CROSS-REFERENCE TO RELATED APPLICATION

This application claims the benefit of Korean Patent Application No. 10-2019-0102021 filed on Aug. 20, 2019, the entire contents of which is incorporated herein by reference for all purposes as if fully set forth herein.

BACKGROUND
Field of the Disclosure

The present disclosure relates to a lidar system, and more particularly, to a lidar system capable of detecting obstacles in a full distance and an autonomous driving system using the same.

Related Art

Vehicles, in accordance with the prime mover that is used, can be classified into an internal combustion engine vehicle, an external combustion engine vehicle, a gas turbine vehicle, an electric vehicle or the like.

An autonomous vehicle refers to a vehicle that can be driven by itself without operation by a driver or a passenger and an autonomous driving system refers to a system that monitors and controls such an autonomous vehicle so that the autonomous vehicle can be driven by itself.

In the autonomous driving system, there is an increasing demand for technologies that provide passengers or pedestrians with safer traveling environment as well as technologies that control the vehicle to quickly travel to a destination. To this end, autonomous vehicles require various sensors to quickly and accurately detect the surrounding terrains and objects in real time.

A lidar (Light Imaging Detection and Ranging) system radiates laser light pulses to an object and analyzes light reflected by the object, thereby being able to sense the size and disposition of the object and to measure the distance from the object.

SUMMARY

Most vehicle/robot lidar sensors use a high-power laser for detecting a long distance, and therefore have a limitation in detecting a minimum short distance (short distance). A laser beam includes a main beam and side lobes around the main beam. The lidar system detects an object by receiving a main beam reflected from the object.

The size of the side lobe is as small as 10⁻²to 10⁻⁶of the main beam. However, the size of the side lobe reflected at a distance of 1 m may be similar to the size of the main beam reflected from an object tens of meters away. This is due to the high reflectance of light in a short distance. As a result, the existing lidar system is difficult to detect obstacles in a short distance due to the light of the side lobe reflected in the short distance.

Due to the reduced sensitivity of the short distance, the minimum detection range of the most lidar systems is 50 cm or more and the proximity sensor such as an ultrasonic sensor may separately be required to detect the short distance within 50 cm.

The present disclosure aims to address the above-described needs and/or problems.

The present disclosure provides a lidar system capable of detecting obstacles in a full distance including a short distance and having no separate sensor for measuring a short distance, and an autonomous driving system using the same.

Aspects of the present disclosure are not limited to the above-mentioned aspects. That is, other aspects that are not mentioned may be obviously understood by those skilled in the art from the following disclosure.

In an aspect, a lidar system includes; a light emitter configured to include a light source generating a laser beam and a scanner moving the laser beam from the light source to scan an object with the laser beam; a receiving sensor configured to include a plurality of pixels converting a received signal of light received from the object into an electrical signal; and a sensor controller configured to synchronize the scanner with the receiving sensor and activate some pixel of the receiving sensor corresponding to a scan angle of the scanner.

The some of the laser beam is converted into the electrical signal by the activated pixels.

In another aspect, an autonomous driving system includes an autonomous driving device that receives the sensor data received from the lidar system and reflects the object information to the movement control of the vehicle.

BRIEF DESCRIPTION OF THE DRAWINGS

Accompanying drawings included as a part of the detailed description for helping understand the present disclosure provide embodiments of the present disclosure and are provided to describe technical features of the present disclosure with the detailed description.

FIG. 1 is a block diagram of a wireless communication system to which methods proposed in the disclosure are applicable.

FIG. 2 is a diagram showing an example of a signal transmission/reception method in a wireless communication system.

FIG. 3 shows an example of basic operations of a user equipment and a 5G network in a 5G communication system.

FIG. 4 shows an example of a basic operation between vehicles using 5G communication.

FIG. 5 is a diagram showing a vehicle according to an embodiment of the present disclosure.

FIG. 6 is a control block diagram of the vehicle according to an embodiment of the present disclosure.

FIG. 7 is a control block diagram of an autonomous device according to an embodiment of the present disclosure.

FIG. 8 is a signal flow diagram of an autonomous device according to an embodiment of the present disclosure.

FIG. 9 is a diagram referenced to describe a use scenario of a user according to an embodiment of the present disclosure.

FIG. 10 is a diagram showing an example of V2X communication to which the present disclosure can be applied.

FIG. 11 is a diagram showing a resource allocation method in sidelink in which the V2X is used.

FIG. 12 is a block diagram showing a lidar system according to an embodiment of the present disclosure.

FIG. 13 is a block diagram showing in detail a signal processor.

FIG. 14 is a diagram showing a detection distance of a lidar system according to an embodiment of the present disclosure.

FIG. 15 is a diagram showing a main lobe and side lobes of a laser beam.

FIG. 16 is a diagram showing the intensity of light of a laser beam received by a receiving sensor in a short distance.

FIG. 17 is a diagram showing an example of a scan angle of a laser beam.

FIG. 18 is a diagram showing pixels of a receiving sensor activated for each scan angle shown in FIG. 17.

FIG. 19 is a diagram showing the intensity of light of a laser beam received by the pixels of the receiving sensor activated for each scan angle.

FIG. 20 is a flowchart showing a method for removing noise of a received signal according to an embodiment of the present disclosure.

FIG. 21 is a diagram showing a method for detecting a valid waveform of a received signal.

FIG. 22 is a flowchart showing a method for removing noise of a received signal according to another embodiment of the present disclosure.

FIG. 23 is a diagram showing pixels of a receiving sensor activated for each scan angle upon detecting a short distance.

FIG. 24 is a diagram showing pixels of a receiving sensor activated for each scan angle upon detecting a long distance.

The accompanying drawings, which are included as part of the detailed description to assist understanding of the disclosure, illustrate embodiments of the disclosure and explain the technical features of the disclosure together with the detailed description.

DESCRIPTION OF EXEMPLARY EMBODIMENTS

Hereinafter, embodiments of the disclosure will be described in detail with reference to the attached drawings. The same or similar components are given the same reference numbers and redundant description thereof is omitted. The suffixes “module” and “unit” of elements herein are used for convenience of description and thus can be used interchangeably and do not have any distinguishable meanings or functions. Further, in the following description, if a detailed description of known techniques associated with the present disclosure would unnecessarily obscure the gist of the present disclosure, detailed description thereof will be omitted. In addition, the attached drawings are provided for easy understanding of embodiments of the disclosure and do not limit technical spirits of the disclosure, and the embodiments should be construed as including all modifications, equivalents, and alternatives falling within the spirit and scope of the embodiments.

While terms, such as “first”, “second”, etc., may be used to describe various components, such components must not be limited by the above terms. The above terms are used only to distinguish one component from another.

When an element is “coupled” or “connected” to another element, it should be understood that a third element may be present between the two elements although the element may be directly coupled or connected to the other element. When an element is “directly coupled” or “directly connected” to another element, it should be understood that no element is present between the two elements.

The singular forms are intended to include the plural forms as well, unless the context clearly indicates otherwise.

In addition, in the specification, it will be further understood that the terms “comprise” and “include” specify the presence of stated features, integers, steps, operations, elements, components, and/or combinations thereof, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or combinations.

Hereafter, a device that requires autonomous driving information and/or 5G communication (5th generation mobile communication) that an autonomous vehicle requires are described through a paragraph A to a paragraph G.

A. Example of Block Diagram of UE and 5G Network

FIG. 1 is a block diagram of a wireless communication system to which methods proposed in the disclosure are applicable.

Referring to FIG. 1, a device (autonomous device) including an autonomous module is defined as a first communication device (910 of FIG. 1), and a processor 911 can perform detailed autonomous operations.

A 5G network including another vehicle communicating with the autonomous device is defined as a second communication device (920 of FIG. 1), and a processor 921 can perform detailed autonomous operations.

The 5G network may be represented as the first communication device and the autonomous device may be represented as the second communication device.

For example, the first communication device or the second communication device may be a base station, a network node, a transmission terminal, a reception terminal, a wireless device, a wireless communication device, an autonomous device, or the like.

For example, a terminal or user equipment (UE) may include a vehicle, a cellular phone, a smart phone, a laptop computer, a digital broadcast terminal, personal digital assistants (PDAs), a portable multimedia player (PMP), a navigation device, a slate PC, a tablet PC, an ultrabook, a wearable device (e.g., a smartwatch, a smart glass and a head mounted display (HMD)), etc. For example, the HMD may be a display device worn on the head of a user. For example, the HMD may be used to realize VR, AR or MR. Referring to FIG. 1, the first communication device 910 and the second communication device 920 include processors 911 and 921, memories 914 and 924, one or more Tx/Rx radio frequency (RF) modules 915 and 925, Tx processors 912 and 922, Rx processors 913 and 923, and antennas 916 and 926. The Tx/Rx module is also referred to as a transceiver. Each Tx/Rx module 915 transmits a signal through each antenna 926. The processor implements the aforementioned functions, processes and/or methods. The processor 921 may be related to the memory 924 that stores program code and data. The memory may be referred to as a computer-readable medium. More specifically, the Tx processor 912 implements various signal processing functions with respect to L1 (i.e., physical layer) in DL (communication from the first communication device to the second communication device). The Rx processor implements various signal processing functions of L1 (i.e., physical layer).

UL (communication from the second communication device to the first communication device) is processed in the first communication device 910 in a way similar to that described in association with a receiver function in the second communication device 920. Each Tx/Rx module 925 receives a signal through each antenna 926. Each Tx/Rx module provides RF carriers and information to the Rx processor 923. The processor 921 may be related to the memory 924 that stores program code and data. The memory may be referred to as a computer-readable medium.

B. Signal Transmission/Reception Method in Wireless Communication System

FIG. 2 is a diagram showing an example of a signal transmission/reception method in a wireless communication system.

