# US 12,179,800 B2 · Distributed computing systems for autonomous vehicle operations > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 12,179,800 B2 - Document ID: US12179800B2 - Status: Granted - Kind: B2 - Application number: 18/331,705 - Filed: 2023-06-08 - Published: 2023-10-12 - Granted: 2024-12-31 - Earliest claimed: 2019-09-13 - Assignees: Tusimple, Inc. - Applicants: Tusimple, Inc. - Inventors: Charles A. Price; Zehua Huang; Xiaoling Han; Ruiliang Zhang; Xiaodi Hou - Web page: https://patentgrep.com/patent/US12179800B2 ## CPC - B60W 60/0017: {of other traffic participants} - G01C 21/3407: {specially adapted for specific applications} - B60W 30/0956: {the prediction being responsive to traffic or environmental parameters} - B60W 60/001: {Planning or execution of driving tasks} - B60W 60/0027: {using trajectory prediction for other traffic participants} - G01C 21/3815: {Road data} - G08G 1/143: {inside the vehicles} - G08G 1/16: Anti-collision systems (road vehicle drive control systems for predicting or avoiding probable or impending collision otherwise than by control of a particular sub-unit B60W30/08) - B60W 2420/403: Image sensing, e.g. optical camera - B60W 2420/408: Radar; Laser, e.g. lidar - B60W 2510/0604: Throttle position - B60W 2510/1005: Transmission ratio engaged - B60W 2510/18: Braking system - B60W 2510/20: Steering systems - B60W 2554/20: Static objects - B60W 2554/4041: Position - B60W 2554/4044: Direction of movement, e.g. backwards - G08G 1/165: {for passive traffic, e.g. including static obstacles, trees} - G08G 1/166: {for active traffic, e.g. moving vehicles, pedestrians, bikes} - B60W: CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT - 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) - G08G: TRAFFIC CONTROL SYSTEMS (guiding railway traffic, ensuring the safety of railway traffic B61L; arrangement of road signs or traffic signals E01F9/00; radar or analogous systems, sonar systems, lidar systems specially adapted for traffic control G01S13/91, G01S15/88, G01S17/88; {radar or analogous systems, sonar systems, lidar systems specially adapted for anti-collision purposes G01S13/93, G01S15/93, G01S17/93}) ## Abstract Disclosed are distributed computing systems and methods for controlling multiple autonomous control modules and subsystems in an autonomous vehicle. In some aspects of the disclosed technology, a computing architecture for an autonomous vehicle includes distributing the complexity of autonomous vehicle operation, thereby avoiding the use of a single high-performance computing system and enabling off-the-shelf components to be use more readily and reducing system failure rates. ## Claims ### Claim 1 A method of operating a vehicle, comprising: determining a set of trajectories on which the vehicle is to be operated on a road, wherein the set of trajectories is determined based on a drivable area information and a motion pattern of an object located on the road; wherein the drivable area information indicates a region where the vehicle is allowed to be driven, wherein the drivable area information is determined from landmarks stored in a map database and a fused data comprising image data that includes the object and point cloud data that includes the object, and wherein the motion pattern of the object indicates a predicted trajectory information of the object; causing a driving operation of the vehicle based on a location of the vehicle, an orientation of the vehicle, and a trajectory from the set of trajectories, wherein the determining the set of trajectories and the causing the driving operation is performed using an autonomous driving software having a calculated metric that characterizes a performance of the autonomous driving software and that is greater than a pre-determined threshold. ### Claim 2 (depends on 1) The method of claim 1, wherein the determining the set of trajectories and the causing the driving operation is performed by a same computer in the vehicle as part of a set of operations that is assigned to the same computer. ### Claim 3 (depends on 1) The method of claim 1, wherein the autonomous driving software enables assignment of a first set of operations to a first computer in the vehicle, and wherein the autonomous driving software enables assignment of a second set of operations to a second computer in the vehicle, wherein the second set of operations include the determining the set of trajectories and the causing the driving operation. ### Claim 4 (depends on 1) The method of claim 1, further comprising: performing a tracking operation by tracking another location of the object from a plurality of images received from a camera on the vehicle, and storing a set of locations of the object over a pre-determined time. ### Claim 5 (depends on 4) The method of claim 4, wherein a temporal fusion operation is performed by correlating the object in an image from the plurality of images with the object in one or more additional images from the plurality of images. ### Claim 6 (depends on 1) The method of claim 1, wherein the driving operation caused by: determining one or more values that includes an amount of brake pressure to apply, a steering angle of