controller/processor 359 may be configured to perform aspects in connection with the detection component 198 of FIG. 1.

Instructions executed by a CPU (e.g., software instructions) or a display processor may cause the CPU or the display processor to search for and/or generate a composition strategy for composing a frame based on a dynamic priority and runtime statistics associated with one or more composition strategy groups. A frame to be displayed by a physical display device, such as a display panel, may include a plurality of layers. Also, composition of the frame may be based on combining the plurality of layers into the frame (e.g., based on a frame buffer). After the plurality of layers are combined into the frame, the frame may be provided to the display panel for display thereon. The process of combining each of the plurality of layers into the frame may be referred to as composition, frame composition, a composition procedure, a composition process, or the like.

A frame composition procedure or composition strategy may correspond to a technique for composing different layers of the plurality of layers into a single frame. The plurality of layers may be stored in doubled data rate (DDR) memory. Each layer of the plurality of layers may further correspond to a separate buffer. A composer or hardware composer (HWC) associated with a block or function may determine an input of each layer/buffer and perform the frame composition procedure to generate an output indicative of a composed frame. That is, the input may be the layers and the output may be a frame composition procedure for composing the frame to be displayed on the display panel.

In some aspects, a display device may present frames at different frame rates on the first display panel and the second display panel. For instance, a display panel may present frames at 60 frames per second (FPS) on both the first display panel and the second display panel, 45 FPS on both the first display panel and the second display panel, etc. The display device may synchronize frame rates of content with refresh rates of the display panels (via a vertical synchronization process, which may be referred to as vsync, Vsync, VSync, or VSYNC). For instance, content may be available at 60 FPS and the first display panel and the second display panel may have a refresh rate of 95 Hz. Via Vsync, the refresh rate of the first display panel and the second display panel may be set to 60 Hz to match the 60 FPS content.

As indicated herein, VSync is a graphics technology that synchronizes the frame rate of an application/game with a refresh rate at a display (e.g., a display on a client device). Vsync may be utilized as a manner in which to deal with screen tearing (i.e., the screen displays portions of multiple frames at once). That can result in the display appearing to be split along a line. Tearing may occur when the display refresh rate (i.e., how many times the display updates per second) is not in synchronization with the frames per second (FPS). VSync signals may synchronize the display pipeline (e.g., the pipeline including application rendering, compositor, and a hardware composer (HWC) that presents images on the display). For instance, VSync signals may help to synchronize the time in which applications wake up to start rendering, the time the compositor wakes up to composite the screen, and the display refresh cycle. This synchronization may help to eliminate display refresh issues and improve visual performance. In some examples, the HWC may generates VSync events/signals and send the events/signals to the compositor.

FIG. 4 is a diagram 400 that illustrates processing components, such as a processing unit 430 and the system memory 440, as may be identified in connection with a device for processing data. In aspects, the processing unit 430 may include a CPU 402 and a GPU 412. The GPU 412 and the CPU 402 may be formed as an integrated circuit (e.g., a system-on-a-chip (SOC)) and/or the GPU 412 may be incorporated onto a motherboard with the CPU 402. Alternatively, the CPU 402 and the GPU 412 may be configured as distinct processing units that are communicatively coupled to each other. For example, the GPU 412 may be incorporated on a graphics card that is installed in a port of the motherboard that includes the CPU 402.

The CPU 402 may be configured to execute a software application that causes graphical content to be displayed (e.g., on a display(s) of a device) based on one or more operations of the GPU 412. The software application may issue instructions to a graphics application program interface (API) 404, which may be a runtime program that translates instructions received from the software application into a format that is readable by a GPU driver 410. After receiving instructions from the software application via the graphics API 404, the GPU driver 410 may control an operation of the GPU 412 based on the instructions. For example, the GPU driver 410 may generate one or more command streams that are placed into the system memory 440, where the GPU 412 is instructed to execute the command streams (e.g., via one or more system calls). A command engine 414 included in the GPU 412 is configured to retrieve the one or more commands stored in the command streams. The command engine 414 may provide commands from the command stream for execution by the GPU 412. The command engine 414 may be hardware of the GPU 412, software/firmware executing on the GPU 412, or a combination thereof. While the GPU driver 410 is configured to implement the graphics API 404, the GPU driver 410 is not limited to being configured in accordance with any particular API. The system memory 440 may store the code for the GPU driver 410, which the CPU 402 may retrieve for execution. In examples, the GPU driver 410 may be configured to allow communication between the CPU 402 and the GPU 412, such as when the CPU 402 offloads graphics or non-graphics processing tasks to the GPU 412 via the GPU driver 410.

The system memory 440 may further store source code for one or more of an early preamble shader 424, a feedback shader 425, or a main shader 426. In such configurations, a shader compiler 408 executing on the CPU 402 may compile the source code of the shaders 424-426 to create object code or intermediate code executable by a shader core 416 of the GPU 412 during runtime (e.g., at the time when the shaders 424-426 are to be executed on the shader core 416). In some examples, the shader compiler 408 may pre-compile the shaders 424-426 and store the object code or intermediate code of the shader programs in the system memory 440. The shader compiler 408 (or in another example the GPU driver 410) executing on the CPU 402 may build a shader program with multiple components including the early preamble shader 424, the feedback shader 425, and the main shader 426. The main shader 426 may correspond to a portion or the entirety of the shader program that does not include the early preamble shader 424 or the feedback shader 425. The shader compiler 408 may receive instructions to compile the shader(s) 424-426 from a program executing on the CPU 402. The shader compiler 408 may also identify constant load instructions and common operations in the shader program for including the common operations within the early preamble shader 424 (rather than the main shader 426). The shader compiler 408 may identify such common instructions, for example, based on (presently undetermined) constants 406 to be included in the common instructions. The constants 406 may be defined within the graphics API 404 to be constant across an entire draw call. The shader compiler 408 may utilize instructions such as a preamble shader start to indicate a beginning of the early preamble shader 424 and a preamble shader end to indicate an end of the early preamble shader 424. Similar instructions may be used for the feedback shader 425 and the main shader 426. The feedback shader 425 will be described in further detail below.

The shader core 416 included in the GPU 412 may include general purpose registers (GPRs) 418 and constant memory 420. The GPRs 418 may correspond to a single GPR, a GPR file, and/or a GPR bank. Each GPR in the GPRs 418 may store data accessible to a single thread. The software and/or firmware executing on GPU 412 may be a shader program 424-426, which may execute on the shader core 416 of GPU 412. The shader core 416 may be configured to execute many instances of the same instructions of the same shader program in parallel. For example, the shader core 416 may execute the main shader 426 for each pixel that defines a given shape. The shader core 416 may transmit and receive data from applications executing on the CPU 402. In examples, constants 406 used for execution of the shaders 424-426 may be stored in a constant memory 420 (e.g., a read/write constant RAM) or the GPRs 418. The shader core 416 may load the constants 406 into the constant memory 420. In further examples, execution of the early preamble shader 424 or the feedback shader 425 may cause a constant value or a set of constant values to be stored in on-chip memory such as the constant memory 420 (e.g., constant RAM), the GPU memory 422, or the system memory 440. The constant memory 420 may include memory accessible by all aspects of the shader core 416 rather than just a particular portion reserved for a particular thread such as values held in the GPRs 418.

In recent years, vehicle manufacturers have been developing vehicles with assisted driving and/or autonomous driving capabilities. Assisted driving, which may also be called advanced driver assistance systems (ADAS), may refer to a set of technologies designed to enhance vehicle safety and improve the driving experience by providing assistance and automation to the driver. These technologies may use various sensor(s), such as camera(s), radar(s), light detection and ranging (lidar(s) or lidar sensor(s)), etc., and other components to monitor a vehicle's surroundings and assist the driver of the vehicle with certain driving tasks. For example, some features of assisted driving systems may include: (1) adaptive cruise control (ACC) (e.g., a system that automatically adjusts a vehicle's speed to maintain a safe following distance from the vehicle ahead), (2) lane-keeping assist (LKA) (e.g., a system that uses cameras to detect lane markings and helps keep the vehicle centered within the lance, and provides steering inputs to prevent unintentional lane departure), (3) autonomous emergency braking (AEB) (e.g., a system that detects potential collisions with obstacles or pedestrians and automatically apply the brakes to avoid or mitigate the impact), (4) blind spot monitoring (BSM) (e.g., a system that uses sensors to detect vehicles in a driver's blind spots and provides visual or audible alerts to avoid potential collisions during lane changes), (5) parking assistance (e.g., a system that assists drivers in parking their vehicles by using camera(s) and sensor(s) to help with parallel parking or maneuvering into tight spaces), and/or traffic sign recognition (e.g., camera(s) and image processing are used to recognize and display traffic signs such as speed limits, stop signs, and other road regulations on the vehicle's dashboard).