Referring to FIG. 2, when a UE is powered on or enters a new cell, the UE performs an initial cell search operation such as synchronization with a BS (S201). For this operation, the UE can receive a primary synchronization channel (P-SCH) and a secondary synchronization channel (S-SCH) from the BS to synchronize with the BS and acquire information such as a cell ID. In LTE and NR systems, the P-SCH and S-SCH are respectively called a primary synchronization signal (PSS) and a secondary synchronization signal (SSS). After initial cell search, the UE can acquire broadcast information in the cell by receiving a physical broadcast channel (PBCH) from the BS. Further, the UE can receive a downlink reference signal (DL RS) in the initial cell search step to check a downlink channel state. After initial cell search, the UE can acquire more detailed system information by receiving a physical downlink shared channel (PDSCH) according to a physical downlink control channel (PDCCH) and information included in the PDCCH (S202).

Meanwhile, when the UE initially accesses the BS or has no radio resource for signal transmission, the UE can perform a random access procedure (RACH) for the BS (steps S203 to S206). To this end, the UE can transmit a specific sequence as a preamble through a physical random access channel (PRACH) (S203 and S205) and receive a random access response (RAR) message for the preamble through a PDCCH and a corresponding PDSCH (S204 and S206). In the case of a contention-based RACH, a contention resolution procedure may be additionally performed.

After the UE performs the above-described process, the UE can perform PDCCH/PDSCH reception (S207) and physical uplink shared channel (PUSCH)/physical uplink control channel (PUCCH) transmission (S208) as normal uplink/downlink signal transmission processes. Particularly, the UE receives downlink control information (DCI) through the PDCCH. The UE monitors a set of PDCCH candidates in monitoring occasions set for one or more control element sets (CORESET) on a serving cell according to corresponding search space configurations. A set of PDCCH candidates to be monitored by the UE is defined in terms of search space sets, and a search space set may be a common search space set or a UE-specific search space set. CORESET includes a set of (physical) resource blocks having a duration of one to three OFDM symbols. A network can configure the UE such that the UE has a plurality of CORESETs. The UE monitors PDCCH candidates in one or more search space sets. Here, monitoring means attempting decoding of PDCCH candidate(s) in a search space. When the UE has successfully decoded one of PDCCH candidates in a search space, the UE determines that a PDCCH has been detected from the PDCCH candidate and performs PDSCH reception or PUSCH transmission on the basis of DCI in the detected PDCCH. The PDCCH can be used to schedule DL transmissions over a PDSCH and UL transmissions over a PUSCH. Here, the DCI in the PDCCH includes downlink assignment (i.e., downlink grant (DL grant)) related to a physical downlink shared channel and including at least a modulation and coding format and resource allocation information, or an uplink grant (UL grant) related to a physical uplink shared channel and including a modulation and coding format and resource allocation information.

An initial access (IA) procedure in a 5G communication system will be additionally described with reference to FIG. 2.

The UE can perform cell search, system information acquisition, beam alignment for initial access, and DL measurement on the basis of an SSB. The SSB is interchangeably used with a synchronization signal/physical broadcast channel (SS/PBCH) block.

The SSB includes a PSS, an SSS and a PBCH. The SSB is configured in four consecutive OFDM symbols, and a PSS, a PBCH, an SSS/PBCH or a PBCH is transmitted for each OFDM symbol. Each of the PSS and the SSS includes one OFDM symbol and 127 subcarriers, and the PBCH includes 3 OFDM symbols and 576 subcarriers.

Cell search refers to a process in which a UE acquires time/frequency synchronization of a cell and detects a cell identifier (ID) (e.g., physical layer cell ID (PCI)) of the cell. The PSS is used to detect a cell ID in a cell ID group and the SSS is used to detect a cell ID group. The PBCH is used to detect an SSB (time) index and a half-frame.

There are 336 cell ID groups and there are 3 cell IDs per cell ID group. A total of 1008 cell IDs are present. Information on a cell ID group to which a cell ID of a cell belongs is provided/acquired through an SSS of the cell, and information on the cell ID among 336 cell ID groups is provided/acquired through a PSS.

The SSB is periodically transmitted in accordance with SSB periodicity. A default SSB periodicity assumed by a UE during initial cell search is defined as 20 ms. After cell access, the SSB periodicity can be set to one of {5 ms, 10 ms, 20 ms, 40 ms, 80 ms, 160 ms} by a network (e.g., a BS).

Next, acquisition of system information (SI) will be described.

SI is divided into a master information block (MIB) and a plurality of system information blocks (SIBs). SI other than the MIB may be referred to as remaining minimum system information. The MIB includes information/parameter for monitoring a PDCCH that schedules a PDSCH carrying SIB1 (SystemInformationBlock1) and is transmitted by a BS through a PBCH of an SSB. SIB1 includes information related to availability and scheduling (e.g., transmission periodicity and SI-window size) of the remaining SIBs (hereinafter, SIBx, x is an integer equal to or greater than 2). SiBx is included in an SI message and transmitted over a PDSCH. Each SI message is transmitted within a periodically generated time window (i.e., SI-window).

A random access (RA) procedure in a 5G communication system will be additionally described with reference to FIG. 2.

A random access procedure is used for various purposes. For example, the random access procedure can be used for network initial access, handover, and UE-triggered UL data transmission. A UE can acquire UL synchronization and UL transmission resources through the random access procedure. The random access procedure is classified into a contention-based random access procedure and a contention-free random access procedure. A detailed procedure for the contention-based random access procedure is as follows.

A UE can transmit a random access preamble through a PRACH as Msg1 of a random access procedure in UL. Random access preamble sequences having different two lengths are supported. A long sequence length 839 is applied to subcarrier spacings of 1.25 kHz and 5 kHz and a short sequence length 139 is applied to subcarrier spacings of 15 kHz, 30 kHz, 60 kHz and 120 kHz.

When a BS receives the random access preamble from the UE, the BS transmits a random access response (RAR) message (Msg2) to the UE. A PDCCH that schedules a PDSCH carrying a RAR is CRC masked by a random access (RA) radio network temporary identifier (RNTI) (RA-RNTI) and transmitted. Upon detection of the PDCCH masked by the RA-RNTI, the UE can receive a RAR from the PDSCH scheduled by DCI carried by the PDCCH. The UE checks whether the RAR includes random access response information with respect to the preamble transmitted by the UE, that is, Msg1. Presence or absence of random access information with respect to Msg1 transmitted by the UE can be determined according to presence or absence of a random access preamble ID with respect to the preamble transmitted by the UE. If there is no response to Msg1, the UE can retransmit the RACH preamble less than a predetermined number of times while performing power ramping. The UE calculates PRACH transmission power for preamble retransmission on the basis of most recent pathloss and a power ramping counter.

The UE can perform UL transmission through Msg3 of the random access procedure over a physical uplink shared channel on the basis of the random access response information. Msg3 can include an RRC connection request and a UE ID. The network can transmit Msg4 as a response to Msg3, and Msg4 can be handled as a contention resolution message on DL. The UE can enter an RRC connected state by receiving Msg4.

C. Beam Management (BM) Procedure of 5G Communication System

A BM procedure can be divided into (1) a DL MB procedure using an SSB or a CSI-RS and (2) a UL BM procedure using a sounding reference signal (SRS). In addition, each BM procedure can include Tx beam swiping for determining a Tx beam and Rx beam swiping for determining an Rx beam.

The DL BM procedure using an SSB will be described.

Configuration of a beam report using an SSB is performed when channel state information (CSI)/beam is configured in RRC_CONNECTED.

- A UE receives a CSI-ResourceConfig IE including CSI-SSB-ResourceSetList for SSB resources used for BM from a BS. The RRC parameter “csi-SSB-ResourceSetList” represents a list of SSB resources used for beam management and report in one resource set. Here, an SSB resource set can be set as {SSBx1, SSBx2, SSBx3, SSBx4, . . . }. An SSB index can be defined in the range of 0 to 63.
- The UE receives the signals on SSB resources from the BS on the basis of the CSI-SSB-ResourceSetList.
- When CSI-RS reportConfig with respect to a report on SSBRI and reference signal received power (RSRP) is set, the UE reports the best SSBRI and RSRP corresponding thereto to the BS. For example, when reportQuantity of the CSI-RS reportConfig IE is set to ‘ssb-Index-RSRP’, the UE reports the best SSBRI and RSRP corresponding thereto to the BS.

When a CSI-RS resource is configured in the same OFDM symbols as an SSB and ‘QCL-TypeD’ is applicable, the UE can assume that the CSI-RS and the SSB are quasi co-located (QCL) from the viewpoint of ‘QCL-TypeD’. Here, QCL-TypeD may mean that antenna ports are quasi co-located from the viewpoint of a spatial Rx parameter. When the UE receives signals of a plurality of DL antenna ports in a QCL-TypeD relationship, the same Rx beam can be applied.

Next, a DL BM procedure using a CSI-RS will be described.

An Rx beam determination (or refinement) procedure of a UE and a Tx beam swiping procedure of a BS using a CSI-RS will be sequentially described. A repetition parameter is set to ‘ON’ in the Rx beam determination procedure of a UE and set to ‘OFF’ in the Tx beam swiping procedure of a BS.

First, the Rx beam determination procedure of a UE will be described.

- The UE receives an NZP CSI-RS resource set IE including an RRC parameter with respect to ‘repetition’ from a BS through RRC signaling. Here, the RRC parameter ‘repetition’ is set to ‘ON’.
- The UE repeatedly receives signals on resources in a CSI-RS resource set in which the RRC parameter ‘repetition’ is set to ‘ON’ in different OFDM symbols through the same Tx beam (or DL spatial domain transmission filters) of the BS.
- The UE determines an RX beam thereof.
- The UE skips a CSI report. That is, the UE can skip a CSI report when the RRC parameter ‘repetition’ is set to ‘ON’.

Next, the Tx beam determination procedure of a BS will be described.

