# US 12,007,779 B2 · Adaptive vehicle motion control system > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 12,007,779 B2 - Document ID: US12007779B2 - Status: Granted - Kind: B2 - Application number: 17/344,507 - Filed: 2021-06-10 - Published: 2021-09-30 - Granted: 2024-06-11 - Earliest claimed: 2017-02-02 - Assignees: Uatc, LLC - Applicants: Uatc, LLC - Inventors: Albert Costa; Michael L. Phillips; Michael Bode - Web page: https://patentgrep.com/patent/US12007779B2 ## CPC - G05D 1/0223: {involving speed control of the vehicle (vehicle fittings for automatically controlling, i.e. preventing speed from exceeding an arbitrarily established velocity or maintaining speed at a particular velocity, as selected by the vehicle operator B60K31/00)} - B60W 30/095: Predicting travel path or likelihood of collision - B60W 30/0953: {the prediction being responsive to vehicle dynamic parameters} - G01C 21/3415: {Dynamic re-routing, e.g. recalculating the route when the user deviates from calculated route or after detecting real-time traffic data or accidents} - G05D 1/0027: {involving a plurality of vehicles, e.g. fleet or convoy travelling (fleet control of land vehicles from a control room G05D1/0297; traffic control systems for road vehicles G08G1/00; for marine craft G08G3/00; for aircraft G08G5/00)} - G05D 1/0088: {characterized by the autonomous decision making process, e.g. artificial intelligence, predefined behaviours (using knowledge based models G06N5/00)} - G05D 1/0217: {in accordance with energy consumption, time reduction or distance reduction criteria} - G05D 1/227: Handing over between remote control and on-board control; Handing over between remote control arrangements - G05D 1/644: Optimisation of travel parameters, e.g. of energy consumption, journey time or distance - G05D 1/65: Following a desired speed profile - G05D 1/692: involving a plurality of disparate vehicles - G05D 1/81: Handing over between on-board automatic and on-board manual control - B60W 2554/00: Input parameters relating to objects - B60W 2554/80: Spatial relation or speed relative to objects - B60W 2720/10: Longitudinal speed - B60W 2754/30: Longitudinal distance - G05D: SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES - 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) ## Abstract Systems and methods for controlling the motion of an autonomous are provided. In one example embodiment, a computer implemented method includes obtaining, by one or more computing devices on-board an autonomous vehicle, data associated with one or more objects that are proximate to the autonomous vehicle. The data includes a predicted path of each respective object. The method includes identifying at least one object as an object of interest based at least in part on the data associated with the object of interest. The method includes generating cost data associated with the object of interest. The method includes determining a motion plan for the autonomous vehicle based at least in part on the cost data associated with the object of interest. The method includes providing data indicative of the motion plan to one or more vehicle control systems to implement the motion plan for the autonomous vehicle. ## Claims ### Claim 1 A computing system for controlling autonomous vehicle motion, comprising: one or more processors on-board an autonomous vehicle; and one or more memory devices on-board the autonomous vehicle, the one or more memory devices storing instructions that when executed by the one or more processors cause the computing system to perform operations, the operations comprising: obtaining data associated with a plurality of objects that are within an environment of the autonomous vehicle, wherein the data comprises respective predicted paths for the plurality of objects; generating cost data associated with the plurality of objects, wherein the cost data for a respective object, of the plurality of objects, is indicative of an effect of controlling a motion of the autonomous vehicle such that the autonomous vehicle travels behind or in front of the respective object; outputting data indicative of the cost data associated with the plurality of objects; determining a motion plan for the autonomous vehicle based at least in part on the cost data; and causing the autonomous vehicle to implement at least a portion of the motion plan for the autonomous vehicle. ### Claim 2 (depends on 1) The computing system of claim 1, wherein the motion plan comprises one or more parameters associated with the motion of the autonomous vehicle. ### Claim 3 (depends on 1) The computing system of claim 1, wherein implementation of the motion plan causes the autonomous vehicle to travel in a manner that corresponds to a motion of at least one object of the plurality of objects with at least a minimum distance between the autonomous vehicle and the at least one object. ### Claim 4 (depends on 1) The computing system of claim 1, wherein the cost data is based at least in part on one or more constraints, and wherein the one or more constraints comprise at least one of a headway between the autonomous vehicle and the respective object and a time to a potential collision between the autonomous vehicle and the respective object. ### Claim 5 (depends on 1) The computing system of claim 1, wherein the predicted paths indicate that at least one object of the plurality of objects is predicted to