Autonomous driving, which may also be called as self-driving or driverless technology, may refer to the ability of a vehicle to navigate and operate itself without specifying human intervention (e.g., travelling from one place to another place without a human controlling the vehicle). The goal of the autonomous driving is to create vehicles that are capable of perceiving their surroundings, making decisions, and controlling their movements, all without the direct involvement of a human driver. To achieve or improve the autonomous driving, a vehicle may be specified to use a map (or map data) with detailed information, such as a high-definition (HD) map. An HD map may refer to a highly detailed and accurate digital map designed for use in autonomous driving and ADAS. In one example, HD maps may typically include one or more of: (1) geometric information (e.g., precise road geometry, including lane boundaries, curvature, slopes, and detailed 3D models of the surrounding environment), (2) lane-level information (e.g., information about individual lanes on the road, such as lane width, lane type (e.g., driving, turning, or parking lanes), and lane connectivity), (3) road attributes (e.g., data on road features like traffic signs, signals, traffic lights, speed limits, and road markings), (4) topology (e.g., information about the relationships between different roads, intersections, and connectivity patterns), (5) static objects (e.g., locations and details of fixed objects along the road, such as buildings, traffic barriers, and poles), (6) dynamic objects (e.g., real-time or frequently updated data about moving objects, like other vehicles, pedestrians, and cyclists), and/or (7) localization and positioning: precise reference points and landmarks that help in accurate vehicle localization on the map, etc.

Note while some assisted/autonomous driving systems may demand the use of HD map data, there are also assisted/autonomous driving systems and information systems that may be configured not to use HD map data (e.g., due to costs). For example, the Society of Automotive Engineers (SAE) has defined six levels of driving automation, from Level 0 (no automation) to Level 5 (full automation). For Level 0 (no automation), the human driver may be responsible for all aspects of driving, and the system may provide warnings or momentary assistance but does not take control of the vehicle. Example features for SAE Level 0 may include automatic emergency braking, blind spot warnings, and lane departure warnings, etc. As such, SAE Level 0 may not specify using HD map data. For Level 1 (driver assistance), the vehicle may assist with either steering or acceleration/deceleration (but may not perform both simultaneously). The human driver is still responsible for most driving tasks and may need to be ready to take over at any time. Example features for SAE Level 1 may include adaptive cruise control or lane-keeping assistance (e.g., lane centering), etc. For Level 2 (partial automation), the vehicle may control both steering and acceleration/deceleration under certain conditions, but the human driver is requested to remain engaged and monitor the driving environment at all times. Example features for SAE Level 2 may include ADAS, adaptive cruise control and lane-keeping assistance at the same time, etc. For Level 3 (conditional automation), the vehicle may perform all driving tasks under specific conditions, and the human driver may not be specified to monitor the environment but may need to be ready to take over when requested by the system. Example features for SAE Level 3 may include traffic jam chauffeur, where the vehicle is capable of handling driving in traffic jams without driver intervention. For Level 4 (high automation), the vehicle is capable of handling all driving tasks within certain conditions or environments (geofenced areas). The system may operate without human intervention but may specify a human driver outside its operational domain. Example features for SAE Level 4 may include local driverless taxi and pedals/steering, etc. For Level 5 (full automation), the vehicle is capable of performing all driving tasks under all conditions, and does not specify the human driver at any time. Example features for SAE Level 5 may include fully autonomous vehicles with no steering wheel or pedals. In summary, SAE Level 0 may be defined as features to provide warnings and assistance. ADAS is usually SAE Level 1 and 2, while AD is considered SAE level 3 to 5. Aspects presented herein (described below) may apply to all levels of SAE, including SAE Level 0 (e.g., for speed warning). For purposes of the present disclosure, a system or information system that is used in associated with SAE Level 0 to Level 5 may collectively be referred to as a “vehicle system,” which may encompass the assisted driving and the autonomous driving.

To enable a vehicle to be capable of providing assisted driving and/or autonomous driving, the vehicle may be configured to use various machine learning (ML) and/or neural network (NN) frameworks. An ML/NN framework may refer to a set of tools, libraries, and/or software components that are configured to provide a structured way to design, build, and deploy ML/NN models and applications. These frameworks may be able to simplify the process of developing ML/NN algorithms and applications by providing a foundation of pre-built functions, algorithms, and utilities. They may typically include features for data preprocessing, model training, evaluation, and/or deployment, etc. ML/NN frameworks may come in various programming languages, and they may be configured to cater to different types of machine learning tasks, including supervised learning, unsupervised learning, and/or reinforcement learning, etc. An ML/NN model may refer to a mathematical representation of a real-world process or problem, created using ML/NN algorithms and techniques. These ML/NN models may be configured to make predictions, classify data, and/or solve specific tasks based on patterns and relationships learned from input data. A deep learning framework may refer to a specialized software library or toolset that provides specified components and abstractions for building, training, and deploying deep neural networks. Deep learning frameworks may be designed to facilitate the development of complex neural network models, especially deep neural networks with multiple layers. These frameworks may offer a wide range of pre-implemented layers, optimizers, loss functions, and other components, making it easier for researchers and developers to work with deep learning models.

FIG. 5 is a diagram 500 illustrating an example of a vehicle performing road object detection using different types of sensors in accordance with various aspects of the present disclosure. In some implementations, a vehicle system may be configured to perform road object detections using multiple types of sensors (and also one or more ML/NN models). For purposes of the present disclosure, a road object or a traffic participant may refer to an object that is related to roads and driving, and is typically/commonly used/considered by the vehicle system in providing assisted driving or performing autonomous driving. In some examples, the road object/traffic participant may also be referred to as a traffic-related object. For example, a road object/traffic participant may be another vehicle, a pedestrian, a cyclist/bicycle, an animal, a traffic cone, a traffic sign, a traffic light, traffic, a traffic lane, a traffic line, a vulnerable road user (VRU), an object that is within a threshold distance of the vehicle, and/or any objects that may typically present on the roads (e.g., on the driving paths of vehicles), etc. On the other hand, a non-road object or a non-traffic participant (which may also be referred to as a non-traffic related object) may refer to an object that is not related to roads and driving, and is typically/commonly not used/considered by the vehicle system in providing assisted driving or performing autonomous driving. For example, a non-road object/non-traffic participant may be an object that is not within a threshold distance of the vehicle (e.g., a house on the side of the road, a mountain that is far away), an object that is not typically presented on a driving path/road (an airplane, a fire hydrant, a tree, etc.), a structure that is typically not traversed by vehicles (e.g., a pedestrian bridge), etc. An ML/NN model may be trained to identify whether an object is a road object or a non-road object.

For example, as shown by the diagram 500, a vehicle or a vehicle system (collectively as a “UE 502”) may be configured to use different types of sensors, such as a set of cameras 504 and/or a set of radars 506 for detecting road objects. For purposes of the present disclosure, the term “radar” may broadly refer to a device/component that is capable of detecting at least the presence and/or the distance of a physical object. Examples of radar may include an RF radar, a sonar, an ultrasonic sensor, a light detection and ranging (lidar), etc. In some implementations, the UE 502 may also use different MN/NN models for identifying different types of road objects. For example, a first ML/NN model may be trained/used to detect and track polylines from sensor output(s) (e.g., images captured by the camera(s) of the vehicle, point clouds generated from radar(s)/lidar(s), etc.), while a second ML/NN model may be trained/used to detect and track objects in a three-dimensional (3D) space (e.g., to perform 3D object detection (3DOD) tasks). Then, the outputs of different types of sensors (e.g., from the set of cameras 504 and the set of radars 506) may be processed and used by the ADAS or the autonomous driving system (e.g., for assisted/autonomous driving). A point cloud may refer to a discrete set of data points in space, where these points may represent a 3D shape or object. In some implementations, each point position may be associated with a set of Cartesian coordinates (X, Y, Z). Point clouds may be produced by radar(s)/lidar(s) by detecting multiple points on the external surfaces of objects.

As described in connection with FIG. 5, various applications (e.g., use cases) such as assisted driving and/or autonomous driving, may specify the use of map data. To keep the map data up-to-date, these applications (or devices running these applications) may be configured to download updated map data from a server from time to time or based on certain pre-defined conditions (e.g., when travelling to an area that is without map data). In some implementations, downloading map data from a server may be referred to as “map over the air” (MOTA).

FIG. 6 is a diagram 600 illustrating an example of a vehicle performing map over the air in accordance with various aspects of the present disclosure. In one example, map over the air may refer to a process of a server 604 sending (real-time) map data 606 to a UE 602 (e.g., a vehicle, a vehicle system, an on-board unit (OBU) of the vehicle, a device running a navigation application, etc.) over a wireless network/communication (e.g., an LTE network, a 5G network, etc.), enabling the UE 602 to make decisions based on the latest information about the road and traffic conditions. Depending on implementations and conditions, different amount of map data 606 may be downloaded by the UE 602 from the server 604. For example, in some scenarios, the UE 602 may be configured to (1) download map data before driving, (2) download just updates for road conditions (e.g., traffic jams, construction work, etc.) while driving, (3) continuously download updated map data whenever available, or (4) a combination thereof (e.g., the UE 602 may download map data before driving, and continuously to download the updates while driving, including changes in map data (e.g., newly opened or closed street/highway, short term construction work). In some scenarios, the UE 602 may also be configured to stream the map data 606, which means the UE 602 does not download the map data before driving (e.g., the map data is streamed in real-time while the UE 602 is driving).