- A UE receives an NZP CSI-RS resource set IE including an RRC parameter with respect to ‘repetition’ from the BS through RRC signaling. Here, the RRC parameter ‘repetition’ is related to the Tx beam swiping procedure of the BS when set to ‘OFF’.
- The UE receives signals on resources in a CSI-RS resource set in which the RRC parameter ‘repetition’ is set to ‘OFF’ in different DL spatial domain transmission filters of the BS.
- The UE selects (or determines) a best beam.
- The UE reports an ID (e.g., CRI) of the selected beam and related quality information (e.g., RSRP) to the BS. That is, when a CSI-RS is transmitted for BM, the UE reports a CRI and RSRP with respect thereto to the BS.

Next, the UL BM procedure using an SRS will be described.

- A UE receives RRC signaling (e.g., SRS-Config IE) including a (RRC parameter) purpose parameter set to ‘beam management” from a BS. The SRS-Config IE is used to set SRS transmission. The SRS-Config IE includes a list of SRS-Resources and a list of SRS-ResourceSets. Each SRS resource set refers to a set of SRS-resources.

The UE determines Tx beamforming for SRS resources to be transmitted on the basis of SRS-SpatialRelation Info included in the SRS-Config IE. Here, SRS-SpatialRelation Info is set for each SRS resource and indicates whether the same beamforming as that used for an SSB, a CSI-RS or an SRS will be applied for each SRS resource.

- When SRS-SpatialRelationInfo is set for SRS resources, the same beamforming as that used for the SSB, CSI-RS or SRS is applied. However, when SRS-SpatialRelationInfo is not set for SRS resources, the UE arbitrarily determines Tx beamforming and transmits an SRS through the determined Tx beamforming.

Next, a beam failure recovery (BFR) procedure will be described.

In a beamformed system, radio link failure (RLF) may frequently occur due to rotation, movement or beamforming blockage of a UE. Accordingly, NR supports BFR in order to prevent frequent occurrence of RLF. BFR is similar to a radio link failure recovery procedure and can be supported when a UE knows new candidate beams. For beam failure detection, a BS configures beam failure detection reference signals for a UE, and the UE declares beam failure when the number of beam failure indications from the physical layer of the UE reaches a threshold set through RRC signaling within a period set through RRC signaling of the BS. After beam failure detection, the UE triggers beam failure recovery by initiating a random access procedure in a PCell and performs beam failure recovery by selecting a suitable beam. (When the BS provides dedicated random access resources for certain beams, these are prioritized by the UE). Completion of the aforementioned random access procedure is regarded as completion of beam failure recovery.

D. URLLC (Ultra-Reliable and Low Latency Communication)

URLLC transmission defined in NR can refer to (1) a relatively low traffic size, (2) a relatively low arrival rate, (3) extremely low latency requirements (e.g., 0.5 and 1 ms), (4) relatively short transmission duration (e.g., 2 OFDM symbols), (5) urgent services/messages, etc. In the case of UL, transmission of traffic of a specific type (e.g., URLLC) needs to be multiplexed with another transmission (e.g., eMBB) scheduled in advance in order to satisfy more stringent latency requirements. In this regard, a method of providing information indicating preemption of specific resources to a UE scheduled in advance and allowing a URLLC UE to use the resources for UL transmission is provided.

NR supports dynamic resource sharing between eMBB and URLLC. eMBB and URLLC services can be scheduled on non-overlapping time/frequency resources, and URLLC transmission can occur in resources scheduled for ongoing eMBB traffic. An eMBB UE may not ascertain whether PDSCH transmission of the corresponding UE has been partially punctured and the UE may not decode a PDSCH due to corrupted coded bits. In view of this, NR provides a preemption indication. The preemption indication may also be referred to as an interrupted transmission indication.

With regard to the preemption indication, a UE receives DownlinkPreemption IE through RRC signaling from a BS. When the UE is provided with DownlinkPreemption IE, the UE is configured with INT-RNTI provided by a parameter int-RNTI in DownlinkPreemption IE for monitoring of a PDCCH that conveys DCI format 2_1. The UE is additionally configured with a corresponding set of positions for fields in DCI format 2_1 according to a set of serving cells and positionInDCI by INT-ConfigurationPerServing Cell including a set of serving cell indexes provided by servingCelllD, configured having an information payload size for DCI format 2_1 according to dci-Payloadsize, and configured with indication granularity of time-frequency resources according to timeFrequencySect.

The UE receives DCI format 2_1 from the BS on the basis of the DownlinkPreemption IE.

When the UE detects DCI format 2_1 for a serving cell in a configured set of serving cells, the UE can assume that there is no transmission to the UE in PRBs and symbols indicated by the DCI format 2_1 in a set of PRBs and a set of symbols in a last monitoring period before a monitoring period to which the DCI format 2_1 belongs. For example, the UE assumes that a signal in a time-frequency resource indicated according to preemption is not DL transmission scheduled therefor and decodes data on the basis of signals received in the remaining resource region.

E. mMTC (Massive MTC)

mMTC (massive Machine Type Communication) is one of 5G scenarios for supporting a hyper-connection service providing simultaneous communication with a large number of UEs. In this environment, a UE intermittently performs communication with a very low speed and mobility. Accordingly, a main goal of mMTC is operating a UE for a long time at a low cost. With respect to mMTC, 3GPP deals with MTC and NB (NarrowBand)-IoT.

mMTC has features such as repetitive transmission of a PDCCH, a PUCCH, a PDSCH (physical downlink shared channel), a PUSCH, etc., frequency hopping, retuning, and a guard period.

That is, a PUSCH (or a PUCCH (particularly, a long PUCCH) or a PRACH) including specific information and a PDSCH (or a PDCCH) including a response to the specific information are repeatedly transmitted. Repetitive transmission is performed through frequency hopping, and for repetitive transmission, (RF) retuning from a first frequency resource to a second frequency resource is performed in a guard period and the specific information and the response to the specific information can be transmitted/received through a narrowband (e.g., 6 resource blocks (RBs) or 1 RB).

F. Basic Operation Between Autonomous Vehicles Using 5G Communication

FIG. 3 shows an example of basic operations of an autonomous vehicle and a 5G network in a 5G communication system.

The autonomous vehicle transmits specific information to the 5G network (S1). The specific information may include autonomous driving related information. In addition, the 5G network can determine whether to remotely control the vehicle (S2). Here, the 5G network may include a server or a module which performs remote control related to autonomous driving. In addition, the 5G network can transmit information (or signal) related to remote control to the autonomous vehicle (S3).

G. Applied Operations Between Autonomous Vehicle and 5G Network in 5G Communication System

Hereinafter, the operation of an autonomous vehicle using 5G communication will be described in more detail with reference to wireless communication technology (BM procedure, URLLC, mMTC, etc.) described in FIGS. 1 and 2.

First, a basic procedure of an applied operation to which a method proposed by the present disclosure which will be described later and eMBB of 5G communication are applied will be described.

As in steps S1 and S3 of FIG. 3, the autonomous vehicle performs an initial access procedure and a random access procedure with the 5G network prior to step S1 of FIG. 3 in order to transmit/receive signals, information and the like to/from the 5G network.

More specifically, the autonomous vehicle performs an initial access procedure with the 5G network on the basis of an SSB in order to acquire DL synchronization and system information. A beam management (BM) procedure and a beam failure recovery procedure may be added in the initial access procedure, and quasi-co-location (QCL) relation may be added in a process in which the autonomous vehicle receives a signal from the 5G network.

In addition, the autonomous vehicle performs a random access procedure with the 5G network for UL synchronization acquisition and/or UL transmission. The 5G network can transmit, to the autonomous vehicle, a UL grant for scheduling transmission of specific information. Accordingly, the autonomous vehicle transmits the specific information to the 5G network on the basis of the UL grant. In addition, the 5G network transmits, to the autonomous vehicle, a DL grant for scheduling transmission of 5G processing results with respect to the specific information. Accordingly, the 5G network can transmit, to the autonomous vehicle, information (or a signal) related to remote control on the basis of the DL grant.

Next, a basic procedure of an applied operation to which a method proposed by the present disclosure which will be described later and URLLC of 5G communication are applied will be described.

As described above, an autonomous vehicle can receive DownlinkPreemption IE from the 5G network after the autonomous vehicle performs an initial access procedure and/or a random access procedure with the 5G network. Then, the autonomous vehicle receives DCI format 2_1 including a preemption indication from the 5G network on the basis of DownlinkPreemption IE. The autonomous vehicle does not perform (or expect or assume) reception of eMBB data in resources (PRBs and/or OFDM symbols) indicated by the preemption indication. Thereafter, when the autonomous vehicle needs to transmit specific information, the autonomous vehicle can receive a UL grant from the 5G network.

Next, a basic procedure of an applied operation to which a method proposed by the present disclosure which will be described later and mMTC of 5G communication are applied will be described.

Description will focus on parts in the steps of FIG. 3 which are changed according to application of mMTC.

In step S1 of FIG. 3, the autonomous vehicle receives a UL grant from the 5G network in order to transmit specific information to the 5G network. Here, the UL grant may include information on the number of repetitions of transmission of the specific information and the specific information may be repeatedly transmitted on the basis of the information on the number of repetitions. That is, the autonomous vehicle transmits the specific information to the 5G network on the basis of the UL grant. Repetitive transmission of the specific information may be performed through frequency hopping, the first transmission of the specific information may be performed in a first frequency resource, and the second transmission of the specific information may be performed in a second frequency resource. The specific information can be transmitted through a narrowband of 6 resource blocks (RBs) or 1 RB.

H. Autonomous Driving Operation Between Vehicles Using 5G Communication

FIG. 4 shows an example of a basic operation between vehicles using 5G communication.

A first vehicle transmits specific information to a second vehicle (S61). The second vehicle transmits a response to the specific information to the first vehicle (S62).

Meanwhile, a configuration of an applied operation between vehicles may depend on whether the 5G network is directly (sidelink communication transmission mode 3) or indirectly (sidelink communication transmission mode 4) involved in resource allocation for the specific information and the response to the specific information.

Next, an applied operation between vehicles using 5G communication will be described.