travel through an intersection. ### Claim 6 (depends on 1) The computing system of claim 1, wherein the predicted paths indicate that at least one object of the plurality of objects is predicted to merge into a current travel lane of the autonomous vehicle. ### Claim 7 (depends on 1) The computing system of claim 1, wherein at least one object of the plurality of objects is located in a travel lane and wherein the autonomous vehicle is to merge into the travel lane. ### Claim 8 An autonomous vehicle comprising: one or more processors; and one or more memory devices, the one or more memory devices storing instructions that when executed by the one or more processors cause the one or more processors to perform operations, the operations comprising: obtaining data associated with a plurality of objects that are within an environment of the autonomous vehicle, wherein the data associated with the plurality of objects comprises respective predicted paths of the plurality of objects; performing a cost analysis associated with the plurality of objects, wherein the cost analysis for a respective object, of the plurality of objects, is associated with an effect of controlling a motion of the autonomous vehicle such that the autonomous vehicle travels behind or in front of the respective object; determining a motion plan for the autonomous vehicle based at least in part on the cost analysis; and causing the autonomous vehicle to implement at least a portion of the motion plan for the autonomous vehicle. ### Claim 9 (depends on 8) The autonomous vehicle of claim 8, wherein the plurality of objects comprise a first object that is in a current travel lane of the autonomous vehicle. ### Claim 10 (depends on 8) The autonomous vehicle of claim 8, wherein performing the cost analysis associated with the plurality of objects comprises: performing a cost analysis associated with a second object of the plurality of objects, wherein the second object is in another travel lane that is different from a current travel lane of the autonomous vehicle, and wherein the cost analysis associated with the second object is indicative of an effect of controlling the motion of the autonomous vehicle based at least in part on a motion of the second object. ### Claim 11 (depends on 8) The autonomous vehicle of claim 8, wherein the cost analysis is based at least in part on one or more constraints, and wherein the one or more constraints comprise at least one of: (i) a headway, (ii) a time, or (iii) a preferred distance between the autonomous vehicle and the respective object. ### Claim 12 (depends on 8) The autonomous vehicle of claim 8, wherein the operations further comprise: determining that the autonomous vehicle and a first object of the plurality of objects will travel in a same travel lane based at least in part on the predicted path of the first object. ### Claim 13 (depends on 8) The autonomous vehicle of claim 8, wherein the motion plan comprises one or more parameters associated with the motion of the autonomous vehicle. ### Claim 14 (depends on 13) The autonomous vehicle of claim 13, wherein the one or more parameters associated with the motion of the autonomous vehicle comprise at least one of a trajectory of the autonomous vehicle or a speed of the autonomous vehicle. ### Claim 15 A computer-implemented method, comprising: obtaining data associated with a plurality of objects that are within an environment of an autonomous vehicle, wherein the data comprises respective predicted paths for the plurality of objects; generating cost data associated with the plurality of objects, wherein the cost data for a respective object, of the plurality of objects, is indicative of an effect of controlling a motion of the autonomous vehicle such that the autonomous vehicle travels behind or in front of the respective object; outputting data indicative of the cost data associated with the plurality of objects; determining a motion plan for the autonomous vehicle based at least in part on the cost data; and causing the autonomous vehicle to implement at least a portion of the motion plan for the autonomous vehicle. ### Claim 16 (depends on 15) The computer-implemented method of claim 15, wherein the motion plan comprises one or more parameters associated with the motion of the autonomous vehicle. ### Claim 17 (depends on 16) The computer-implemented method of claim 16, wherein the motion plan comprises a distance between the autonomous vehicle and at least one object of the plurality of objects, and wherein the motion plan is indicative of a modulation of a speed of the autonomous vehicle such that the autonomous vehicle maintains at least the distance between the autonomous vehicle and the at least one object. ### Claim 18 (depends on 15) The computer-implemented method of claim 15, wherein the predicted path of at least one object of the plurality of objects indicates that the at least one object is predicted to travel in a travel lane in which the autonomous vehicle is currently or will be travelling. ### Claim 19 (depends on 15) The computer-implemented method of claim 15, wherein the cost data is further indicative of an effect of controlling the motion of the autonomous vehicle such that the autonomous vehicle travels behind or in front of the respective object. ### Claim 20 (depends on 1) The computing system of claim 1, wherein the autonomous vehicle is an autonomous truck.