# US 12,183,203 B2 · Knowledge transfer for early unsafe driving behavior recognition > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 12,183,203 B2 - Document ID: US12183203B2 - Status: Granted - Kind: B2 - Application number: 17/578,677 - Filed: 2022-01-19 - Published: 2023-07-20 - Granted: 2024-12-31 - Earliest claimed: 2022-01-19 - Assignees: Toyota Motor Engineering & Manufacturing North America, Inc. - Applicants: Toyota Motor Engineering & Manufacturing North America, Inc. - Inventors: Seyhan Ucar; Takamasa Higuchi; Kentaro Oguchi - Web page: https://patentgrep.com/patent/US12183203B2 ## CPC - G08G 1/096716: {where the received information does not generate an automatic action on the vehicle control} - G08G 1/162: {event-triggered} - B60W 40/09: Driving style or behaviour - G08G 1/096791: {where the origin of the information is another vehicle} - G08G 1/166: {for active traffic, e.g. moving vehicles, pedestrians, bikes} - H04W 4/029: Location-based management or tracking services - H04W 4/46: for vehicle-to-vehicle communication [V2V] - 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}) - 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 - H04W: WIRELESS COMMUNICATION NETWORKS (broadcast communication H04H; communication systems using wireless links for non-selective communication, e.g. wireless extensions H04M1/72) ## Abstract Systems and methods of unsafe driving detection are provided which share partial unsafe driving behavior analyses with others in order to ensure that unsafe driving behavior is detected as early as possible. For example, in response to an event which interrupts a first detecting vehicle from collecting additional driving behavior data associated with a subject vehicle, the first detecting vehicle may transfer driving behavior data it has already collected and processed, to another detecting entity (e.g., a second detecting vehicle) in observable range of the subject vehicle. ## Claims ### Claim 1 A computer-implemented method comprising: collecting, by a first detecting vehicle, driving behavior data associated with a subject vehicle; processing, by the first detecting vehicle, the collected driving behavior data to determine whether the subject vehicle is driving unsafely; and in response to a second detecting vehicle merging in between the first detecting vehicle and the subject vehicle, transferring, by the first detecting vehicle, the processed driving behavior data to the second detecting vehicle. ### Claim 2 (depends on 1) The computer-implemented method of claim 1, wherein, processing the collected driving behavior data to determine whether the subject vehicle is driving unsafely comprises: detecting, by the first detecting vehicle, unsafe driving behavior by the subject vehicle based on the collected driving behavior data; and determining, by the first detecting vehicle, that the detected unsafe driving behavior does not satisfy a threshold factor for unsafe driving behavior that indicates the subject vehicle is driving unsafely. ### Claim 3 (depends on 2) The computer-implemented method of claim 2, wherein processing the collected driving behavior data to determine whether the subject vehicle is driving unsafely comprises: detecting, by the first detecting vehicle, swerving by the subject vehicle based on lane offset measurements; and determining, by the first detecting vehicle, that the detected swerving does not satisfy a threshold swerving factor that indicates the subject vehicle is driving unsafely. ### Claim 4 (depends on 1) The computer-implemented method of claim 1, wherein the collected driving behavior data comprises lane offset measurements for the subject vehicle. ### Claim 5 (depends on 1) The computer-implemented method of claim 1, wherein the driving behavior data is collected from one or more image and proximity sensors of the first detecting vehicle. ### Claim 6 (depends on 1) The computer-implemented method of claim 1, further comprising: constructing, by the first detecting vehicle, a pseudo-identification for the subject vehicle; and in response to the second detecting vehicle merging in between the first detecting vehicle and the subject vehicle, transferring, by the first detecting vehicle, the pseudo-identification to the second detecting vehicle. ### Claim 7 (depends on 6) The computer-implemented method of claim 6, wherein the pseudo-identification comprises one or more hash values corresponding to at least one of the following: vehicle type; vehicle color; or location of the subject vehicle within a road section. ### Claim 8 (depends on 1) The computer-implemented method of claim 1, further comprising: determining, by the first detecting vehicle, that the second detecting vehicle intends to merge in between the first detecting