First, a method in which a 5G network is directly involved in resource allocation for signal transmission/reception between vehicles will be described.

The 5G network can transmit DCI format 5A to the first vehicle for scheduling of mode-3 transmission (PSCCH and/or PSSCH transmission). Here, a physical sidelink control channel (PSCCH) is a 5G physical channel for scheduling of transmission of specific information a physical sidelink shared channel (PSSCH) is a 5G physical channel for transmission of specific information. In addition, the first vehicle transmits SCI format 1 for scheduling of specific information transmission to the second vehicle over a PSCCH. Then, the first vehicle transmits the specific information to the second vehicle over a PSSCH.

Next, a method in which a 5G network is indirectly involved in resource allocation for signal transmission/reception will be described.

The first vehicle senses resources for mode-4 transmission in a first window. Then, the first vehicle selects resources for mode-4 transmission in a second window on the basis of the sensing result. Here, the first window refers to a sensing window and the second window refers to a selection window. The first vehicle transmits SCI format 1 for scheduling of transmission of specific information to the second vehicle over a PSCCH on the basis of the selected resources. Then, the first vehicle transmits the specific information to the second vehicle over a PSSCH.

The above-described 5G communication technology can be combined with methods proposed in the present disclosure which will be described later and applied or can complement the methods proposed in the present disclosure to make technical features of the methods concrete and clear.

Driving

(1) Exterior of Vehicle

FIG. 5 is a diagram showing a vehicle according to an embodiment of the present disclosure.

Referring to FIG. 5, a vehicle 10 according to an embodiment of the present disclosure is defined as a transportation means traveling on roads or railroads. The vehicle 10 includes a car, a train and a motorcycle. The vehicle 10 may include an internal-combustion engine vehicle having an engine as a power source, a hybrid vehicle having an engine and a motor as a power source, and an electric vehicle having an electric motor as a power source. The vehicle 10 may be a private own vehicle. The vehicle 10 may be a shared vehicle. The vehicle 10 may be an autonomous vehicle.

(2) Components of Vehicle

FIG. 6 is a control block diagram of the vehicle according to an embodiment of the present disclosure.

Referring to FIG. 6, the vehicle 10 may include a user interface device 200, an object detection device 210, a communication device 220, a driving operation device 230, a main ECU 240, a driving control device 250, an autonomous driving device 260, a sensing unit 270, and a position data generation device 280. The object detection device 210, the communication device 220, the driving operation device 230, the main ECU 240, the driving control device 250, the autonomous driving device 260, the sensing unit 270 and the position data generation device 280 may be realized by electronic devices which generate electric signals and exchange the electric signals from one another.

1) User Interface Device

The user interface device 200 is a device for communication between the vehicle 10 and a user. The user interface device 200 can receive user input and provide information generated in the vehicle 10 to the user. The vehicle 10 can realize a user interface (UI) or user experience (UX) through the user interface device 200. The user interface device 200 may include an input device, an output device and a user monitoring device.

2) Object Detection Device

The object detection device 210 can generate information about objects outside the vehicle 10. Information about an object can include at least one of information on presence or absence of the object, positional information of the object, information on a distance between the vehicle 10 and the object, and information on a relative speed of the vehicle 10 with respect to the object. The object detection device 210 can detect objects outside the vehicle 10. The object detection device 210 may include at least one sensor which can detect objects outside the vehicle 10. The object detection device 210 may include at least one of a camera, a radar, a lidar, an ultrasonic sensor and an infrared sensor. The object detection device 210 can provide data about an object generated on the basis of a sensing signal generated from a sensor to at least one electronic device included in the vehicle.

2.1) Camera

The camera can generate information about objects outside the vehicle 10 using images. The camera may include at least one lens, at least one image sensor, and at least one processor which is electrically connected to the image sensor, processes received signals and generates data about objects on the basis of the processed signals.

The camera may be at least one of a mono camera, a stereo camera and an around view monitoring (AVM) camera. The camera can acquire positional information of objects, information on distances to objects, or information on relative speeds with respect to objects using various image processing algorithms. For example, the camera can acquire information on a distance to an object and information on a relative speed with respect to the object from an acquired image on the basis of change in the size of the object over time. For example, the camera may acquire information on a distance to an object and information on a relative speed with respect to the object through a pin-hole model, road profiling, or the like. For example, the camera may acquire information on a distance to an object and information on a relative speed with respect to the object from a stereo image acquired from a stereo camera on the basis of disparity information.

The camera may be attached at a portion of the vehicle at which FOV (field of view) can be secured in order to photograph the outside of the vehicle. The camera may be disposed in proximity to the front windshield inside the vehicle in order to acquire front view images of the vehicle. The camera may be disposed near a front bumper or a radiator grill. The camera may be disposed in proximity to a rear glass inside the vehicle in order to acquire rear view images of the vehicle. The camera may be disposed near a rear bumper, a trunk or a tail gate. The camera may be disposed in proximity to at least one of side windows inside the vehicle in order to acquire side view images of the vehicle. Alternatively, the camera may be disposed near a side mirror, a fender or a door.

2.2) Radar

The radar can generate information about an object outside the vehicle using electromagnetic waves. The radar may include an electromagnetic wave transmitter, an electromagnetic wave receiver, and at least one processor which is electrically connected to the electromagnetic wave transmitter and the electromagnetic wave receiver, processes received signals and generates data about an object on the basis of the processed signals. The radar may be realized as a pulse radar or a continuous wave radar in terms of electromagnetic wave emission. The continuous wave radar may be realized as a frequency modulated continuous wave (FMCW) radar or a frequency shift keying (FSK) radar according to signal waveform. The radar can detect an object through electromagnetic waves on the basis of TOF (Time of Flight) or phase shift and detect the position of the detected object, a distance to the detected object and a relative speed with respect to the detected object. The radar may be disposed at an appropriate position outside the vehicle in order to detect objects positioned in front of, behind or on the side of the vehicle.

2.3) Lidar

The lidar can generate information about an object outside the vehicle 10 using a laser beam. The lidar may include a light transmitter, a light receiver, and at least one processor which is electrically connected to the light transmitter and the light receiver, processes received signals and generates data about an object on the basis of the processed signal. The lidar may be realized according to TOF or phase shift. The lidar may be realized as a driven type or a non-driven type. A driven type lidar may be rotated by a motor and detect an object around the vehicle 10. A non-driven type lidar may detect an object positioned within a predetermined range from the vehicle according to light steering. The vehicle 10 may include a plurality of non-drive type lidars. The lidar can detect an object through a laser beam on the basis of TOF (Time of Flight) or phase shift and detect the position of the detected object, a distance to the detected object and a relative speed with respect to the detected object. The lidar may be disposed at an appropriate position outside the vehicle in order to detect objects positioned in front of, behind or on the side of the vehicle.

3) Communication Device

The communication device 220 can exchange signals with devices disposed outside the vehicle 10. The communication device 220 can exchange signals with at least one of infrastructure (e.g., a server and a broadcast station), another vehicle and a terminal. The communication device 220 may include a transmission antenna, a reception antenna, and at least one of a radio frequency (RF) circuit and an RF element which can implement various communication protocols in order to perform communication.

For example, the communication device can exchange signals with external devices on the basis of C-V2X (Cellular V2X). For example, C-V2X can include sidelink communication based on LTE and/or sidelink communication based on NR. Details related to C-V2X will be described later.

For example, the communication device can exchange signals with external devices on the basis of DSRC (Dedicated Short Range Communications) or WAVE (Wireless Access in Vehicular Environment) standards based on IEEE 802.11p PHY/MAC layer technology and IEEE 1609 Network/Transport layer technology. DSRC (or WAVE standards) is communication specifications for providing an intelligent transport system (ITS) service through short-range dedicated communication between vehicle-mounted devices or between a roadside device and a vehicle-mounted device. DSRC may be a communication scheme that can use a frequency of 5.9 GHz and have a data transfer rate in the range of 3 Mbps to 27 Mbps. IEEE 802.11p may be combined with IEEE 1609 to support DSRC (or WAVE standards).

The communication device of the present disclosure can exchange signals with external devices using only one of C-V2X and DSRC. Alternatively, the communication device of the present disclosure can exchange signals with external devices using a hybrid of C-V2X and DSRC.

4) Driving Operation Device

The driving operation device 230 is a device for receiving user input for driving. In a manual mode, the vehicle 10 may be driven on the basis of a signal provided by the driving operation device 230. The driving operation device 230 may include a steering input device (e.g., a steering wheel), an acceleration input device (e.g., an acceleration pedal) and a brake input device (e.g., a brake pedal).

5) Main ECU

The main ECU 240 can control the overall operation of at least one electronic device included in the vehicle 10.

6) Driving Control Device

The driving control device 250 is a device for electrically controlling various vehicle driving devices included in the vehicle 10. The driving control device 250 may include a power train driving control device, a chassis driving control device, a door/window driving control device, a safety device driving control device, a lamp driving control device, and an air-conditioner driving control device. The power train driving control device may include a power source driving control device and a transmission driving control device. The chassis driving control device may include a steering driving control device, a brake driving control device and a suspension driving control device. Meanwhile, the safety device driving control device may include a seat belt driving control device for seat belt control.

The driving control device 250 includes at least one electronic control device (e.g., a control ECU (Electronic Control Unit)).

The driving control device 250 can control vehicle driving devices on the basis of signals received by the autonomous driving device 260. For example, the driving control device 250 can control a power train, a steering device and a brake device on the basis of signals received by the autonomous driving device 260.

7) Autonomous Device

The autonomous driving device 260 can generate a route for self-driving on the basis of acquired data. The autonomous driving device 260 can generate a driving plan for traveling along the generated route. The autonomous driving device 260 can generate a signal for controlling movement of the vehicle according to the driving plan. The autonomous driving device 260 can provide the signal to the driving control device 250.

