# US 11,994,592 B2 · Lidar-based unmanned vehicle testing method and apparatus > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 11,994,592 B2 - Document ID: US11994592B2 - Status: Granted - Kind: B2 - Application number: 17/407,053 - Filed: 2021-08-19 - Published: 2022-02-10 - Granted: 2024-05-28 - Earliest claimed: 2019-02-20 - Assignees: Venti Technologies Corporation - Applicants: Venti Technologies Corporation - Inventors: Pengcheng Qian - Web page: https://patentgrep.com/patent/US11994592B2 ## CPC - G01S 17/931: of land vehicles - G01C 21/12: executed aboard the object being navigated; Dead reckoning - G01C 21/3602: {Input other than that of destination using image analysis, e.g. detection of road signs, lanes, buildings, real preceding vehicles using a camera} - G01M 17/007: Wheeled or endless-tracked vehicles (G01M17/08 takes precedence) - G01S 17/86: Combinations of lidar systems with systems other than lidar, radar or sonar, e.g. with direction finders - G05D 1/024: {in combination with a laser (lasers per se H01S)} - G05D 1/0274: {using mapping information stored in a memory device (navigation using map-matching G01C21/30)} - G05D 1/247: using signals provided by artificial sources external to the vehicle, e.g. navigation beacons - G06T 7/20: Analysis of motion (motion estimation for coding, decoding, compressing or decompressing digital video signals H04N19/43, H04N19/51) - G01S 17/89: for mapping or imaging - G06T 2207/10028: Range image; Depth image; 3D point clouds - G01S: RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES - G01C: MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY (measuring liquid level G01F; radio navigation, determining distance or velocity by use of propagation effects, e.g. Doppler effects, propagation time, of radio waves, analogous arrangements using other waves G01S) - G01M: TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR - G05D: SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES - G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL ## Abstract A lidar-based unmanned vehicle testing method, the method comprising: acquiring vehicle movement information and point cloud data collected by lidar, the vehicle movement information comprising movement of the vehicle during the vehicle driving process; if the movement of the vehicle is a preset movement then, on the basis of the point cloud data and a map, acquiring road information of the test road on which the vehicle is located; on the basis of the preset movement and the road information, acquiring a performance index of the vehicle; and, on the basis of the vehicle movement information and the performance index, determining a vehicle performance test result. ## Claims ### Claim 1 A method for testing an unmanned vehicle based on a laser radar, comprising: acquiring point cloud data and vehicle motion information, wherein the point cloud data is collected by a laser radar on the vehicle, the vehicle motion information including a motion of the vehicle during travel; acquiring road type information of a test road where the vehicle is located according to the point cloud data and a map in response to the motion of the vehicle being a preset motion, wherein the map being a map including a test road for testing the vehicle and a road type includes at least one of a highway, a cobbled road, a fish scale pit road, a washboard road, a Belgian road, a rough road, a swinging road, a broken road, a square pit, a standard ramp, a ring road, and a mountain road; acquiring a performance indicator of the vehicle according to the preset motion and the road type information, wherein a correspondence among the preset motion, the road type information, and the performance indicator of the vehicle is preset before testing and the performance indicator of the vehicle includes at least one of a time required accelerating to 100 kilometers per hour, a steering radius, a steering angle, and a braking distance for emergency braking; and determining a vehicle performance test result according to the vehicle motion information and the performance indicator, wherein said acquiring road type information of the test road where the vehicle is located according to the point cloud data and the map comprises: determining a location of the vehicle on the test road according to the point cloud data and the map to acquire the road type information corresponding to the location; wherein a correspondence between the road type information and the location on the test road is preset, and the road type information includes the road type; the preset motion comprises one or more of the following: acceleration, deceleration, emergency braking, or steering; the performance indicator includes one or more of the following: a power indicator, an emergency braking indicator, or a control stability indicator. ### Claim 2 (depends on 1) The method according to claim 1, wherein the vehicle motion information further comprises a vehicle motion parameter; and said determining a vehicle performance test result according to the vehicle motion information and the performance indicator includes: determining a performance parameter of the vehicle according