In a typical implementation, the map data 606 is transmitted from the server 604 (e.g., a cloud-based system), where the server 604 may utilize sensors and other data sources to collect and analyze information about the road network and traffic patterns. For example, the server 604 may receive and gather traffic/road information provided by a group of UEs (e.g., vehicles, roadside units (RSUs), etc.). In some examples, the information/data collected by a server from multiple UEs may be referred to as “fleet data” or “crowdsourced/crowdsourcing data.” This data may be processed and combined with other data, such as GPS/GNSS and/or camera data from multiple users (e.g., from other UEs/vehicles and/or the UE 602) to create a detailed map of the environment in real-time. Then, an application (e.g., for autonomous driving, navigation, positioning, etc.) of the UE 602 may access the map data 606 over a wireless network (e.g., a cellular or satellite network), and use the map data 606 to make decisions about speed, route, and other factors, etc. For example, the UE 602 may use the map data 606 to avoid road construction, traffic congestion, or accidents, and to optimize its route for efficiency and safety, etc. In some examples, as shown at 610, the UE 602 may also be configured to receive (additional) road/map information from another road entity 608, such as from another vehicle/UE, a roadside unit (RSU), or a traffic/road infrastructure (e.g., traffic lights), such as based on vehicle-to-everything (V2X) communication protocol/technology.

Map data with lane-level information, such as road-maps with lane-level connectivity, may play a crucial role in enhancing the safety, the efficiency, and/or the overall performance of autonomous driving systems and ADAS systems, and may also contribute to the realization of a safer and more connected transportation future. For purposes of the present disclosure, a map data with lane-level information/connectivity may be referred to as a “lane-map,” a “lane-level map,” “lane-map data,” and/or “lane-level map data,” etc., which may indicate that the map data includes information related to different lanes of a road. In addition, depending on the context, the term “map data” may be used interchangeably with the term “map.”

In some aspects, driving systems for vehicles (e.g., autonomous driving systems) may include a number of circuits or components. For instance, driving systems may include a system-on-chip (SoC), which is an integrated circuit that may integrate most or all of the components of a computer system or electronic system. These components in the system may include an on-chip central processing unit (CPU), memory interfaces, input/output devices and interfaces, and/or secondary storage interfaces. An SoC may also include other components, such as modems and a graphics processing unit (GPU). SoCs may also contain digital functions, analog functions, mixed-signal functions, and/or signal processing functions. An SoC may also integrate a microcontroller, a microprocessor, or several processor cores with peripherals (e.g., a GPU, Wi-Fi and cellular network radio modems, and/or one or more processors). Additionally, an SoC may integrate a microcontroller with advanced peripherals. Compared to a multi-chip architecture, an SoC with equivalent functionality may have reduced power consumption.

In addition, driving systems for vehicles may include an electronic control unit (ECU), which may also be referred to as an electronic control module (ECM). An ECU is an embedded system in automotive electronics that may control one or more of the electrical systems or subsystems in a vehicle. An ECU's main function may be to keep the engine working smoothly. For example, an ECU may control everything in the engine, including the wheel speed, braking power, ignition timing, idle speed, the air/fuel mixture, etc. On vehicles with an electronic fuel injection, an ECU may control the amount of fuel that enters the engine's cylinders. Modern vehicles have a number of different ECUs, which can include one or more of: an ECM, a powertrain control module (PCM), a transmission control module (TCM), a brake control module (BCM), a central control module (CCM), a central timing module (CTM), a general electronic module (GEM), a body control module (BCM), and a suspension control module (SCM). These ECUs may be referred to as a vehicle's computer, although technically they are all separate computers. An ECU may also include one or more SoCs. Some modern vehicles may have a large number of ECUs (e.g., up to 150 ECUs). Further, software may be embedded in ECUs. Managing the increasing complexity and number of ECUs in a vehicle is a challenge for original equipment manufacturers (OEMs). Also, automated driving may include certain technologies (e.g., advanced driver-assistance systems (ADAS) technologies) that assist drivers with the safe operation of a vehicle. Through a human-machine interface, these features (e.g., ADAS features) may increase car and road safety. ADAS features may use automated technology, such as sensors and cameras, to detect nearby obstacles or driver errors, and respond accordingly. ADAS features may enable various levels of autonomous driving.

The computing power needed for autonomous driving vehicles may be provided by powerful chips that produce a significant amount of heat. In some aspects, water cooling in these vehicles may have been utilized in order to operate the components within their operating limits. However, this may not be a desirable approach for these vehicles. For certain levels of automation (e.g., Society of Automotive Engineers (SAE) Level 3 and above), the driver may be distracted. In the event of a technical problem, the vehicle may give the driver a period of time before regaining control or reach a “safe harbor” (i.e., a safe place) autonomously. Increasing the period of time in which the vehicle can operate is a goal of autonomous vehicles.

If a technical problem occurs during autonomous driving, the vehicle may need to be able to reach a safe harbor (e.g., parking space) fully autonomously, which can take some time. Until now, this was just possible with degraded and thus reduced sensor technology (e.g., a minimum risk maneuver (MRM)). That is, until now, a rise in temperature of the chip that resulted in overheating while driving autonomously (e.g., due to a cooling issue in an ECU), may have been detected internally within the control unit with the SoC temperature increasing. If there is a rise in chip temperature (e.g., a chip reaches a threshold or maximum level of temperature), one manner in which this issue may be overcome is a minimum risk maneuver (MRM) with lowered sensor technology. However, these types of maneuvers may not always be possible with reduced sensor functionality. Thus, a rise in chip temperature may result in a relatively rapid degradation of the overall system if a minimum risk maneuver cannot be quickly performed. For example, a rise in temperature of a chip that results in overheating may result in a system degradation at the vehicle.

FIG. 7 is a diagram 700 illustrating an example flowchart for autonomous driving. More specifically, diagram 700 depicts an example flowchart for autonomous driving at an electronic control unit (ECU) of a vehicle. As shown in FIG. 7, diagram 700 includes ECU 702 of a vehicle and MRM ECU 704 of the vehicle. As depicted in FIG. 7, at 710, the flowchart may start for ECU 702. At 720, ECU 702 may turn on autonomous driving for the vehicle. At 730, ECU 702 may measure the temperature of a system-on-chip (SoC) at the vehicle (e.g., an SoC at the ECU 702). At 740, ECU 702 may determine whether the SoC temperature is too high (i.e., the SoC temperature is greater than or equal to a threshold level). If no at 740, ECU 702 may return to 720. If yes at 740, at 750, ECU 702 may communicate that the ECU 702 is not available (i.e., ECU 702 is not available to finish the process or perform a minimum risk maneuver based on the SoC temperature being too high). This may result in MRM ECU 704 taking over to finish the process. At 780, MRM ECU 704 may perform a minimum risk maneuver with a reduced sensor set. At 790, MRM ECU 704 may end the process.

As shown in FIG. 7, a minimum risk maneuver (MRM) may just be possible with degraded and thus reduced sensor technology. That is, as shown in FIG. 7, a rise in temperature of a chip (e.g., an SoC or ECU) that resulted in overheating while driving autonomously (e.g., due to a cooling issue in an SoC or ECU) may have been detected internally within the control unit with the SoC temperature increasing. As shown in FIG. 7, if there is a rise in chip temperature (e.g., a chip reaches a threshold or maximum level of temperature), one manner in which this issue may be overcome is a minimum risk maneuver (MRM) with lowered sensor technology. However, a rise in chip temperature may result in a relatively rapid degradation of the overall system if a minimum risk maneuver cannot be quickly performed. Based on the above, it may be beneficial to detect an imminent degradation for thermal reasons at an early stage, to enable the driver or vehicle to drive to a safe harbor (e.g., parking area). Also, it may be beneficial to perform procedures (e.g., minimum risk maneuvers (MRM)) with full sensor availability at the vehicle after detecting temperature issues or overheating at a chip (e.g., an SoC or ECU of the vehicle). It may also be beneficial to consider input factors for an imminent thermal degradation and react before the occurrence.