The autonomous driving device 260 can implement at least one ADAS (Advanced Driver Assistance System) function. The ADAS can implement at least one of ACC (Adaptive Cruise Control), AEB (Autonomous Emergency Braking), FCW (Forward Collision Warning), LKA (Lane Keeping Assist), LCA (Lane Change Assist), TFA (Target Following Assist), BSD (Blind Spot Detection), HBA (High Beam Assist), APS (Auto Parking System), a PD collision warning system, TSR (Traffic Sign Recognition), TSA (Traffic Sign Assist), NV (Night Vision), DSM (Driver Status Monitoring) and TJA (Traffic Jam Assist).

The autonomous driving device 260 can perform switching from a self-driving mode to a manual driving mode or switching from the manual driving mode to the self-driving mode. For example, the autonomous driving device 260 can switch the mode of the vehicle 10 from the self-driving mode to the manual driving mode or from the manual driving mode to the self-driving mode on the basis of a signal received from the user interface device 200.

8) Sensing Unit

The sensing unit 270 can detect a state of the vehicle. The sensing unit 270 may include at least one of an internal measurement unit (IMU) sensor, a collision sensor, a wheel sensor, a speed sensor, an inclination sensor, a weight sensor, a heading sensor, a position module, a vehicle forward/backward movement sensor, a battery sensor, a fuel sensor, a tire sensor, a steering sensor, a temperature sensor, a humidity sensor, an ultrasonic sensor, an illumination sensor, and a pedal position sensor. Further, the IMU sensor may include one or more of an acceleration sensor, a gyro sensor and a magnetic sensor.

The sensing unit 270 can generate vehicle state data on the basis of a signal generated from at least one sensor. Vehicle state data may be information generated on the basis of data detected by various sensors included in the vehicle. The sensing unit 270 may generate vehicle attitude data, vehicle motion data, vehicle yaw data, vehicle roll data, vehicle pitch data, vehicle collision data, vehicle orientation data, vehicle angle data, vehicle speed data, vehicle acceleration data, vehicle tilt data, vehicle forward/backward movement data, vehicle weight data, battery data, fuel data, tire pressure data, vehicle internal temperature data, vehicle internal humidity data, steering wheel rotation angle data, vehicle external illumination data, data of a pressure applied to an acceleration pedal, data of a pressure applied to a brake panel, etc.

9) Position Data Generation Device

The position data generation device 280 can generate position data of the vehicle 10. The position data generation device 280 may include at least one of a global positioning system (GPS) and a differential global positioning system (DGPS). The position data generation device 280 can generate position data of the vehicle 10 on the basis of a signal generated from at least one of the GPS and the DGPS. According to an embodiment, the position data generation device 280 can correct position data on the basis of at least one of the inertial measurement unit (IMU) sensor of the sensing unit 270 and the camera of the object detection device 210. The position data generation device 280 may also be called a global navigation satellite system (GNSS).

The vehicle 10 may include an internal communication system 50. The plurality of electronic devices included in the vehicle 10 can exchange signals through the internal communication system 50. The signals may include data. The internal communication system 50 can use at least one communication protocol (e.g., CAN, LIN, FlexRay, MOST or Ethernet).

(3) Components of Autonomous Device

FIG. 7 is a control block diagram of the autonomous device according to an embodiment of the present disclosure.

Referring to FIG. 7, the autonomous driving device 260 may include a memory 140, a processor 170, an interface 180 and a power supply 190.

The memory 140 is electrically connected to the processor 170. The memory 140 can store basic data with respect to units, control data for operation control of units, and input/output data. The memory 140 can store data processed in the processor 170. Hardware-wise, the memory 140 can be configured as at least one of a ROM, a RAM, an EPROM, a flash drive and a hard drive. The memory 140 can store various types of data for overall operation of the autonomous driving device 260, such as a program for processing or control of the processor 170. The memory 140 may be integrated with the processor 170. According to an embodiment, the memory 140 may be categorized as a subcomponent of the processor 170.

The interface 180 can exchange signals with at least one electronic device included in the vehicle 10 in a wired or wireless manner. The interface 180 can exchange signals with at least one of the object detection device 210, the communication device 220, the driving operation device 230, the main ECU 240, the driving control device 250, the sensing unit 270 and the position data generation device 280 in a wired or wireless manner. The interface 180 can be configured using at least one of a communication module, a terminal, a pin, a cable, a port, a circuit, an element and a device.

The power supply 190 can provide power to the autonomous driving device 260. The power supply 190 can be provided with power from a power source (e.g., a battery) included in the vehicle 10 and supply the power to each unit of the autonomous driving device 260. The power supply 190 can operate according to a control signal supplied from the main ECU 240. The power supply 190 may include a switched-mode power supply (SMPS).

The processor 170 can be electrically connected to the memory 140, the interface 180 and the power supply 190 and exchange signals with these components. The processor 170 can be realized using at least one of application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), processors, controllers, micro-controllers, microprocessors, and electronic units for executing other functions.

The processor 170 can be operated by power supplied from the power supply 190. The processor 170 can receive data, process the data, generate a signal and provide the signal while power is supplied thereto.

The processor 170 can receive information from other electronic devices included in the vehicle 10 through the interface 180. The processor 170 can provide control signals to other electronic devices in the vehicle 10 through the interface 180.

The autonomous driving device 260 may include at least one printed circuit board (PCB). The memory 140, the interface 180, the power supply 190 and the processor 170 may be electrically connected to the PCB.

(4) Operation of Autonomous Device

FIG. 8 is a diagram showing a signal flow in an autonomous vehicle according to an embodiment of the present disclosure.

1) Reception Operation

Referring to FIG. 8, the processor 170 can perform a reception operation. The processor 170 can receive data from at least one of the object detection device 210, the communication device 220, the sensing unit 270 and the position data generation device 280 through the interface 180. The processor 170 can receive object data from the object detection device 210. The processor 170 can receive HD map data from the communication device 220. The processor 170 can receive vehicle state data from the sensing unit 270. The processor 170 can receive position data from the position data generation device 280.

2) Processing/Determination Operation

The processor 170 can perform a processing/determination operation. The processor 170 can perform the processing/determination operation on the basis of traveling situation information. The processor 170 can perform the processing/determination operation on the basis of at least one of object data, HD map data, vehicle state data and position data.

2.1) Driving Plan Data Generation Operation

The processor 170 can generate driving plan data. For example, the processor 170 may generate electronic horizon data. The electronic horizon data can be understood as driving plan data in a range from a position at which the vehicle 10 is located to a horizon. The horizon can be understood as a point a predetermined distance before the position at which the vehicle 10 is located on the basis of a predetermined traveling route. The horizon may refer to a point at which the vehicle can arrive after a predetermined time from the position at which the vehicle 10 is located along a predetermined traveling route.

The electronic horizon data can include horizon map data and horizon path data.

2.1.1) Horizon Map Data

The horizon map data may include at least one of topology data, road data, HD map data and dynamic data. According to an embodiment, the horizon map data may include a plurality of layers. For example, the horizon map data may include a first layer that matches the topology data, a second layer that matches the road data, a third layer that matches the HD map data, and a fourth layer that matches the dynamic data. The horizon map data may further include static object data.

The topology data may be explained as a map created by connecting road centers. The topology data is suitable for approximate display of a location of a vehicle and may have a data form used for navigation for drivers. The topology data may be understood as data about road information other than information on driveways. The topology data may be generated on the basis of data received from an external server through the communication device 220. The topology data may be based on data stored in at least one memory included in the vehicle 10.

The road data may include at least one of road slope data, road curvature data and road speed limit data. The road data may further include no-passing zone data. The road data may be based on data received from an external server through the communication device 220. The road data may be based on data generated in the object detection device 210.

The HD map data may include detailed topology information in units of lanes of roads, connection information of each lane, and feature information for vehicle localization (e.g., traffic signs, lane marking/attribute, road furniture, etc.). The HD map data may be based on data received from an external server through the communication device 220.

The dynamic data may include various types of dynamic information which can be generated on roads. For example, the dynamic data may include construction information, variable speed road information, road condition information, traffic information, moving object information, etc. The dynamic data may be based on data received from an external server through the communication device 220. The dynamic data may be based on data generated in the object detection device 210.

The processor 170 can provide map data in a range from a position at which the vehicle 10 is located to the horizon.

2.1.2) Horizon Path Data

The horizon path data may be explained as a trajectory through which the vehicle 10 can travel in a range from a position at which the vehicle 10 is located to the horizon. The horizon path data may include data indicating a relative probability of selecting a road at a decision point (e.g., a fork, a junction, a crossroad, or the like). The relative probability may be calculated on the basis of a time taken to arrive at a final destination. For example, if a time taken to arrive at a final destination is shorter when a first road is selected at a decision point than that when a second road is selected, a probability of selecting the first road can be calculated to be higher than a probability of selecting the second road.

The horizon path data can include a main path and a sub-path. The main path may be understood as a trajectory obtained by connecting roads having a high relative probability of being selected. The sub-path can be branched from at least one decision point on the main path. The sub-path may be understood as a trajectory obtained by connecting at least one road having a low relative probability of being selected at at least one decision point on the main path.

3) Control Signal Generation Operation

The processor 170 can perform a control signal generation operation. The processor 170 can generate a control signal on the basis of the electronic horizon data. For example, the processor 170 may generate at least one of a power train control signal, a brake device control signal and a steering device control signal on the basis of the electronic horizon data.

The processor 170 can transmit the generated control signal to the driving control device 250 through the interface 180. The driving control device 250 can transmit the control signal to at least one of a power train 251, a brake device 252 and a steering device 254.

FIG. 9 is a diagram referenced to describe a use scenario of a user according to an embodiment of the present disclosure.

1) Destination Prediction Scenario

The autonomous vehicle may include a cabin system. Hereinafter, the cabin system can be interpreted as a traveling vehicle. A first scenario S111 is a destination prediction scenario of a user. A user terminal may install an application interoperable with the cabin system. The user terminal may predict the destination of the user based on user's contextual information using the application. The user terminal may provide vacancy information in the cabin using the application.