to the vehicle motion parameter; and determining that the vehicle performance test result is qualified in response to the performance parameter of the vehicle meeting the performance indicator, wherein the vehicle motion parameter includes one or more of the following: a starting time of the preset motion, an ending time of the preset motion, a speed corresponding to the starting time, a speed corresponding to the ending time, a travel distance from the starting time to the ending time, a vehicle steering angle, or a vehicle steering radius. ### Claim 3 (depends on 1) The method according to claim 1, further comprising: determining a vehicle pose according to the point cloud data and the map. ### Claim 4 (depends on 3) The method according to claim 3, further comprising: locating the vehicle and recording fault information, in response to a vehicle fault being determined according to the vehicle pose. ### Claim 5 (depends on 4) The method according to claim 4, further comprising: acquiring wear data of the vehicle in response to a travel mileage of the vehicle reaching a preset mileage; and determining a durability test result of the vehicle according to the wear data, the fault information, and the vehicle performance test result. ### Claim 6 (depends on 1) The method according to claim 1, wherein the unmanned vehicle travels on the test road using the laser radar; or, the unmanned vehicle travels on the test road according to preconfigured motion information, wherein the preconfigured motion information includes a speed and a steering angle corresponding to each location on the test road, or the preconfigured motion information includes a speed and a steering angle corresponding to each time period in a test. ### Claim 7 (depends on 1) The non-volatile computer-readable storage medium according to claim 1, wherein the processor is further configured to: determine a vehicle pose according to the point cloud data and the map. ### Claim 8 (depends on 7) The non-volatile computer-readable storage medium according to claim 7, wherein the processor is further configured to: locate the vehicle and recording fault information, in response to a vehicle fault being determined according to the vehicle pose. ### Claim 9 (depends on 8) The non-volatile computer-readable storage medium according to claim 8, wherein the processor is further configured to: acquire wear data of the vehicle in response to a travel mileage of the vehicle reaching a preset mileage; and determine a durability test result of the vehicle according to the wear data, the fault information, and the vehicle performance test result. ### Claim 10 A device for testing an unmanned vehicle device based on a laser radar, comprising: a processor; and a memory configured to store processor-executable instructions, wherein the processor is configured to execute the executable instructions to implement operations comprising: acquiring point cloud data and vehicle motion information, wherein the point cloud data is collected by a laser radar on the vehicle, the vehicle motion information including a motion of the vehicle during travel; acquiring road type information of a test road where the vehicle is located according to the point cloud data and a map in response to the motion of the vehicle being a preset motion, wherein the map being a map including a test road for testing the vehicle and a road type includes at least one of a highway, a cobbled road, a fish scale pit road, a washboard road, a Belgian road, a rough road, a swinging road, a broken road, a square pit, a standard ramp, a ring road, and a mountain road; acquiring a performance indicator of the vehicle according to the preset motion and the road type information, wherein a correspondence among the preset motion, the road type information, and the performance indicator of the vehicle is preset before testing and the performance indicator of the vehicle includes at least one of a time required accelerating to 100 kilometers per hour, a steering radius, a steering angle, and a braking distance for emergency braking; and determining a vehicle performance test result according to the vehicle motion information and the performance indicator, wherein said acquiring road type information of the test road where the vehicle is located according to the point cloud data and the map comprises: determining a location of the vehicle on the test road according to the point cloud data and the map to acquire the road type information corresponding to the location; wherein a correspondence between the road type information and the location on the test road is preset, and the road type information includes the road type; the preset motion comprises one or more of the following: acceleration, deceleration, emergency braking, or steering; the performance indicator includes one or more of the following: a power indicator, an emergency braking indicator, or a control stability indicator. ### Claim 11 (depends on 10) The device according to claim 10, wherein the vehicle motion information further comprises a vehicle motion parameter; and said determining a vehicle performance test result according to the vehicle motion information