# US 11,993,281 B2 · Learning in lane-level route planner > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 11,993,281 B2 - Document ID: US11993281B2 - Status: Granted - Kind: B2 - Application number: 17/186,987 - Filed: 2021-02-26 - Published: 2022-09-01 - Granted: 2024-05-28 - Earliest claimed: 2021-02-26 - Assignees: Nissan North America, Inc.; University of Massachusetts - Applicants: Nissan North America, Inc.; The University of Massachusetts - Inventors: Kyle Hollins Wray; Stefan Witwicki; Shlomo Zilberstein - Web page: https://patentgrep.com/patent/US11993281B2 ## CPC - B60W 60/001: {Planning or execution of driving tasks} - B60W 40/04: Traffic conditions - B60W 60/0053: {from vehicle to occupant} - G01C 21/3407: {specially adapted for specific applications} - G01C 21/3461: {Preferred or disfavoured areas, e.g. dangerous zones, toll or emission zones, intersections, manoeuvre types or segments such as motorways, toll roads or ferries} - G01C 21/3837: {Data obtained from a single source} - G01C 21/3841: {Data obtained from two or more sources, e.g. probe vehicles} - G01C 21/3889: {Transmission of selected map data, e.g. depending on route} - G08G 1/167: {Driving aids for lane monitoring, lane changing, e.g. blind spot detection} - B60W 2554/4029: Pedestrians - B60W 2554/404: Characteristics - B60W 2556/50: of positioning data, e.g. GPS [Global Positioning System] data - 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 Lane-level route planning includes obtaining lane-level information of a road, where the road includes a first lane and a second lane and the lane-level information includes first lane information related to the first lane and second lane information related to the second lane; converting the lane-level information to probabilities for a state transition function; receiving a destination; and obtaining a policy as a solution to a model that uses the state transition function. ## Claims ### Claim 1 A method for lane-level route planning, comprising: obtaining lane-level information of a road, wherein the road comprises a first lane and a second lane, and wherein the lane-level information comprises first lane information related to the first lane and second lane information related to the second lane; converting the lane-level information to probabilities for a state transition function; obtaining a policy as a solution to a model that uses the state transition function, wherein, given that a vehicle is on a first lane segment, the policy provides an action for controlling the vehicle with respect to moving to a second lane segment that neighbors the first lane segment, wherein the model is a decision process that incorporates, into a cost function, a user preference for objectives including a first objective relating to comfort, a second objective relating to autonomy, and a third objective relating to urban lane segments, and a user input indicating a slack time for alternative routes to a destination relative to the user preference, wherein the cost function represents an expected immediate cost of performing the action in a state, wherein the first objective relating to comfort indicates a preference for lane segments where traffic moves at speeds that are within a threshold speed of speed limits on the lane segments, wherein the second objective relating to autonomy indicates a preference for lane segments where an autonomous vehicle (AV) can be autonomously controlled as opposed to being manually controlled, wherein the third objective relating to urban lane segments indicates whether to maximize selection of lane segments classified as urban over lane segments that are not classified as urban, and wherein the slack time indicates an allowable deviation in travel time relative to the user preference; receiving the destination; and at time steps along a route to the destination, autonomously controlling the AV according to one or more respective actions obtained from the policy based on respective current lanes of the AV. ### Claim 2 (depends on 1) The method of claim 1, wherein the lane-level information is obtained at a host vehicle. ### Claim 3 (depends on 1) The method of claim 1, wherein the lane-level information is obtained from several vehicles. ### Claim 4 (depends on 1) The method of claim 1, wherein the lane-level information comprises at least two of environment information, vehicle information, or human information. ### Claim 5 (depends on 4) The method of claim 4, wherein the environment information comprises at least two of traffic patterns, pedestrian patterns, or traversal difficulties information of lane segments. ### Claim 6 (depends on 4) The method of claim 4, wherein the vehicle information comprises preferred routes of a user and transfer of control requests by the user. ### Claim 7 (depends on 1) The method of claim 1, wherein obtaining the lane-level information of the road comprises: recording first times of automated traversal of the road with stop on the road; recording second times of automated traversal of the road without stops on the road; recording third times of manual traversal of the road with stop on the road; and recording fourth times of manual traversal of the road without stops on the road. ### Claim 8 (depends on 1) The method of claim 1, wherein obtaining the lane-level information of the road comprises: recording successor lane segments during manual traversal. ### Claim 9 (depends on 1) The method of claim 1, wherein obtaining the lane-level information of the road comprises: recording overrides by a human of an automated travel control. ### Claim 10 An apparatus for lane-level route planning, comprising: a processor configured to: obtain lane-level information of a road, wherein the road comprises a first lane and a second lane, and wherein the lane-level information