2) Cabin Interior Layout Preparation Scenario

A second scenario S112 is a cabin interior layout preparation scenario. The cabin system may further include a scanning device for acquiring data about a user located outside the vehicle. The scanning device may acquire user's body data and baggage data by scanning the user. The user's body data and the baggage data can be used to set the layout. The user's body data may be used to authenticate the user. The scanning device may include at least one image sensor. The image sensor may acquire a user image using light in a visible light band or an infrared band.

The cabin system may include a seat system. The seat system may set the layout in the cabin based on at least one of the user's body data and the baggage data. For example, the seat system may be provided with a luggage storage space or a car seat installation space.

3) User Welcome Scenario

3) User Welcome Scenario: A third scenario S113 is a user welcome scenario. The cabin system may further include at least one guide light. The guide light may be disposed on a floor in the cabin. The cabin system may output a guide light to allow the user to sit on a predetermined seat among a plurality of seats when the user's boarding is detected. For example, a main controller of the cabin system may implement moving lights by sequentially turning on a plurality of light sources with time from an open door to a predetermined user seat.

4) Seat Adjustment Service Scenario

A fourth scenario S114 is a seat adjustment service scenario. The seat system may adjust at least one element of the seats that match the user based on the acquired body information.

5) Personal Content Providing Scenario

A fifth scenario S115 is a personal content providing scenario. A display system of the cabin system may receive user personal data via an input device or a communication device. The display system may provide content corresponding to the user personal data.

6) Product Providing Scenario

A sixth scenario S116 is a product providing scenario. The cabin system may further include a cargo system. The cargo system may receive user data via the input device or the communication device. The user data may include user's preference data, user's destination data, and the like. The cargo system may provide products based on the user data.

7) Payment Scenario

A seventh scenario S117 is a payment scenario. The cabin system may further include a payment system. The payment system may receive data for price calculation from at least one of the input device, the communication device, and the cargo system. The payment system may calculate a vehicle usage price of the user based on the received data. The payment system may request a payment from a user (for example, a user's mobile terminal) at a calculated price.

8) Display System Control Scenario of User

An eighth scenario S118 is a display system control scenario of a user. The input device of the cabin system may receive a user input of at least one type and convert the user input into an electrical signal. The display system may control the displayed content based on the electrical signal.

9) AI Agent Scenario

A main controller of the cabin system may include an artificial intelligence agent. The artificial intelligence agent may perform machine learning based on data acquired through the input device. The AI agent may control at least one of the display system, the cargo system, the seat system, and the payment system based on the machine-learned result.

A ninth scenario S119 is a multi-channel artificial intelligence (AI) agent scenario for a plurality of users. The artificial intelligence agent may classify user input for each of a plurality of users. The artificial intelligence agent may control at least one of the display system, the cargo system, the seat system, and the payment system based on the electrical signal into which the plurality of user individual user inputs are converted.

10) Multimedia Content Providing Scenario for a Plurality of Users

A tenth scenario S120 is a multimedia content providing scenario for a plurality of users. The display system may provide content that all users can watch together. In this case, the display system may provide the same sound to a plurality of users individually through speakers provided for each sheet. The display system may provide content that a plurality of users can watch individually. In this case, the display system may provide individual sound to a plurality of users through speakers provided for each sheet.

11) User Safety Ensuring Scenario

An eleventh scenario S121 is a user safety ensuring scenario. When acquiring object information around a vehicle that threatens a user, the main controller may control an alarm for an object around the vehicle to be output through the display system.

12) Scenario for Preventing Belonging from Being Lost

A twelfth scenario S122 is a scenario for preventing belongings of a user from being lost. The main controller may acquire data about the belongings of the user through the input device. The main controller may acquire motion data of the user through the input device. The main controller may determine whether the user leaves the belongings and gets off based on the data and the motion data about the belongings. The main controller may control an alarm for the belongings to be output through the display system.

13) Get Off Report Scenario

A thirteenth scenario S123 is a get off report scenario. The main controller may receive get off data of the user through the input device. After the user gets off, the main controller may provide a report data according to getting off to a user's mobile terminal through the communication device. The report data may include total usage fee data of a vehicle 10.

V2X (Vehicle-to-Everything)

FIG. 10 is a diagram showing an example of V2X communication to which the present disclosure can be applied.

The V2X communication refers to communication between vehicles and all entities such as vehicle-to-vehicle (V2V) which refers to communication between vehicles, vehicle to infrastructure which refers to communication between a vehicle and an eNB or a road side unit (RSU), vehicle-to-pedestrian (V2P) which refers to the communication between a vehicle and UEs carried by an individual (pedestrian, cyclist, vehicle driver, or passenger), and vehicle-to-network (V2N).

The V2X communication may have the same meaning as V2X sidelink or NR V2X or may have a broader meaning including the V2X sidelink or the NR V2X.

The V2X communication can be applied to various services such as forward collision warnings, automatic parking systems, cooperative adaptive cruise control (CACC), control loss warnings, traffic matrix warnings, traffic vulnerable safety warnings, emergency vehicle warnings, speed warning when traveling on curved roads, and traffic flow control.

The V2X communication may be provided via a PC5 interface and/or a Uu interface. In this case, in a wireless communication system supporting V2X communication, specific network entities may exist for supporting communication between the vehicle and all the entities. For example, the network entity may be a BS (eNB), a road side unit (RSU), a UE, an application server (for example, a traffic safety server), or the like.

In addition, the UE performing the V2X communication may mean not only a general handheld UE, but also a vehicle UE (vehicle UE (V-UE)), a pedestrian UE, a BS type (eNB type) RSU, or a UE type RSU, a robot including a communication module, or the like.

The V2X communication may be performed directly between the UEs or via the network entity(s). The V2X operation mode may be classified according to the method for performing V2X communication.

The V2X communication requires support of anonymity and privacy of the UE in the use of the V2X application so that operators or third parties cannot track a UE identifier within an area in which the V2X is supported.

Terms frequently used in V2X communication are defined as follows.

- Road side unit (RSU): RSU is a V2X serviceable device that can perform transmission/reception to/from a mobile vehicle using V2I service. In addition, the RSU is a fixed infrastructure entity that supports V2X applications and can exchange messages with other entities that support V2X applications. The RSU is a term frequently used in the existing ITS specification, and the reason for introducing the term in the 3GPP specification is to make the document easier to read in the ITS industry. The RSU is a logical entity that combines V2X application logic with the functionality of a BS (called a BS-type RSU) or a UE (called a UE-type RSU).
- V2I service: A type of V2X service in which one is a vehicle and the other is an infrastructure.
- V2P service: A type of V2X service in which one is a vehicle and the other is a device carried by an individual (for example, a portable UE device carried by a pedestrian, a cyclist, a driver or a passenger).
- V2X service: A 3GPP communication service type associated with transmitting or receiving devices in a vehicle.
- V2X enabled UE: UE supporting V2X service.
- V2V service: A type of V2X service, in which both communicating objects are vehicles.
- V2V communication range: Direct communication range between two vehicles participating in the V2V service.

As described above, the V2X application called vehicle-to-everything (V2X) are four types of (1) vehicle-to-vehicle (V2V), (2) vehicle-to-infrastructure (V2I), (3) vehicle-to-network (V2N), and (4) vehicle-to-pedestrian (V2P).

FIG. 11 is a diagram showing a resource allocation method in sidelink in which the V2X is used.

In the sidelink, as shown in FIG. 13A, different physical sidelink control channels (PSCCHs) may be spaced from each other and allocated in the frequency domain, and different physical sidelink shared channels (PSSCHs) may be spaced apart from each other and allocated. Alternatively, as shown in FIG. 13B, different PSCCHs may be continuously allocated in the frequency domain, and the PSSCHs may also be continuously allocated in the frequency domain.

NR V2X

The support for V2V and V2X services in LTE is introduced to extend the 3GPP platform to the automotive industry during 3GPP releases 14 and 15.

Requirements for supporting the enhanced V2X use case are largely grouped into four use case groups.

(1) Vehicle Plating allows vehicles may dynamically form a platoon in which vehicles move together. All the vehicles in the platoon obtain information from a leading vehicle to manage the platoon. This information enables vehicles to drive more harmoniously than normal, go in the same direction and drive together.

(2) Extended sensors may exchange raw or processed data, which are collected via local sensors or live video images, in vehicles, road site units, pedestrian devices, and V2X application servers. Vehicles can increase their environmental awareness more than their sensors can detect. High data rate is one of the main features.

(3) Advanced driving enables semi-automatic or fully-automatic driving. Each vehicle and/or RSU may share its own awareness data obtained from the local sensors with proximity vehicles, and synchronize and coordinate trajectory or maneuver. Each vehicle shares a proximity driving vehicle and a driving intent.

(4) Remote driving enables a remote driver or a V2X application to drive a remote vehicle for passengers who are unable to travel on their own or in a remote vehicle in a hazardous environment. If fluctuations are limited and a route can be predicted as in public transportation, driving based on cloud computing may be used. High reliability and low latency are key requirements.

The 5G communication technology described above may be applied in combination with the methods proposed in the present disclosure to be described later, or may be supplemented to specify or clarify the technical features of the methods proposed in the present disclosure.

Hereinafter, the lidar system according to the embodiment of the present disclosure and an autonomous driving system using the same will be described in detail. In the lidar system according to the present disclosure, at least one of an autonomous vehicle, an AI device, and an external device may be linked with an artificial intelligence module, a drone (unmanned aerial vehicle (UAV)), a robot, an augmented reality (AR) device, a virtual reality (VR) device, devices related to 5G network, and the like. In the following, an embodiment is described based on an example where the lidar system is applied to an autonomous vehicle, but it should be noted that the present disclosure is not limited thereto.

An object detection device 210 may include a lidar system as shown in FIGS. 12 to 24.

FIG. 12 is a block diagram showing a lidar system according to an embodiment of the present disclosure. FIG. 13 is a block diagram showing in detail a signal processor.