the vehicle, a throttle amount to control a speed of the vehicle, or a transmission gear of the vehicle; and sending one or more instructions to one or more devices in the vehicle based on the one or more values. ### Claim 7 An apparatus for operating a vehicle, comprising: a computer comprising a processor configured to: determine a set of trajectories on which the vehicle is to be operated on a road, wherein the set of trajectories is determined based on a drivable area information and a motion pattern of an object located on the road; wherein the drivable area information indicates a region where the vehicle is allowed to be driven, wherein the drivable area information is determined from landmarks stored in a map database and a fused data comprising image data that includes the object and point cloud data that includes the object, and wherein the motion pattern of the object indicates a predicted trajectory information of the object; cause a driving operation of the vehicle based on a location of the vehicle, an orientation of the vehicle, and a trajectory from the set of trajectories, wherein the determine the set of trajectories and the cause the driving operation is performed using an autonomous driving software having a calculated metric that characterizes a performance of the autonomous driving software and that is greater than a pre-determined threshold. ### Claim 8 (depends on 7) The apparatus of claim 7, wherein the drivable area information is determined from landmarks stored in a map database and a fused data comprising image data that includes the object and point cloud data that includes the object. ### Claim 9 (depends on 7) The apparatus of claim 7, wherein the vehicle includes a distributed computing vehicle control system that includes a plurality of computing systems, wherein each computing system includes at least one computer, and wherein the determining the set of trajectories and the causing the driving operation is assigned to a computing system from the plurality of computing systems. ### Claim 10 (depends on 7) The apparatus of claim 7, wherein the predicted trajectory information of the object is over a pre-determined length of time after an image comprising the object is received by a camera on the vehicle. ### Claim 11 (depends on 7) The apparatus of claim 7, wherein the motion pattern of the object is determined based on a speed of the object and a direction of movement the object. ### Claim 12 A non-transitory computer readable program storage medium having code stored thereon, the code, when executed by a processor, causing the processor to implement a method comprising: determining a set of trajectories on which a vehicle is to be operated on a road, wherein the set of trajectories is determined based on a drivable area information and a motion pattern of an object located on the road; wherein the drivable area information indicates a region where the vehicle is allowed to be driven, wherein the drivable area information is determined from landmarks stored in a map database and a fused data comprising image data that includes the object and point cloud data that includes the object, and wherein the motion pattern of the object indicates a predicted trajectory information of the object; causing a driving operation of the vehicle based on a location of the vehicle, an orientation of the vehicle, and a trajectory from the set of trajectories, wherein the determining the set of trajectories and the causing the driving operation is performed using an autonomous driving software having a calculated metric that characterizes a performance of the autonomous driving software and that is greater than a pre-determined threshold. ### Claim 13 (depends on 12) The non-transitory computer readable program storage medium of claim 12, further comprising: assigning a tag to the object based on the motion pattern, wherein the tag describes the motion pattern of the object. ### Claim 14 (depends on 13) The non-transitory computer readable program storage medium of claim 13, wherein the tag includes a speed of the object. ### Claim 15 (depends on 13) The non-transitory computer readable program storage medium of claim 13, wherein the tag includes another location of the object. ### Claim 16 (depends on 13) The non-transitory computer readable program storage medium of claim 13, wherein the tag includes an indication that the object is stopped. ### Claim 17 (depends on 13) The non-transitory computer readable program storage medium of claim 13, wherein the tag includes an indication of whether a speed of the object is increasing or decreasing. ### Claim 18 (depends on 12) The non-transitory computer readable program storage medium of claim 12, wherein the method further comprises: receiving Radar data from a Radar on the vehicle; tracking, using the Radar data, the object from a first point cloud data and a first image obtained at a first time to a second point cloud data and a second image obtained at a second time that is later than the first time. ### Claim 19 (depends on 12) The non-transitory computer readable program storage medium of claim 12, wherein the object includes another vehicle or a pedestrian.