Aspects of the present disclosure may detect an imminent degradation of a vehicle to enable the driver or vehicle to reach a safe place (e.g., a safe harbor). For instance, aspects presented herein may detect an imminent degradation of a chip (e.g., SoC or ECU) at a vehicle for thermal reasons (e.g., overheating), and make the detection at an early enough stage to enable the driver or vehicle to reach a safe harbor (e.g., parking area) before the degradation occurs. Also, aspects presented herein may also perform procedures (e.g., a minimum risk maneuvers (MRMs)) with full sensor availability at the vehicle after detecting temperature issues or overheating at a chip (e.g., an SoC or ECU of the vehicle). In order to do so, aspects of the present disclosure may consider input factors for an imminent thermal degradation and react before the occurrence of the temperature issues or overheating at the chip. For example, aspects presented herein may determine that certain parameters (e.g., a set of temperature parameters, a pump status of the vehicle, an actual temperature of the SoC of the vehicle, an actual temperature of the ECU of the vehicle, a temperature of a liquid in a cooling system for the vehicle, or a flow rate of the liquid in the cooling system for the vehicle) are overheating or approaching a threshold temperature level. Based on this determination that a parameter is overheating or approaching a threshold temperature level (e.g., greater than or equal to the threshold temperature level), aspects presented herein may adjust or reduce a functionality of a portion of at least one of a system-on-chip (SoC) of the vehicle or an electronic control unit (ECU) of the vehicle. Also, based on this determination that a parameter is overheating or approaching a threshold temperature level (e.g., greater than or equal to the threshold temperature level), aspects presented herein may initiate the safe harbor maneuver for the vehicle.

Aspects presented herein may relate to thermal management in autonomous driving. For instance, if a chip (e.g., an SoC or ECU of the vehicle) overheats, aspects presented herein may give the autonomous vehicle enough time to reach a “safe harbor” autonomously. For example, aspects presented herein may allow for early detection of a chip overheating or approaching a threshold temperature, such that a vehicle or driver has enough time to reach a “safe harbor” (e.g., a safe space or parking spot) autonomously. Also, aspects presented herein may propose to add sensors in a cooling circuit to detect imminent thermal degradation of a parameter (e.g., coolant flow rate, ambient temperature, temperature gradients, pump status, etc.) in order to take early measures and to help the vehicle or driver reach a safe place (i.e., a safe harbor) to stop the vehicle autonomously. In some instances, aspects presented herein may utilize advanced temperature measures and/or thermal power degradation modes for autonomous driving. As shown herein, the detection of an imminent degradation for thermal reasons by aspects herein may consider more input factors than just SoC temperature, such as coolant flow rate, ambient temperature, temperature gradients, pump status, etc. Aspects presented herein may detect an imminent degradation for thermal reasons at an early stage, to enable the driver or vehicle to drive to a safe parking area. An early detection of issues in the cooling circuit can help to take early countermeasures.

FIG. 8 is a diagram 800 illustrating an example flowchart for autonomous driving. More specifically, diagram 800 depicts an example flowchart for autonomous driving at an electronic control unit (ECU) of a vehicle. As shown in FIG. 8, diagram 800 includes ECU 802 of a vehicle and MRM ECU 804 of the vehicle. As depicted in FIG. 8, at 810, the flowchart may start for ECU 802. At 820, ECU 802 may turn on autonomous driving for the vehicle. At 830, ECU 802 may measure the temperature of a system-on-chip (SoC) at the vehicle (e.g., an SoC at the ECU 802). At 840, ECU 802 may determine whether the SoC temperature is too high (i.e., the SoC temperature is greater than or equal to a threshold level). If no at 840, ECU 802 may return to step 820. If yes at 840, at 850, ECU 802 may communicate that the ECU 802 is not available (i.e., ECU 802 is not available to finish the process or perform a minimum risk maneuver based on the SoC temperature being too high). This may result in MRM ECU 804 taking over to finish the process. At 880, MRM ECU 804 may perform a minimum risk maneuver with a reduced sensor set. At 890, MRM ECU 804 may end the process. Please note that aspects presented herein may include system-in-system solutions (e.g., multiple systems in the same ECU). Accordingly, although FIG. 8 displays multiple ECUs (e.g., ECU 802 and MRM ECU 804), it is noted that the MRM solutions herein may be utilized at a single ECU. That is, the solutions shown at ECU 802 and MRM ECU 804 in FIG. 8 may occur within a single ECU.

As shown in FIG. 8, at 880, a minimum risk maneuver (MRM) may be utilized with degraded and reduced sensor technology. As shown in FIG. 8, if there is a rise in chip temperature (e.g., a chip reaches a threshold level of temperature), one manner in which this issue may be overcome is a minimum risk maneuver (MRM) with lowered sensor technology. However, a rise in chip temperature may result in a relatively rapid degradation of the overall system if a minimum risk maneuver cannot be quickly performed. As shown in FIG. 8, aspects presented herein may detect an imminent degradation for thermal reasons at an early stage, to enable the driver or vehicle to drive to a safe harbor (e.g., parking area). As further shown in FIG. 8, aspects presented herein may perform procedures (e.g., a minimum risk maneuver (MRM)) with full sensor availability at the vehicle after detecting temperature issues or overheating at a chip (e.g., an SoC or ECU of the vehicle). For instance, at 842, after measuring the SoC temperature at 830, ECU 802 may measure coolant factors (e.g., coolant flow rate, ambient temperature, temperature gradients, pump status, etc.). At 852, after measuring the coolant factors at 842, ECU 802 may determine whether cooling is sufficient for these factors/parameters (e.g., a set of temperature parameters, a pump status of the vehicle, an actual temperature of the SoC of the vehicle, an actual temperature of the ECU of the vehicle, a temperature of a liquid in a cooling system for the vehicle, or a flow rate of the liquid in the cooling system for the vehicle). If yes at 852, and cooling is sufficient for these factors/parameters, ECU 802 may again measure the SoC temperature at 830. If no at 852, and cooling is not sufficient for these factors/parameters, at 862, ECU 802 may adjust the SoC to a power saving mode (e.g., reduce a functionality of a portion of at least one of an SoC or an ECU of the vehicle). At 872, after adjusting the SoC to a power saving mode (e.g., reducing a functionality of a portion of at least one of an SoC or an ECU of the vehicle), ECU 802 may perform a safe harbor maneuver with a full sensor set (e.g., initiate a safe harbor maneuver for the vehicle with a full sensor capability). At 872, ECU 802 may also output an indication to perform a safe harbor maneuver for the vehicle. A safe harbor maneuver may be a driving maneuver that the vehicle may execute in order to go from a current driving condition to reach a safe harbor. Additionally, a minimum risk maneuver (MRM) may be a driving maneuver that the vehicle may execute in order to go from a current driving condition to reach a safe stop. At 892, ECU 802 may end the process.

As shown in FIG. 8, diagram 800 may measure or detect coolant factors of an autonomously driving vehicle. For instance, one of these factors may be to measure or detect the coolant temperature. As depicted in FIG. 8, aspects presented herein may utilize multiple approaches to detect an increase of coolant temperature. In one instance, aspects presented herein may perform a direct measurement with a temperature sensor in a cooling circuit. In another instance, aspects presented herein may perform an indirect measurement through combined data from multiple ECUs, which are connected to the same cooling circuit. Additionally, as shown in FIG. 8, aspects presented herein may include a separate path going from autonomous driving at 820 and not just measure the SoC temperature at 830, but also measure/detect all the coolant factors/parameters that are involved in this process at 842. If the cooling factors are not approaching a threshold level, the vehicle may just keep on autonomous driving. If the vehicle comes to a point where the cooling factors are approaching a threshold level, aspects presented herein may go into a power saving mode. This may not be a degradation of the entire ECU, but rather may just be a power saving mode (e.g., a power saving mode at the SoC or the ECU). Aspects presented herein may also include a capability to reach a safe harbor with all the sensors at the vehicle maintaining complete functionality. That is, because the ECU is not fully degraded, and aspects presented herein may perform a measurement of some of the coolant factors/parameters.

In some aspects, as shown in FIG. 8, if the measurement/detection of the cooling factors/parameters results in a needed cooling situation (e.g., a threshold cooling situation) which occurs before the SoC reaches a threshold or maximum temperature, a power saving mode may be entered to slow down or prevent heating up the SoC or ECU. For instance, aspects presented herein may detect an imminent degradation for thermal reasons at an early stage (e.g., when the threshold temperature level is approach), consider input factors for an imminent thermal degradation, and react before the occurrence. This reaction may be a specially defined power saving mode (e.g., at the SoC or ECU), which may allow the vehicle to maintain certain features (e.g., advanced driver-assistance systems (ADAS) features) to be fully running. This may also be performed while saving energy to prevent overheating, such as by shutting down certain features and functions of the SoC or ECU, which may not be needed to perform a driving task. Accordingly, aspects presented herein may measure/detect certain cooling factors/parameters, and if these cooling factors/parameters are approaching a threshold level (e.g., greater than or equal to a threshold level), aspects presented herein may reduce a functionality of an SoC or ECU, which may not be needed to perform a driving task, and then perform a safe harbor maneuver to reach a safe place.

As shown in FIG. 8, ECU 802 may obtain an indication of a set of parameters associated with the vehicle. At 842, ECU 802 may also measure the at least one parameter in the set of parameters to determine whether the at least one parameter in the set of parameters is greater than or equal to the threshold level. At 852, ECU 802 may also determine that at least one parameter in the set of parameters is greater than or equal to a threshold level. Also, ECU 802 may output an indication of the determination that the at least one parameter is greater than or equal to the threshold level. At 862, ECU 802 may also reduce, based on the indication to perform the safe harbor maneuver, a functionality of a portion of at least one of a system-on-chip (SoC) of the vehicle or an electronic control unit (ECU) of the vehicle. At 872, ECU 802 may also output an indication to perform a safe harbor maneuver for the vehicle based on the determination that the at least one parameter is greater than or equal to the threshold level. At 872, ECU 802 may also initiate the safe harbor maneuver for the vehicle based on the determination that the at least one parameter is greater than or equal to the threshold level.