and the performance indicator includes: determining a performance parameter of the vehicle according to the vehicle motion parameter; and determining that the vehicle performance test result is qualified in response to the performance parameter of the vehicle meeting the performance indicator, wherein the vehicle motion parameter includes one or more of the following: a starting time of the preset motion, an ending time of the preset motion, a speed corresponding to the starting time, a speed corresponding to the ending time, a travel distance from the starting time to the ending time, a vehicle steering angle, or a vehicle steering radius. ### Claim 12 (depends on 10) The device according to claim 10, wherein the processor is further configured to: determine a vehicle pose according to the point cloud data and the map. ### Claim 13 (depends on 12) The device according to claim 12, wherein the processor is further configured to: locate the vehicle and recording fault information, in response to a vehicle fault being determined according to the vehicle pose. ### Claim 14 (depends on 13) The device according to claim 13, wherein the processor is further configured to: acquire wear data of the vehicle in response to a travel mileage of the vehicle reaching a preset mileage; and determine a durability test result of the vehicle according to the wear data, the fault information, and the vehicle performance test result. ### Claim 15 (depends on 10) The device according to claim 10, wherein the unmanned vehicle travels on the test road using the laser radar; or, the unmanned vehicle travels on the test road according to preconfigured motion information, wherein the preconfigured motion information includes a speed and a steering angle corresponding to each location on the test road, or the preconfigured motion information includes a speed and a steering angle corresponding to each time period in a test. ### Claim 16 A non-volatile computer-readable storage medium, storing computer program instructions therein, wherein the computer program instructions, when executed by a processor, implement operations comprising: acquiring point cloud data and vehicle motion information, wherein the point cloud data is collected by a laser radar on the vehicle, the vehicle motion information including a motion of the vehicle during travel; acquiring road type information of a test road where the vehicle is located according to the point cloud data and a map in response to the motion of the vehicle being a preset motion, wherein the map being a map including a test road for testing the vehicle and a road type includes at least one of a highway, a cobbled road, a fish scale pit road, a washboard road, a Belgian road, a rough road, a swinging road, a broken road, a square pit, a standard ramp, a ring road, and a mountain road; acquiring a performance indicator of the vehicle according to the preset motion and the road type information, wherein a correspondence among the preset motion, the road type information, and the performance indicator of the vehicle is preset before testing and the performance indicator of the vehicle includes at least one of a time required accelerating to 100 kilometers per hour, a steering radius, a steering angle, and a braking distance for emergency braking; and determining a vehicle performance test result according to the vehicle motion information and the performance indicator, wherein said acquiring road type information of the test road where the vehicle is located according to the point cloud data and the map comprises: determining a location of the vehicle on the test road according to the point cloud data and the map to acquire the road type information corresponding to the location; wherein a correspondence between the road type information and the location on the test road is preset, and the road type information includes the road type; the preset motion comprises one or more of the following: acceleration, deceleration, emergency braking, or steering; the performance indicator includes one or more of the following: a power indicator, an emergency braking indicator, or a control stability indicator. ### Claim 17 (depends on 16) The device according to claim 16, wherein the unmanned vehicle travels on the test road using the laser radar; or, the unmanned vehicle travels on the test road according to preconfigured motion information, wherein the preconfigured motion information includes a speed and a steering angle corresponding to each location on the test road, or the preconfigured motion information includes a speed and a steering angle corresponding to each time period in a test. ### Claim 18 (depends on 16) The non-volatile computer-readable storage medium according to claim 16, wherein the unmanned vehicle travels on the test road using the laser radar; or, the unmanned vehicle travels on the test road according to preconfigured motion information, wherein the preconfigured motion information includes a speed and a steering angle corresponding to each location on the test road, or the preconfigured motion information includes a speed and a steering angle corresponding to each time period in a test.