comprises first lane information related to the first lane and second lane information related to the second lane; convert the lane-level information to a state transition function; obtain a policy as a solution to a model that uses the state transition function, wherein, given that a vehicle is on a first lane segment, the policy provides an action for controlling the vehicle with respect to moving to a second lane segment that neighbors the first lane segment, wherein the model incorporates, into a cost function, a user preference for objectives including at least a first objective relating to comfort and a second objective relating to urban lane segments, and a user input indicating a slack time for alternative routes to a destination relative to the user preference, wherein the cost function represents an expected immediate cost of performing the action in a state, wherein the first objective relating to comfort indicates a preference for lane segments where traffic moves at speeds that are within a threshold speed of speed limits on the lane segments, wherein the second objective relating to urban lane segments indicates whether to maximize selection of lane segments classified as urban, and wherein the slack time indicates an allowable deviation in travel time relative to the user preference; receive the destination over lane segments that are not classified as urban; and at time steps along a route to the destination, autonomously control an AV according to one or more respective actions obtained from the policy based on respective current lanes of the AV. ### Claim 11 (depends on 10) The apparatus of claim 10, wherein the lane-level information is obtained from a host vehicle. ### Claim 12 (depends on 10) The apparatus of claim 10, wherein the lane-level information is obtained from several vehicles. ### Claim 13 (depends on 10) The apparatus of claim 10, wherein the lane-level information comprises at least two of environment information, vehicle information, or human information. ### Claim 14 (depends on 13) The apparatus of claim 13, wherein the environment information comprises at least two of traffic patterns, pedestrian patterns, or traversal difficulties information of lane segments. ### Claim 15 (depends on 13) The apparatus of claim 13, wherein the vehicle information comprises preferred routes of a user, transfer of control requests by the user. ### Claim 16 (depends on 10) The apparatus of claim 10, wherein obtaining the lane-level information of the road comprises: recording first times of automated traversal of the road with stop on the road; recording second times of automated traversal of the road without stops on the road; recording third times of manual traversal of the road with stop on the road; and recording fourth times of manual traversal of the road without stops on the road. ### Claim 17 (depends on 10) The apparatus of claim 10, wherein obtaining the lane-level information of the road comprises: recording successor lane segments during manual traversal; and recording overrides by a human of an automated travel control. ### Claim 18 (depends on 10) The apparatus of claim 10, wherein the objectives further include a third objective relating to autonomy, wherein the third objective relating to autonomy indicates a preference for lane segments where an autonomous vehicle (AV) can be autonomously controlled as opposed to being manually controlled. ### Claim 19 A non-transitory computer-readable storage medium, comprising executable instructions that, when executed by a processor, facilitate performance of operations comprising operations to: receive from vehicles traversing a road respective lane-level information; obtain a navigation map from lane-level information received from the vehicles, the navigation map comprising a state transition graph and a reward function, wherein the lane-level information comprises at least two of environment information, vehicle information, or human information; transmit the navigation map to a vehicle, wherein the vehicle uses the navigation map to obtain lane-level routes; obtain a policy as a solution to a model that uses the state transition function, wherein, given that a vehicle is on a first lane segment, the policy provides an action for controlling the vehicle with respect to moving to a second lane segment that neighbors the first lane segment, wherein the model incorporates, into a cost function, a user preference for objectives including a first objective relating to urban lane segments and a second objective relating to comfort, and a user input indicating a slack time for alternative routes to a destination relative to the user preference, wherein the cost function represents an expected immediate cost of performing the action in a state, wherein the first objective relating to urban lane segments indicates whether to maximize selection of lane segments classified as urban over lane segments that are not classified as urban, wherein the second objective relating to comfort indicates a preference for lane segments where traffic moves at speeds that are within a threshold speed of speed limits on the lane segments, and wherein the slack time indicates an allowable deviation in travel time relative to the user preference; receive the destination; and at time steps along the lane-level routes to the destination, autonomously control an AV according to one or more respective actions obtained from the policy based on respective current lanes of the AV. ### Claim 20 (depends on 19) The non-transitory computer-readable storage medium of claim 19, wherein the objectives further include: a third objective relating to autonomy that indicates a preference for lane segments where an autonomous vehicle (AV) can be autonomously controlled as opposed to being manually controlled.