FIG. 9 includes diagram 900 and diagram 950 illustrating an example diagram of a flow of coolant at a vehicle. More specifically, diagram 900 and diagram 950 depict an example diagram of a flow of coolant at a vehicle including a cold plate, SoC, and ECU. As shown in FIG. 9, diagram 900 includes pump 910, heat exchanger 912, ECU 920 including cold plate 922 and SoC 924, and flow of coolant 940. Each of the aforementioned components in diagram 900 (pump 910, heat exchanger 912, ECU 920 including cold plate 922 and SoC 924) are included in cooling circuit 930. As illustrated in FIG. 9, the flow of coolant 940 moves from pump 910 to ECU 920 and cold plate 922, then to heat exchanger 912, and then back to pump 910. As depicted in FIG. 9, if just the temperature of SoC 924 rises (e.g., the SoC temperature is greater than or equal to a threshold level), this may be due to a higher workload at the SoC. Accordingly, aspects presented herein may reduce a functionality at the SoC to solve this issue. As further shown in FIG. 9, diagram 950 includes pump 960, heat exchanger 962, ECU 970 including cold plate 972 and SoC 974, and flow of coolant 990. Each of the aforementioned components in diagram 950 (pump 960, heat exchanger 962, ECU 970 including cold plate 972 and SoC 974) are included in cooling circuit 980. As further illustrated in FIG. 9, the flow of coolant 990 moves from pump 960 to ECU 970 and cold plate 972, then to heat exchanger 962, and then back to pump 960. As depicted in FIG. 9, if the temperature of both coolant 990 and SoC 974 rise (e.g., both the coolant and SoC temperatures are greater than or equal to a threshold level), this may be due to a cooling issue (e.g., a failure at pump 960). Accordingly, aspects presented herein may notify the autonomous vehicle or driver of the vehicle that this cooling issue is an external problem (e.g., a failure at pump 960) that needs to be resolved.

As depicted in FIG. 9, certain cold plate designs (e.g., cold plate 922 and cold plate 972) may enable a temperature sensor to measure the coolant temperature. If not just the temperature of SoC 924, but also the temperature gradient of coolant (e.g., coolant 940 or coolant 990) rises above a threshold, it can be assumed that this is not caused by an increased operating rate of the SOC, but by external problems, such as a pump failure (e.g., failure of pump 910 and pump 960). This measurement may be based on a relative increase of temperature (AT), not the absolute value. In some instances, even if the cooling capacity decreases, there may still be a cooling effect on the SoC (e.g., SoC 924 or SoC 974). By doing so, aspects presented herein may save time and allow certain actions to be taken before the thermal performance limit of the SoC (e.g., SoC 924 or SoC 974) is reached.

FIG. 10 includes diagram 1000 and diagram 1050 illustrating an example diagram of a flow of coolant at a vehicle. More specifically, diagram 1000 and diagram 1050 depict an example diagram of a flow of coolant at a vehicle including multiple ECUs. As shown in FIG. 10, diagram 1000 includes pump 1010, heat exchanger 1012, ECU 1020, ECU 1021, ECU 1022, communication interface 1028, and flow of coolant 1040. Each of the aforementioned components in diagram 1000 (pump 1010, heat exchanger 1012, ECU 1020, ECU 1021, ECU 1022, communication interface 1028) are included in cooling circuit 1030. As illustrated in FIG. 10, the flow of coolant 1040 moves from pump 1010 to ECU 1020, then to ECU 1021, then to ECU 1022, then to heat exchanger 1012, and then back to pump 1010. As depicted in FIG. 10, if the temperature of an SoC increases in just one ECU (e.g., the SoC temperature in ECU 1020), this may be due to a higher workload. Accordingly, aspects presented herein may reduce a functionality at the SoC or ECU (e.g., ECU 1020 or SoC at ECU 1020) to solve this issue. As further shown in FIG. 10, diagram 1050 includes pump 1060, heat exchanger 1062, ECU 1070, ECU 1071, ECU 1072, communication interface 1078, and flow of coolant 1090. Each of the aforementioned components in diagram 1050 (pump 1060, heat exchanger 1062, ECU 1070, ECU 1071, ECU 1072, communication interface 1078) are included in cooling circuit 1080. As further illustrated in FIG. 10, the flow of coolant 1090 may move from pump 1060 to ECU 1070, then to ECU 1071, then to ECU 1072, then to heat exchanger 1062, and then back to pump 1060. As depicted in FIG. 10, if the temperature an SoC increases in all ECUs (e.g., the SoC temperature in ECU 1020, ECU 1021, and ECU 1022 are greater than or equal to a threshold level), this may be due to a cooling issue (e.g., a failure at pump 1060). Accordingly, aspects presented herein may notify the autonomous vehicle or the driver of the vehicle and the system that this cooling issue is an external problem (e.g., a failure at pump 1060) that needs to be resolved. In some instances, the ECU may react itself in the case of autonomous driving, thus, not just the driver may react.

As depicted in FIG. 10, an increase in temperature at an SoC without an increased or exceptional workload may indicate a problem in the cooling circuit. To reinforce this indication, the ECUs (e.g., ECU 1020, ECU 1021, and ECU 1022) may be used collectively. If several ECUs (e.g., ECU 1020, ECU 1021, and ECU 1022) show an increased SoC temperature without an increased workload, it can be assumed that there is a problem in the cooling circuit (e.g., a failure at pump 1060). This measurement may be based on a relative increase of temperature (ΔT), not the absolute value. In some instances, even if the cooling capacity decreases, there may still be a cooling effect on the SoC (e.g., an SoC at ECU 1020, ECU 1021, and/or ECU 1022). By doing so, aspects presented herein may save time and allow action to be taken before the thermal performance limit of the SoC (e.g., an SoC at ECU 1020, ECU 1021, and/or ECU 1022) is reached.

FIG. 11 is a graph 1100 illustrating temperature at a system-on-chip (SoC) charted against time. More specifically, graph 1100 depicts an SoC temperature including a threshold temperature graphed against time. As shown in FIG. 11, graph 1100 includes a number of different options for an estimated temperature rise at an SoC (e.g., estimated temperature rise 1110, estimated temperature rise 1120, and estimated temperature rise 1130). As depicted in FIG. 11, near the left side of the time portion of graph 1100, the SoC is within an operating temperature range (i.e., normal temperature variations due to ambient temperature change, workload variation, etc.). At a certain point, there may be a detection of threshold cooling factors, which may result in one of the three estimated temperature rises at the SoC (e.g., estimated temperature rise 1110, estimated temperature rise 1120, and estimated temperature rise 1130). As shown in FIG. 11, estimated temperature rise 1110 is an estimated temperature rise without action, thus, the ECU is not available before completing a safe harbor maneuver. Estimated temperature rise 1120 is an estimated temperature rise with SoC degradation with autonomous functions still active, thus, there is ECU degradation after completing a safe harbor maneuver. Also, estimated temperature rise 1130 is an estimated temperature rise with SoC degradation with autonomous functions still active, thus, there is no ECU degradation needed to reach final position. FIG. 11 also depicts that estimated temperature rise 1110 and estimated temperature rise 1120 may approach a threshold temperature for the SoC. For instance, the time needed to perform a safe harbor maneuver and reach a safe place to stop the vehicle autonomously may be equal to the time between the detection of the threshold cooling factors and the time that the estimated temperature rise 1120 reaches the threshold temperature.

Aspects presented herein include a number of novel aspects, such as an indirect measurement of certain malfunctions, which offers the advantage that the rest of the cooling system does not have to be intelligently designed. For instance, equipping a pump with self-monitoring and communication capability may be significantly more expensive than using existing ECUs intelligently or using a simple temperature sensor as additional hardware. An early detection of issues in the cooling circuit can help to take early countermeasures. Also, aspects presented herein include a novel aspect of SoC degradation resulting in autonomous power saving mode. The SoC autonomous power saving mode allows full functionality for autonomous driving, but at the same time a reduced power consumption to increase the time to a full degradation if a thermal issue occurs. This can be achieved by reducing the workload of the processor (e.g., not using comfort features of the vehicle anymore). Also, aspects presented herein may shut down certain portions of the SoC or ECU (e.g., not use the GPU for visualization of augmented reality features). Aspects presented herein may be utilized in a number of different cases. For instance, aspects presented herein may be utilized as a system improvement for original equipment manufacturers (OEMs) for autonomous driving (e.g., autonomous driving in SAE level 3 or higher). Further, aspects presented herein may be utilized with advanced cooling supervision for certain OEMs (e.g., mid-tier OEMs).

