# US 12,602,048 B2 · Travel route generation method for autonomous vehicle and control apparatus for autonomous vehicle > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 12,602,048 B2 - Document ID: US12602048B2 - Status: Granted - Kind: B2 - Application number: 18/184,684 - Filed: 2023-03-16 - Published: 2024-09-19 - Granted: 2026-04-14 - Earliest claimed: 2023-03-16 - Assignees: Honda Motor Co., Ltd. - Applicants: Honda Motor Co., Ltd. - Inventors: Yoichi Natori - Web page: https://patentgrep.com/patent/US12602048B2 ## CPC - G01C 21/20: Instruments for performing navigational calculations (G01C21/24, G01C21/26 take precedence) - G05D 1/0214: {in accordance with safety or protection criteria, e.g. avoiding hazardous areas (monitoring the location of vehicles within a certain area, e.g. forbidden or allowed areas, in traffic control systems for road vehicles G08G1/13)} - B60W 60/001: {Planning or execution of driving tasks} - G01C 21/3407: {specially adapted for specific applications} - 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} - G05D 1/0246: {using a video camera in combination with image processing means} - G05D 1/0278: {using satellite positioning signals, e.g. GPS} - G06T 7/13: Edge detection - G06T 2207/30252: Vehicle exterior; Vicinity of vehicle - 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) - 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 - G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL ## Abstract Problem to be solved: Provided is a travel route generation method that is for an autonomous vehicle and enables a travel route to be accurately generated, even in a case where positioning using GPS or the like is unavailable and the boundary of a travel path is unclear. Solution: Scene information that includes a travel path is obtained by sensing surroundings of the autonomous vehicle, a boundary of the travel path is detected based on the obtained scene information, a likelihood based on machine learning is used to evaluate the detected boundary, and a provisional travel route on the travel path for the autonomous vehicle is generated based on the boundary and in accordance with the likelihood for the boundary. ## Claims ### Claim 1 A travel route generation method for an autonomous vehicle, the method comprising: obtaining, by sensing surroundings of the autonomous vehicle, scene information that includes a travel path, for one frame at a predetermined sampling cycle detecting a boundary of the travel path based on the obtained scene information: using a likelihood based on machine learning to evaluate the detected boundary; generating, based on the boundary, a provisional travel route on the travel path for the autonomous vehicle such that a safety margin is formed between the provisional travel route and the boundary, and setting a size of the safety margin in accordance with the likelihood for the boundary, wherein for a plurality of the provisional travel routes generate based on the boundary detected based on the scene information for each one frame, it is determined whether or not there is a deviation greater than or less than a preset range for amounts of deviation between the provisional travel route newly generated based on the scene information for one frame and the provisional travel route generated based on the scene information for another one frame previous to the one frame in a case where the deviation is present, the provisional travel route is updated to the provisional travel route newly generated and in a case where the deviation is not present, the provisional travel route is not updated to the provisional travel route newly generated. ### Claim 2 (depends on 1) The method according to claim 1, wherein the boundary of the travel path is detected by performing segmentation on the obtained scene information. ### Claim 3 (depends on 1) The method according to claim 1, wherein in a situation where it is possible to identify a self position of the autonomous vehicle, a normal travel route for the autonomous vehicle to a destination is generated based on the identified self position, and in a poor situation for identification of the self position of the autonomous vehicle, the provisional travel route is generated based on the boundary, and the provisional travel route is corrected based on a relative angle of a direction of the destination with respect to a self position and orientation of the autonomous vehicle immediately before the poor situation for identification of the self position was entered. ### Claim 4 A control apparatus for an autonomous vehicle, the apparatus comprising: a processor configured to detect a boundary of a travel path based on scene information that includes the travel path in relation to forward of the autonomous vehicle and is obtained by a sensor for one frame at a predetermined sampling cycle, generate, based on the boundary detected, a provisional travel route for the autonomous vehicle on the travel path, and use a likelihood based on machine learning to evaluate the boundary, wherein the processor generates the provisional travel route based on the boundary such that a safety margin is formed between the provisional travel route and the boundary, and sets a size of the safety margin in accordance with the likelihood for the boundary, for a plurality of the provisional travel routes generated based on the boundary detected based on the scene information for each one frame, the processor determines whether or not there is a deviation greater than or less than a preset range for amounts of deviation, between the provisional travel route newly generated based on the scene information for one frame and the provisional travel route generated based on the scene information for another one frame previous to the one frame, in a case where the deviation is present, the processor updates the provisional travel route to the provisional travel route newly generated, and in a case where the deviation is not present, the processor does not update the provisional travel route to the provisional travel route newly generated. ### Claim 5 (depends on 4) The control apparatus according to claim 4, wherein the processor detects the boundary of the travel path by performing segmentation on the scene information obtained by the sensor. ### Claim 6 (depends on 4) The control apparatus according to claim 4, wherein the processor is further configured to identify a self position of the autonomous vehicle, generate, in a situation where the processor can identify the self position, a normal travel route to a destination based on the identified self position of the autonomous vehicle, and generate, in a poor situation for identification of the self position by the processor, the provisional travel route based on the boundary and correct the provisional travel route based on a relative angle of a direction of the destination with respect to a self position and orientation of the autonomous vehicle immediately before the poor situation for identification of the self position was entered.