Referring to FIGS. 12 and 13, the lidar system includes a light source driver 100, a light emitter 102, a receiving sensor 106, a signal processor 108, and a sensor controller 120.

The light emitter 102 may include one or more light sources LS and a light scanner SC.

The light source driver 100 supplies a current to the laser light source LS of the light emitter 102 to drive the light source LS. The light source LS may emit a laser beam in the form of a line light source or a point light source.

The light source driver 100 may periodically alternate optical power into low power and high power by adjusting the amount of current of the light source LS.

The light source driver 100 may vary optical power by adjusting a driving current of each of the light sources LS according to traveling environment information on a traveling path received through a network. The traveling environment information may include terrain information, traffic congestion information, weather, and the like of a traveling section.

A wavelength of a laser beam generated from the light source LS may be 905 nm or 1550 nm. The 905 nm laser light source may be implemented as an InGaAs/GaAs based semiconductor diode laser, and may emit high power laser light. The peak power of an InGaAs/GaAs-based semiconductor diode laser is 25 W at one emitter. In order to increase the output of the InGaAs/GaAs-based semiconductor diode laser, three emitters may be combined into a stack structure to output 75 W laser light. The InGaAs/GaAs-based semiconductor diode laser can be implemented in a small size and at low cost. A driving mode of the InGaAs/GaAs-based semiconductor diode laser is a spatial mode and a multi mode.

A 1550 nm laser light source may be implemented as a fiber laser, a diode pumped solid state (DPSS) laser, a semiconductor diode laser, or the like. A representative example of a fiber laser is an erbium-doped fiber laser. The 1550 nm fiber laser can emit a 1550 nm laser through the erbium-doped fiber using a 980 nm diode Laser as pump laser. The peak power of the 1550 nm fiber laser can be up to several kW. The operating mode of the 1550 nm fiber laser is a spatial mode, a few mode. The 1550 nm fiber laser has a high optical quality and a small aperture size to detect an object with high resolution. DPSS laser can emit 1534 nm laser light through laser crystal such as MgAlO and YVO using a 980 nm diode laser as a pump laser. The 1550 nm semiconductor diode laser can be implemented as an InGaAsP/InP-based semiconductor diode laser, and the peak power thereof is several tens of W. The size of the 1550 nm semiconductor diode laser is smaller than that of the fiber laser.

The laser beam generated from the light source LS is incident on the light scanner SC. The light scanner SC reciprocates the laser beam from the light source LS to implement a preset field of view (FOV). The optical scanner SC may be implemented as a two-dimensional (2D) scanner for reciprocating the laser beam within a predetermined rotation angle range in each of the horizontal direction (x axis) and the vertical direction (y axis), or one or more one-dimensional (1D) scanners pivoting in a direction orthogonal to each other. The scanner may be implemented as a galvano scanner or a micro electro mechanical systems (MEMS) scanner.

The light scanner SC may be synchronized with the pixels of the receiving sensor 106 that are activated for each scan angle of the laser beam under the control of the sensor controller 120.

The laser beam emitted from the light emitter 102 is reflected on the object 110 and received by the receiving sensor 106. The pixels of the receiving sensor 106 may be arranged in a matrix form in which a plurality of row lines and a plurality of column lines are intersected. Each of the pixels converts the received light into a current using a photo-diode.

The signal processor 108 converts the output of the receiving sensor 106 into a voltage, amplifies the signal, and then converts the amplified signal into a digital signal using an analog to digital converter (ADC). The signal processor 108 analyzes digital data input from the ADC using a time of flight (TOF) algorithm or a phase-shift algorithm to detect a distance from the object 110, a shape of the object 110, and the like.

As shown in FIG. 13, the signal processor 108 includes a trans impedance amplifier (TIA) 310 which converts the current input from the activated pixels of the receiving sensor 106 into a voltage and amplifies the voltage, an integrator (INT) 320 which integrates an output signal of the trans impedance amplifier 310, a noise remover 330 which removes noise from an output signal of the integrator 320, an ADC 340 which converts the output signal of the noise remover 330 into a digital signal, a detector 350 which analyzes the digital signal input from the ADC 340, and the like.

The trans impedance amplifier 310 amplifies the output of the receiving sensor 106. The gain of the trans impedance amplifier 310 may be variable to a programmable gain. In this case, the gain of the trans impedance amplifier 310 may be changed according to data input from the autonomous driving device 260 or an external device connected to the network through I2C communication.

The integrator 320 accumulates the output of the trans impedance amplifier 310 in a capacitor a predetermined number of times to increase a voltage level of the signal.

The noise remover 330 removes noise by detecting a waveform of an input signal and analyzing waveform characteristics. In addition, the noise remover 330 may remove the noise of the input signal in the same manner as in FIGS. 20 to 22.

The detector 350 may analyze the digital signals of each of the activated pixels input from the ADC 340 using the TOF or the phase-shift algorithm to generate depth information for each scan angle, thereby being able to measure the distance of the object 110.

The signal processor 108 may provide sensor data including the distance from the object and shape information to the autonomous vehicle 260. The autonomous vehicle 260 receives the sensor data received from the lidar system and reflects the detected object information to the movement control of the vehicle.

FIG. 14 is a diagram showing a detection distance of a lidar system according to an embodiment of the present disclosure.

Referring to FIG. 14, the lidar system may be mounted on at least one of the front, rear, and side surfaces of the vehicle 10. When the lidar system is disposed on the front surface of the vehicle 10 of the vehicle 10, the object 110 may be sensed at full distance including a short distance and a long distance. The short distance may be up to 30 m from the mounted position of the lidar system and the long distance may be greater than or equal to 30 m, but the present disclosure are not limited thereto. In particular, the lidar system can detect the object 110 within a short distance of 50 cm by selectively receiving only the main lobe of the laser beam or by removing noise due to the side lobe in the short distance.

FIG. 15 is a diagram showing a main lobe and side lobes of a laser beam. In FIG. 15, a horizontal axis represents a width of the laser beam whose center of the main lobe is normalized to zero. The vertical axis represents the normalized intensity of light. FIG. 16 is a diagram showing the intensity of light of a laser beam received by a receiving sensor in a short distance.

Referring to FIGS. 15 and 16, the laser beam emitted from the light emitter 102 includes a main lobe 71 and a side lobe 72 beside the main lobe. Since the reflectance is high in the short distance, the light of the side lobes 72 reflected in the short distance may be received by the receiving sensor 106 at the intensity of light equal to or greater than the main lobe reflected in the long distance as in the example of FIG. 16.

FIG. 17 is a diagram showing an example of a scan angle of a laser beam. FIG. 18 is a diagram showing pixels of a receiving sensor activated for each scan angle shown in FIG. 17. FIG. 19 is a diagram showing the intensity of light of a laser beam received by the pixels of the receiving sensor activated for each scan angle.

Referring to FIGS. 17 to 19, the sensor controller 120 may synchronize the scanning of the optical scanner SC with the pixels of the receiving sensor 102 to selectively activate the pixels for each scan angle of the laser beam, and therefore may not receive the light of the side lobe 72. For example, when the laser beam is emitted forward at a front angle (0°), only 0° pixels from which the laser beam is received at a front angle (0°) may be activated (ON) as shown in FIG. 18. In this case, only the light of the main lobe 71 received at the front angle (0°) is converted into a current. The pixels of the side lobe 72 are not converted into an electrical signal because pixels other than the 0° pixels are inactivated (OFF). Therefore, the influence due to the light of the side lobe 72 in the received signal may be reduced.

When the laser beam is emitted forward at +10° by the scanner SC, only +10° pixels receiving a laser beam reflected from +10° may be activated (ON) as shown in FIG. 18. In this case, only the light of the main lobe 71 received at +10° is converted into a current. The pixels of the side lobe 72 are not converted into an electrical signal because pixels other than the +10° pixels are inactivated (OFF).

When the laser beam is emitted forward at −10° by the scanner SC, only −10° pixels receiving a laser beam reflected from −10° may be activated (ON) as shown in FIG. 18. In this case, only the light of the main lobe 71 received at −10° is converted into a current. The pixels of the side lobe 72 are not converted into an electrical signal because pixels other than the −10° pixels are inactivated (OFF).

The sensor controller 120 synchronizes the scanner SC with the receiving sensor 106 to activate some pixels of the receiving sensor corresponding to the scan angle of the scanner SC. Only a portion of the laser beam received by the receiving sensor 106 by the activated pixels is converted into an electrical signal.

FIG. 20 is a flowchart showing a method for removing noise of a received signal according to an embodiment of the present disclosure. FIG. 21 is a diagram showing a method for detecting a valid waveform of a received signal.

Referring to FIGS. 20 and 21, the light emitter 102 emits a laser beam and reciprocates the laser beam within a predetermined field of view (FOV) to scan the object 110 with the laser beam (S11). The receiving sensor 106 converts the laser beam received through the activated pixels for each scan angle of the laser beam into an electrical signal.

The output signal of the activated pixels is amplified and then integrated by the integrator 320. At the detection distance except the short distance, the signal of the main lobe 71 in the laser beam received by the receiving sensor 106 is much larger than the side lobe 72. Therefore, when the output signal of the activated pixels is amplified and accumulated in the integrator 330, the signal-to-noise ratio (S/N) becomes large, so that the noise is further reduced. The received signal may be accumulated in the integrator 320 five to ten times (S12).

The noise remover 330 detects a waveform of the received signal input from the integrator 320 (S13). The noise remover 330 detects a waveform equal to or greater than a dynamic threshold in the received signal (S13). As shown in FIG. 21, the dynamic threshold may vary according to the magnitude of the input signal, like TH0 and TH1. The dynamic threshold may vary in proportion to the magnitude of the input signal of the noise remover 330. For example, as shown in FIG. 21, when the magnitude of the received signal increases, the dynamic threshold increases from TH0 from TH1. On the other hand, the dynamic threshold may be lowered when the magnitude of the received signal decreases.