Aspects of the present disclosure may include a number of benefits or advantages. For instance, aspects presented herein may detect an imminent degradation of a chip (e.g., SoC or ECU) at a vehicle for thermal reasons (e.g., overheating), and make the detection at an early enough stage to enable the driver or vehicle to reach a safe harbor (e.g., parking area) before the degradation occurs. Additionally, aspects presented herein may also perform procedures (e.g., a minimum risk maneuvers (MRMs)) with full sensor availability at the vehicle after detecting temperature issues or overheating at a chip (e.g., an SoC or ECU of the vehicle). That is, aspects of the present disclosure may consider input factors for an imminent thermal degradation and react before the occurrence of the temperature issues or overheating at the chip. For example, aspects presented herein may determine that certain parameters (e.g., a set of temperature parameters, a pump status of the vehicle, an actual temperature of the SoC of the vehicle, an actual temperature of the ECU of the vehicle, a temperature of a liquid in a cooling system for the vehicle, or a flow rate of the liquid in the cooling system for the vehicle) are overheating or approaching a threshold temperature level. Based on this determination that a parameter is overheating or approaching a threshold temperature level (e.g., greater than or equal to the threshold temperature level), aspects presented herein may adjust or reduce a functionality of a portion of at least one of a system-on-chip (SoC) of the vehicle or an electronic control unit (ECU) of the vehicle. Further, based on this determination that a parameter is overheating or approaching a threshold temperature level (e.g., greater than or equal to the threshold temperature level), aspects presented herein may initiate the safe harbor maneuver for the vehicle.

FIG. 12 is a communication flow diagram 1200 of frame processing in accordance with one or more techniques of this disclosure. As shown in FIG. 12, diagram 1200 includes example communications between vehicle 1202 (e.g., a vehicle, a vehicle component, a system-on-chip (SoC), an electronic control unit (ECU), a user equipment (UE), a graphics processing unit (GPU), a central processing unit (CPU), or any apparatus that may perform communication), vehicle component 1204 (e.g., a vehicle, a vehicle component, a system-on-chip (SoC), an electronic control unit (ECU), a user equipment (UE), a graphics processing unit (GPU), a central processing unit (CPU), or any apparatus that may perform communication), and memory 1206 (e.g., a memory or a cache), in accordance with one or more techniques of this disclosure.

At 1210, vehicle 1202 may obtain an indication of a set of parameters associated with the vehicle (e.g., vehicle 1202 may obtain indication 1212 from vehicle component 1204). In some aspects, the set of parameters may be parameters that influence a temperature of at least one of a system-on-chip (SoC) of the vehicle or an electronic control unit (ECU) of the vehicle. Further, the parameters that influence the temperature of at least one of the SoC of the vehicle or the ECU of the vehicle may include one or more of: a set of temperature parameters, a pump status of the vehicle, an actual temperature of the SoC of the vehicle, an actual temperature of the ECU of the vehicle, a temperature of a liquid in a cooling system for the vehicle, or a flow rate of the liquid in the cooling system for the vehicle. The vehicle may be a fully autonomous driving vehicle, a partially autonomous driving vehicle, or a manual driving vehicle.

At 1220, vehicle 1202 may measure the at least one parameter in the set of parameters to determine whether the at least one parameter in the set of parameters is greater than or equal to the threshold level. In some aspects, measuring the at least one parameter may comprise: calculating one or more of at least one time parameter associated with the vehicle or at least one temperature parameter associated with the vehicle. Further, measuring the at least one parameter may comprise: measuring one or more parameters associated with at least one of a system-on-chip (SoC) of the vehicle or an electronic control unit (ECU) of the vehicle.

At 1230, vehicle 1202 may determine that at least one parameter in the set of parameters is greater than or equal to a threshold level. In some aspects, determining that the at least one parameter is greater than or equal to the threshold level may comprise: detecting, via at least one sensor at the vehicle, that the at least one parameter is greater than or equal to the threshold level. In some aspects, the set of parameters may be associated with at least one of a system-on-chip (SoC) of the vehicle or an electronic control unit (ECU) of the vehicle. The threshold level may be associated with a threshold impact on at least one of the SoC of the vehicle or the ECU of the vehicle. Also, the threshold impact on at least one of the SoC of the vehicle or the ECU of the vehicle may be at least one of: a minimum time for the vehicle to perform a safe harbor maneuver or the threshold impact on a trend of a temperature of at least one of the SoC of the vehicle or the ECU of the vehicle. In some aspects, the set of parameters may be at least one a set of time parameters or a set of temperature parameters, and the threshold level may be at least one a time threshold or a temperature threshold.

At 1240, vehicle 1202 may output an indication of the determination that the at least one parameter is greater than or equal to the threshold level. In some aspects, outputting the indication of the determination that the at least one parameter is greater than or equal to the threshold level may comprise transmitting the indication of the determination that the at least one parameter is greater than or equal to the threshold level (e.g., vehicle 1202 may transmit indication 1242 to vehicle component 1204). Also, outputting the indication of the determination that the at least one parameter is greater than or equal to the threshold level may comprise storing the indication of the determination that the at least one parameter is greater than or equal to the threshold level (e.g., vehicle 1202 may store indication 1244 in memory 1206).

At 1250, vehicle 1202 may output an indication to perform a safe harbor maneuver for the vehicle based on the determination that the at least one parameter is greater than or equal to the threshold level. In some aspects, outputting an indication to perform a safe harbor maneuver for the vehicle may comprise transmitting an indication to perform a safe harbor maneuver for the vehicle (e.g., vehicle 1202 may transmit indication 1252 to vehicle component 1204) or storing an indication to perform a safe harbor maneuver for the vehicle (e.g., vehicle 1202 may store indication 1254 in memory 1206). In some aspects, outputting the indication to perform the safe harbor maneuver may comprise: sending, to a driver of the vehicle, the indication to perform the safe harbor maneuver based on the determination that the at least one parameter is greater than or equal to the threshold level.

At 1260, vehicle 1202 may reduce, based on the indication to perform the safe harbor maneuver, a functionality of a portion of at least one of a system-on-chip (SoC) of the vehicle or an electronic control unit (ECU) of the vehicle. In some aspects, reducing the functionality of the portion of at least one of the SoC of the vehicle or the ECU of the vehicle may comprise: initiating, based on the determination, a power saving mode of at least one of the SoC of the vehicle or the ECU of the vehicle. Additionally, reducing the functionality of the portion of at least one of the SoC of the vehicle or the ECU of the vehicle may comprise at least one of: reducing a functionality of a graphics processing unit (GPU) of the SoC, reducing a functionality of a central processing unit (CPU) of the SoC, reducing a functionality of software associated with the SoC, or reducing a functionality of hardware associated with the SoC.

At 1270, vehicle 1202 may initiate the safe harbor maneuver for the vehicle based on the determination that the at least one parameter is greater than or equal to the threshold level. A safe harbor maneuver may be a driving maneuver that the vehicle may execute in order to take it from a current driving condition to reach safe harbor. Additionally, a minimum risk maneuver (MRM) may be a driving maneuver that the vehicle may execute in order to take it from a current driving condition to reach safe harbor.

FIG. 13 is a flowchart 1300 of an example method of image processing in accordance with one or more techniques of this disclosure. The method may be performed by a vehicle, a vehicle component, a system-on-chip (SoC), an electronic control unit (ECU), a user equipment (UE), a graphics processing unit (GPU), a central processing unit (CPU), or any apparatus that may perform communication, and/or any apparatus that may perform communication as used in connection with the examples of FIGS. 1-12.

At 1302, the vehicle may obtain an indication of a set of parameters associated with the vehicle, as described in connection with the examples in FIGS. 1-12. For example, as described in 1210 of FIG. 12, vehicle 1202 may obtain an indication of a set of parameters associated with the vehicle. Further, step 1302 may be performed by component 198 in FIG. 1. In some aspects, the set of parameters may be parameters that influence a temperature of at least one of a system-on-chip (SoC) of the vehicle or an electronic control unit (ECU) of the vehicle. Further, the parameters that influence the temperature of at least one of the SoC of the vehicle or the ECU of the vehicle may include one or more of: a set of temperature parameters, a pump status of the vehicle, an actual temperature of the SoC of the vehicle, an actual temperature of the ECU of the vehicle, a temperature of a liquid in a cooling system for the vehicle, or a flow rate of the liquid in the cooling system for the vehicle. The vehicle may be a fully autonomous driving vehicle, a partially autonomous driving vehicle, or a manual driving vehicle.