vehicle and the subject vehicle; and before the second detecting vehicle merges in between the first detecting vehicle and the subject vehicle, notifying, by the first detecting vehicle, the second detecting vehicle that the first detecting vehicle intends to transfer the processed driving behavior data to the second detecting vehicle. ### Claim 9 A detecting vehicle comprising: one or more processers including machine executable instructions in non-transitory memory to cause the detecting vehicle to: collect driving behavior data associated with a subject vehicle; process the collected driving behavior data to determine whether the subject vehicle is driving unsafely; and in response to a second detecting vehicle merging in between the detecting vehicle and the subject vehicle, transfer the processed driving behavior data to the second detecting vehicle. ### Claim 10 (depends on 9) The detecting vehicle of claim 9, wherein the machine executable instructions include further instructions to: construct a pseudo-identification for the subject vehicle; and in response to the second detecting vehicle merging in between the detecting vehicle and the subject vehicle, transfer the pseudo-identification to the second detecting vehicle. ### Claim 11 (depends on 10) The detecting vehicle of claim 10, wherein the pseudo-identification comprises one or more hash values corresponding to at least one of the following: vehicle type; vehicle color; or location of the subject vehicle within a road section. ### Claim 12 (depends on 9) The detecting vehicle of claim 9, wherein the received driving behavior data comprises raw driving behavior data and processed driving behavior data. ### Claim 13 (depends on 12) The detecting vehicle of claim 12, wherein: the raw driving behavior data comprises lane offset measurements for the subject vehicle; and the processed driving behavior data comprises detected swerving by the subject vehicle. ### Claim 14 (depends on 13) The detecting vehicle of claim 13, wherein the instruction to determine that the subject vehicle is driving unsafely comprises an instruction to: based on the driving behavior data, detect an amount of swerving by the subject vehicle which satisfies a threshold swerving factor that indicates the subject vehicle is driving unsafely. ### Claim 15 A computer-implemented method comprising: collecting, by a first detecting vehicle, driving behavior data associated with a subject vehicle; processing, by the first detecting vehicle, the collected driving behavior data to determine whether the subject vehicle is driving unsafely; determining, by the first detecting vehicle, that a second detecting vehicle intends to merge in between the first detecting vehicle and the subject vehicle; before the second detecting vehicle merges in between the first detecting vehicle and the subject vehicle, notifying, by the first detecting vehicle, the second detecting vehicle that the first detecting vehicle intends to transfer the processed driving behavior data to the second detecting vehicle; and in response to the second detecting vehicle merging in between the first detecting vehicle and the subject vehicle, transferring, by the first detecting vehicle, the processed driving behavior data to the second detecting vehicle. ### Claim 16 (depends on 15) The computer-implemented method of claim 15, further comprising: constructing, by the first detecting vehicle, a pseudo-identification for the subject vehicle; and transferring, by the first detecting vehicle, the pseudo-identification to the second detecting vehicle. ### Claim 17 (depends on 16) The computer-implemented method of claim 16, wherein the pseudo-identification comprises one or more hash values corresponding to at least one of the following: vehicle type; vehicle color; or location of the subject vehicle within a road section. ### Claim 18 (depends on 15) The computer-implemented method of claim 15, further comprising: determining, by the first detecting vehicle, that the subject vehicle is within observable range of the second detecting vehicle. ### Claim 19 (depends on 15) The computer-implemented method of claim 15, wherein the driving behavior data associated with the subject vehicle comprises lane offset measurements for the subject vehicle. ### Claim 20 (depends on 19) The computer-implemented method of claim 19, wherein processing the collected driving behavior data to determine whether the subject vehicle is driving unsafely comprises: detecting, by the first detecting vehicle, swerving by the subject vehicle based on the lane offset measurements; and determining, by the first detecting vehicle, that the detected swerving does not satisfy a threshold swerving factor that indicates the subject vehicle is driving unsafely.