The noise remover 330 analyzes a waveform equal to or greater than the threshold TH1 from the integrated received signal and detects a valid waveform obtained from the main lobe 71 (S15). When there are two or more waveforms equal to or greater than the threshold TH1 as shown in FIG. 21, the noise remover 330 may detect a valid waveform corresponding to the main lobe 71 of the laser beam by comparing the characteristics of the waveform.

The main lobe 71 has a larger width W and a maximum value I at a distance greater than or equal to the short distance, as compared with the side lobe 72. The maximum value may be a peak value or signal strength. Therefore, the noise remover 330 may determine, as a valid waveform, a waveform having the largest width W and peak value I among waveforms equal to or greater than the threshold TH1 in the signal received from the object 110 at a distance greater than or equal to the short distance.

The reflectance of light is high in the short distance. Due to this, in the case of the signal received from the short distance, the intensity of light of the side lobe 72 may be larger than that of the main lobe 71 as shown in FIG. 16. The noise remover 330 may determine, as a valid waveform, a waveform having the largest width W among waveforms equal to or greater than the threshold TH1 in the signal received from the short distance.

The noise remover 330 determines, as noise, an invalid waveform other than the valid waveform from the input signal from the integrator 320 and removes the noise and then provides the input signal to the ADC 340 (S18). The detector 350 applies the maximum value among the invalid waveform data input from the ADC 340 as depth information for each scan angle (S16 and S17).

FIG. 22 is a flowchart showing a method for removing noise of a received signal according to another embodiment of the present specification.

Referring to FIG. 22, the light source driver 100 may periodically alternate the optical power of the light source LS into low power and high power. Accordingly, the light source LS may alternately emit a high-power laser beam and a low-power laser beam.

The low-power received signal synchronized with the low-power laser beam is accumulated in the integrator 320 a predetermined number of times, for example, five times (S21). The noise remover 330 receives the low-power received signal input from the integrator 320 and measures a distance value (or depth value) of each pixel of one frame at the entire field of view (FOV) (S22). The noise remover 330 may apply a low low-power threshold in the low-power received signal and measure distance values of pixels based on the received signal waveform above the threshold. The distance values of the pixels are a distance between the object 110 and the lidar system for each scan angle obtained from the received signal synchronized with the optical scanner SC.

The high-power received signal synchronized with the high-power laser beam is accumulated in the integrator 320 a predetermined number of times, for example, ten times (S23). The noise remover 330 receives the high-power received signal input from the integrator 320 and measures distance values of each pixel of one frame at the entire field of view (FOV). The side lobe 72 of the laser beam may increase in the high-power received signal. The noise remover 330 may apply a relatively higher-power threshold in the low-power received signal and measure distance values of pixels based on the received signal waveform above the threshold. The high-power threshold may be applied as an appropriate value higher than the low power so that the distance value measured in the low-power received signal and the distance value measured in the high-power received signal are substantially the same.

The noise remover 330 compares the distance value measured in the low-power received signal with each of the pixels at the entire field of view and the distance value measured in the high-power received signal to detect the valid waveform corresponding to the main lobe 71 in the received signal if the low-power measured value and the high-power measured value are the same in the same pixel (S26). If the low-power measured value and the high-power measured value in the same pixel are different in the same pixel, the noise remover 330 removes the noise from the corresponding frame (S28).

Steps S26 and S28 of detecting the valid waveform and removing the noise removes due to the side lobe 72 by performing steps S13 to S16 in FIG. 21 to derive the maximum value of the valid waveform corresponding to the main lobe 71.

The noise remover 330 removes the invalid waveform other than the valid waveform from the input signal from the integrator 320 and provides the input signal to the ADC 340 (S18). The detector 350 applies the maximum value among the invalid waveform data input from the ADC 340 as the depth information for each scan angle (S27).

FIG. 23 is a diagram showing pixels of a receiving sensor activated for each scan angle upon detecting a short distance. FIG. 24 is a diagram showing pixels of a receiving sensor activated for each scan angle upon detecting a long distance.

Referring to FIGS. 23 and 24, the sensor controller 120 may reduce the influence of the side lobe 72 by reducing the number of pixels activated for each scan angle upon detecting a short distance including a short distance.

The sensor controller 120 activates the pixels in column units for each scan angle in the receiving sensor 106, but may further reduce the number of columns activated for each scan angle upon detecting the short distance than the number of columns activated upon detecting the long distance. For example, as shown in FIG. 23, the sensor controller 120 may activate pixels by one column for each scan angle in the receiving sensor 106. As shown in FIG. 24, the sensor controller 120 may activate pixels by two columns for each scan angle in the receiving sensor 106 upon detecting the long distance.

The sensor controller 120 may increase the number of columns activated for each scan angle as the sensing distance increases. As shown in FIGS. 23 and 24, the column activated in the receiving sensor 106 may be shifted depending on the scan angle of the laser beam.

Various embodiments of the lidar system of the present disclosure will be described below.

First Embodiment

A lidar system includes; a light emitter configured to include a light source generating a laser beam and a scanner moving the laser beam from the light source to scan an object with the laser beam; a receiving sensor configured to include a plurality of pixels converting a received signal of light received from the object into an electrical signal; and a sensor controller configured to synchronize the scanner with the receiving sensor and activate some pixel of the receiving sensor corresponding to a scan angle. The some of the laser beam is converted into the electrical signal by the activated pixels.

Second Embodiment

The lidar system may further include: a trans impedance amplifier configured to convert a current input from the activated pixels into a voltage and amplify the voltage; an integrator configured to integrate an output signal of the trans impedance amplifier; a noise remover configured to remove noise from an output signal of the integrator; an analog to digital converter configured to convert the output signal of the noise remover into a digital signal; and a detector configured to analyze the digital signal to generate depth information for each scan angle.

Third Embodiment

The noise remover may detect a waveform equal to or greater than a threshold of the output signal of the integrator, and detect a main lobe of the laser beam as a valid waveform in the waveform greater than or equal to the threshold. The threshold varies in proportion to a magnitude of the received signal.

Fourth Embodiment

The valid waveform may be a waveform having a largest width among the waveforms greater than or equal to the threshold in the signal received from a short distance.

Fifth Embodiment

The noise remover may remove an invalid waveform other than the valid waveform and supply a signal of the valid waveform to the analog to digital converter. The detector may select a maximum value of the valid waveform from the analog to digital converter to detect a depth information for the scan angle.

Sixth Embodiment

The lidar system may further include a light source driver configured to periodically alternate power of the light source into low power and high power.

Seventh Embodiment

The noise remover may compare a distance value measured in a low-power received signal with a distance value measured in a high-power received signal. The valid waveform may include a pixel value from a pixel having a same value between the low-power measured value and the high-power measured value.

Eighth Embodiment

The pixels of the receiving sensor may be arranged in a matrix form in which a plurality of row lines and a plurality of column lines intersect with each other. The sensor controller may reduce the number of pixels activated for the scan angle of a short distance than the number of pixels activated for the scan angle of a long distance.

Ninth Embodiment

The sensor controller may reduce the number of columns activated for the scan angle of the short distance than the number of columns activated for the scan angle of the s long distance. The column activated in the receiving sensor are shifted depending on the scan angle of the laser beam.

Tenth Embodiment

The sensor controller may increase the number of columns activated for the scan angle as a distance between the object and the receiving sensor increases.

The autonomous driving system according to the present disclosure may include the autonomous driving device that receives the sensor data received from the lidar system and reflects the object information to the movement control of the vehicle.

The effects of the lidar system according to the embodiment of the present disclosure will be described below.

In the present specification, it is possible to block the influence of the side lobe in the received signal by activating the pixels that receive the light of the main lobe in the receiving sensor in the short distance in which the intensity of light of the side lobe increases.

In present specification, after the received signal is amplified and accumulated a plurality of number of times to increase the signal-to-noise ratio (SNR) and the dynamic threshold is applied, the waveform characteristics of the received signal are analyzed to be able to detect the valid waveform corresponding to the main lobe and remove the noise due to the side lobes.

In the present specification, the received signals from each of the low-power laser beam and the high-power laser beam are compared to detect the valid waveform when the distance values of each of the pixels of the receiving sensor are the same, thereby removing the noise due to the side lobe more precisely.

In addition, in the present specification, it is possible to block the influence of the side lobes at the short distance and increase the scanning speed at the long distance by changing the number of columns activated for each scan angle in the receiving sensor activated in the receiving sensor according to the detected distance.

Accordingly, in the present specification, it is possible to provide the lidar system and the autonomous driving system using the same disclosure capable of detecting obstacles in the full distance and detecting obstacles in the short distance without the separate sensor for measuring the short distance.

Effects which can be achieved by the present disclosure are not limited to the above-mentioned effects. That is, other objects that are not mentioned may be obviously understood by those skilled in the art to which the present disclosure pertains from the following description.

The present disclosure can be achieved as computer-readable codes on a program-recoded medium. A computer-readable medium includes all kinds of recording devices that keep data that can be read by a computer system. For example, the computer-readable medium may be an HDD (Hard Disk Drive), an SSD (Solid State Disk), an SDD (Silicon Disk Drive), a ROM, a RAM, a CD-ROM, a magnetic tape, a floppy disk, and an optical data storage, and may also be implemented in a carrier wave type (for example, transmission using the internet). Accordingly, the detailed description should not be construed as being limited in all respects and should be construed as an example. The scope of the present disclosure should be determined by reasonable analysis of the claims and all changes within an equivalent range of the present disclosure is included in the scope of the present disclosure.

Although embodiments have been described with reference to a number of illustrative embodiments thereof, it should be understood that numerous other modifications and embodiments can be devised by those skilled in the art that will fall within the scope of the principles of this disclosure. More particularly, various variations and modifications are possible in the component parts and/or arrangements of the subject combination arrangement within the scope of the disclosure, the drawings and the appended claims. In addition to variations and modifications in the component parts and/or arrangements, alternative uses will also be apparent to those skilled in the art.