At 1306, the vehicle may determine that at least one parameter in the set of parameters is greater than or equal to a threshold level, as described in connection with the examples in FIGS. 1-12. For example, as described in 1230 of FIG. 12, vehicle 1202 may determine that at least one parameter in the set of parameters is greater than or equal to a threshold level. Further, step 1306 may be performed by component 198 in FIG. 1. In some aspects, determining that the at least one parameter is greater than or equal to the threshold level may comprise: detecting, via at least one sensor at the vehicle, that the at least one parameter is greater than or equal to the threshold level. In some aspects, the set of parameters may be associated with at least one of a system-on-chip (SoC) of the vehicle or an electronic control unit (ECU) of the vehicle. The threshold level may be associated with a threshold impact on at least one of the SoC of the vehicle or the ECU of the vehicle. Also, the threshold impact on at least one of the SoC of the vehicle or the ECU of the vehicle may be at least one of: a minimum time for the vehicle to perform a safe harbor maneuver or the threshold impact on a trend of a temperature of at least one of the SoC of the vehicle or the ECU of the vehicle. In some aspects, the set of parameters may be at least one a set of time parameters or a set of temperature parameters, and the threshold level may be at least one a time threshold or a temperature threshold.

At 1308, the vehicle may output an indication of the determination that the at least one parameter is greater than or equal to the threshold level, as described in connection with the examples in FIGS. 1-12. For example, as described in 1240 of FIG. 12, vehicle 1202 may output an indication of the determination that the at least one parameter is greater than or equal to the threshold level. Further, step 1308 may be performed by component 198 in FIG. 1. In some aspects, outputting the indication of the determination that the at least one parameter is greater than or equal to the threshold level may comprise transmitting the indication of the determination that the at least one parameter is greater than or equal to the threshold level (e.g., vehicle 1202 may transmit indication 1242 to vehicle component 1204). Also, outputting the indication of the determination that the at least one parameter is greater than or equal to the threshold level may comprise storing the indication of the determination that the at least one parameter is greater than or equal to the threshold level (e.g., vehicle 1202 may store indication 1244 in memory 1206).

FIG. 14 is a flowchart 1400 of an example method of image processing in accordance with one or more techniques of this disclosure. The method may be performed by a vehicle, a vehicle component, a system-on-chip (SoC), an electronic control unit (ECU), a user equipment (UE), a graphics processing unit (GPU), a central processing unit (CPU), or any apparatus that may perform communication, and/or any apparatus that may perform communication as used in connection with the examples of FIGS. 1-12.

At 1402, the vehicle may obtain an indication of a set of parameters associated with the vehicle, as described in connection with the examples in FIGS. 1-12. For example, as described in 1210 of FIG. 12, vehicle 1202 may obtain an indication of a set of parameters associated with the vehicle. Further, step 1402 may be performed by component 198 in FIG. 1. In some aspects, the set of parameters may be parameters that influence a temperature of at least one of a system-on-chip (SoC) of the vehicle or an electronic control unit (ECU) of the vehicle. Further, the parameters that influence the temperature of at least one of the SoC of the vehicle or the ECU of the vehicle may include one or more of: a set of temperature parameters, a pump status of the vehicle, an actual temperature of the SoC of the vehicle, an actual temperature of the ECU of the vehicle, a temperature of a liquid in a cooling system for the vehicle, or a flow rate of the liquid in the cooling system for the vehicle. The vehicle may be a fully autonomous driving vehicle, a partially autonomous driving vehicle, or a manual driving vehicle.

At 1404, the vehicle may measure the at least one parameter in the set of parameters to determine whether the at least one parameter in the set of parameters is greater than or equal to the threshold level, as described in connection with the examples in FIGS. 1-12. For example, as described in 1220 of FIG. 12, vehicle 1202 may measure the at least one parameter in the set of parameters to determine whether the at least one parameter in the set of parameters is greater than or equal to the threshold level. Further, step 1404 may be performed by component 198 in FIG. 1. In some aspects, measuring the at least one parameter may comprise: calculating one or more of at least one time parameter associated with the vehicle or at least one temperature parameter associated with the vehicle. Further, measuring the at least one parameter may comprise: measuring one or more parameters associated with at least one of a system-on-chip (SoC) of the vehicle or an electronic control unit (ECU) of the vehicle.

At 1406, the vehicle may determine that at least one parameter in the set of parameters is greater than or equal to a threshold level, as described in connection with the examples in FIGS. 1-12. For example, as described in 1230 of FIG. 12, vehicle 1202 may determine that at least one parameter in the set of parameters is greater than or equal to a threshold level. Further, step 1406 may be performed by component 198 in FIG. 1. In some aspects, determining that the at least one parameter is greater than or equal to the threshold level may comprise: detecting, via at least one sensor at the vehicle, that the at least one parameter is greater than or equal to the threshold level. In some aspects, the set of parameters may be associated with at least one of a system-on-chip (SoC) of the vehicle or an electronic control unit (ECU) of the vehicle. The threshold level may be associated with a threshold impact on at least one of the SoC of the vehicle or the ECU of the vehicle. Also, the threshold impact on at least one of the SoC of the vehicle or the ECU of the vehicle may be at least one of: a minimum time for the vehicle to perform a safe harbor maneuver or the threshold impact on a trend of a temperature of at least one of the SoC of the vehicle or the ECU of the vehicle. In some aspects, the set of parameters may be at least one a set of time parameters or a set of temperature parameters, and the threshold level may be at least one a time threshold or a temperature threshold.

At 1408, the vehicle may output an indication of the determination that the at least one parameter is greater than or equal to the threshold level, as described in connection with the examples in FIGS. 1-12. For example, as described in 1240 of FIG. 12, vehicle 1202 may output an indication of the determination that the at least one parameter is greater than or equal to the threshold level. Further, step 1408 may be performed by component 198 in FIG. 1. In some aspects, outputting the indication of the determination that the at least one parameter is greater than or equal to the threshold level may comprise transmitting the indication of the determination that the at least one parameter is greater than or equal to the threshold level (e.g., vehicle 1202 may transmit indication 1242 to vehicle component 1204). Also, outputting the indication of the determination that the at least one parameter is greater than or equal to the threshold level may comprise storing the indication of the determination that the at least one parameter is greater than or equal to the threshold level (e.g., vehicle 1202 may store indication 1244 in memory 1206).

At 1410, the vehicle may output an indication to perform a safe harbor maneuver for the vehicle based on the determination that the at least one parameter is greater than or equal to the threshold level, as described in connection with the examples in FIGS. 1-12. For example, as described in 1250 of FIG. 12, vehicle 1202 may output an indication to perform a safe harbor maneuver for the vehicle based on the determination that the at least one parameter is greater than or equal to the threshold level. Further, step 1410 may be performed by component 198 in FIG. 1. In some aspects, outputting an indication to perform a safe harbor maneuver for the vehicle may comprise transmitting an indication to perform a safe harbor maneuver for the vehicle (e.g., vehicle 1202 may transmit indication 1252 to vehicle component 1204) or storing an indication to perform a safe harbor maneuver for the vehicle (e.g., vehicle 1202 may store indication 1254 in memory 1206). In some aspects, outputting the indication to perform the safe harbor maneuver may comprise: sending, to a driver of the vehicle, the indication to perform the safe harbor maneuver based on the determination that the at least one parameter is greater than or equal to the threshold level.

At 1412, the vehicle may reduce, based on the indication to perform the safe harbor maneuver, a functionality of a portion of at least one of a system-on-chip (SoC) of the vehicle or an electronic control unit (ECU) of the vehicle, as described in connection with the examples in FIGS. 1-12. For example, as described in 1260 of FIG. 12, vehicle 1202 may reduce, based on the indication to perform the safe harbor maneuver, a functionality of a portion of at least one of a system-on-chip (SoC) of the vehicle or an electronic control unit (ECU) of the vehicle. Further, step 1412 may be performed by component 198 in FIG. 1. In some aspects, reducing the functionality of the portion of at least one of the SoC of the vehicle or the ECU of the vehicle may comprise: initiating, based on the determination, a power saving mode of at least one of the SoC of the vehicle or the ECU of the vehicle. Additionally, reducing the functionality of the portion of at least one of the SoC of the vehicle or the ECU of the vehicle may comprise at least one of: reducing a functionality of a graphics processing unit (GPU) of the SoC, reducing a functionality of a central processing unit (CPU) of the SoC, reducing a functionality of software associated with the SoC, or reducing a functionality of hardware associated with the SoC.

At 1414, the vehicle may initiate the safe harbor maneuver for the vehicle based on the determination that the at least one parameter is greater than or equal to the threshold level, as described in connection with the examples in FIGS. 1-12. For example, as described in 1270 of FIG. 12, vehicle 1202 may initiate the safe harbor maneuver for the vehicle based on the determination that the at least one parameter is greater than or equal to the threshold level. Further, step 1414 may be performed by component 198 in FIG. 1. A safe harbor maneuver may be a driving maneuver that the vehicle may execute in order to take it from a current driving condition to reach safe harbor. Additionally, a minimum risk maneuver (MRM) may be a driving maneuver that the vehicle may execute in order to take it from a current driving condition to reach safe harbor.

The subject matter described herein may be implemented to realize one or more benefits or advantages. For instance, the described processing techniques may be used by a vehicle, a vehicle component, a system-on-chip (SoC), an electronic control unit (ECU), a user equipment (UE), a graphics processing unit (GPU), a central processing unit (CPU), or any apparatus that may perform communication, or some other processor that may perform communication to implement the temperature adjustment techniques described herein. This may also be accomplished at a low cost compared to other communication techniques. Moreover, the communication techniques herein may improve or speed up data processing or execution. Further, the communication techniques herein may improve resource or data utilization and/or resource efficiency. Additionally, aspects of the present disclosure may utilize temperature adjustment techniques in order to improve memory bandwidth efficiency and/or increase processing speed at a vehicle, a vehicle component, a system-on-chip (SoC), an electronic control unit (ECU), a user equipment (UE), a graphics processing unit (GPU), a central processing unit (CPU).

FIG. 15 is a diagram 1500 illustrating an example of a hardware implementation for an apparatus 1504. The apparatus 1504 may be a UE, a component of a UE, a vehicle, a component of a vehicle, an SoC, an ECU, or may implement UE or vehicle functionality. In some aspects, the apparatus 1504 may include at least one cellular baseband processor 1524 (also referred to as a modem) coupled to one or more transceivers 1522 (e.g., cellular RF transceiver). The cellular baseband processor(s) 1524 may include at least one on-chip memory 1524′. In some aspects, the apparatus 1504 may further include one or more subscriber identity modules (SIM) cards 1520 and at least one application processor 1506 coupled to a secure digital (SD) card 1508 and a screen 1510. The application processor(s) 1506 may include on-chip memory 1506′. In some aspects, the apparatus 1504 may further include a Bluetooth module 1512, a WLAN module 1514, an SPS module 1516 (e.g., GNSS module), one or more sensor modules 1518 (e.g., barometric pressure sensor/altimeter; motion sensor such as inertial measurement unit (IMU), gyroscope, and/or accelerometer(s); light detection and ranging (LIDAR), radio assisted detection and ranging (RADAR), sound navigation and ranging (SONAR), magnetometer, audio and/or other technologies used for positioning), additional memory modules 1526, a power supply 1530, and/or a camera 1532. The Bluetooth module 1512, the WLAN module 1514, and the SPS module 1516 may include an on-chip transceiver (TRX) (or in some cases, just a receiver (RX)). The Bluetooth module 1512, the WLAN module 1514, and the SPS module 1516 may include their own dedicated antennas and/or utilize the antennas 1580 for communication. The cellular baseband processor(s) 1524 communicates through the transceiver(s) 1522 via one or more antennas 1580 with the UE 104 and/or with an RU associated with a network entity 1502. The cellular baseband processor(s) 1524 and the application processor(s) 1506 may each include a computer-readable medium/memory 1524′, 1506′, respectively. The additional memory modules 1526 may also be considered a computer-readable medium/memory. Each computer-readable medium/memory 1524′, 1506′, 1526 may be non-transitory. The cellular baseband processor(s) 1524 and the application processor(s) 1506 are each responsible for general processing, including the execution of software stored on the computer-readable medium/memory. The software, when executed by the cellular baseband processor(s) 1524/application processor(s) 1506, causes the cellular baseband processor(s) 1524/application processor(s) 1506 to perform the various functions described supra. The cellular baseband processor(s) 1524 and the application processor(s) 1506 are configured to perform the various functions described supra based at least in part of the information stored in the memory. That is, the cellular baseband processor(s) 1524 and the application processor(s) 1506 may be configured to perform a first subset of the various functions described supra without information stored in the memory and may be configured to perform a second subset of the various functions described supra based on the information stored in the memory. The computer-readable medium/memory may also be used for storing data that is manipulated by the cellular baseband processor(s) 1524/application processor(s) 1506 when executing software. The cellular baseband processor(s) 1524/application processor(s) 1506 may be a component of the UE 350 and may include the at least one memory 360 and/or at least one of the TX processor 368, the RX processor 356, and the controller/processor 359. In one configuration, the apparatus 1504 may be at least one processor chip (modem and/or application) and include just the cellular baseband processor(s) 1524 and/or the application processor(s) 1506, and in another configuration, the apparatus 1504 may be the entire UE (e.g., see UE 350 of FIG. 3) and include the additional modules of the apparatus 1504.

As discussed supra, the component 198 may be configured to obtain an indication of a set of parameters associated with the vehicle; measure the at least one parameter in the set of parameters to determine whether the at least one parameter in the set of parameters is greater than or equal to the threshold level; determine that at least one parameter in the set of parameters is greater than or equal to a threshold level; output an indication of the determination that the at least one parameter is greater than or equal to the threshold level; output an indication to perform a safe harbor maneuver for the vehicle based on the determination that the at least one parameter is greater than or equal to the threshold level; reduce, based on the indication to perform the safe harbor maneuver, a functionality of a portion of at least one of a system-on-chip (SoC) of the vehicle or an electronic control unit (ECU) of the vehicle; and initiate the safe harbor maneuver for the vehicle based on the determination that the at least one parameter is greater than or equal to the threshold level. The component 198 may be within the cellular baseband processor(s) 1524, the application processor(s) 1506, or both the cellular baseband processor(s) 1524 and the application processor(s) 1506. The component 198 may be one or more hardware components specifically configured to carry out the stated processes/algorithm, implemented by one or more processors configured to perform the stated processes/algorithm, stored within a computer-readable medium for implementation by one or more processors, or some combination thereof. When multiple processors are implemented, the multiple processors may perform the stated processes/algorithm individually or in combination. As shown, the apparatus 1504 may include a variety of components configured for various functions. In one configuration, the apparatus 1504, and in particular the cellular baseband processor(s) 1524 and/or the application processor(s) 1506, may include means for obtaining an indication of a set of parameters associated with the vehicle; means for measuring the at least one parameter in the set of parameters to determine whether the at least one parameter in the set of parameters is greater than or equal to the threshold level; means for determining that at least one parameter in the set of parameters is greater than or equal to a threshold level; means for outputting an indication of the determination that the at least one parameter is greater than or equal to the threshold level; means for outputting an indication to perform a safe harbor maneuver for the vehicle based on the determination that the at least one parameter is greater than or equal to the threshold level; means for reducing, based on the indication to perform the safe harbor maneuver, a functionality of a portion of at least one of a system-on-chip (SoC) of the vehicle or an electronic control unit (ECU) of the vehicle; and means for initiating the safe harbor maneuver for the vehicle based on the determination that the at least one parameter is greater than or equal to the threshold level. The means may be the component 198 of the apparatus 1504 configured to perform the functions recited by the means. As described supra, the apparatus 1504 may include the TX processor 368, the RX processor 356, and the controller/processor 359. As such, in one configuration, the means may be the TX processor 368, the RX processor 356, and/or the controller/processor 359 configured to perform the functions recited by the means.

It is understood that the specific order or hierarchy of blocks in the processes/flowcharts disclosed is an illustration of example approaches. Based upon design preferences, it is understood that the specific order or hierarchy of blocks in the processes/flowcharts may be rearranged. Further, some blocks may be combined or omitted. The accompanying method claims present elements of the various blocks in a sample order, and are not meant to be limited to the specific order or hierarchy presented.

The previous description is provided to enable any person skilled in the art to practice the various aspects described herein. Various modifications to these aspects will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other aspects. Thus, the claims are not intended to be limited to the aspects shown herein, but is to be accorded the full scope consistent with the language of the claims, wherein reference to an element in the singular is not intended to mean “one and only one” unless specifically so stated, but rather “one or more.” The word “exemplary” is used herein to mean “serving as an example, instance, or illustration.” Any aspect described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other aspects.

Unless specifically stated otherwise, the term “some” refers to one or more and the term “or” may be interpreted as “and/or” where context does not dictate otherwise. Combinations such as “at least one of A, B, or C,” “one or more of A, B, or C,” “at least one of A, B, and C,” “one or more of A, B, and C,” and “A, B, C, or any combination thereof” include any combination of A, B, and/or C, and may include multiples of A, multiples of B, or multiples of C. Specifically, combinations such as “at least one of A, B, or C,” “one or more of A, B, or C,” “at least one of A, B, and C,” “one or more of A, B, and C,” and “A, B, C, or any combination thereof” may be A only, B only, C only, A and B, A and C, B and C, or A and B and C, where any such combinations may contain one or more member or members of A, B, or C. All structural and functional equivalents to the elements of the various aspects described throughout this disclosure that are known or later come to be known to those of ordinary skill in the art are expressly incorporated herein by reference and are intended to be encompassed by the claims. Moreover, nothing disclosed herein is intended to be dedicated to the public regardless of whether such disclosure is explicitly recited in the claims. The words “module,” “mechanism,” “element,” “device,” and the like may not be a substitute for the word “means.” As such, no claim element is to be construed as a means plus function unless the element is expressly recited using the phrase “means for.”

In one or more examples, the functions described herein may be implemented in hardware, software, firmware, or any combination thereof. For example, although the term “processing unit” has been used throughout this disclosure, such processing units may be implemented in hardware, software, firmware, or any combination thereof. If any function, processing unit, technique described herein, or other module is implemented in software, the function, processing unit, technique described herein, or other module may be stored on or transmitted over as one or more instructions or code on a computer-readable medium.