# US 2023/0053674 A1 · System and method for connected vehicle-based advanced detection of slow-down events > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2023/0053674 A1 - Document ID: US20230053674A1 - Status: Published application - Kind: A1 - Application number: 17/708,531 - Filed: 2022-03-30 - Published: 2023-02-23 - Earliest claimed: 2021-08-23 - Assignees: Honda Motor Co., Ltd. - Applicants: Honda Motor Co., Ltd. - Inventors: Yasir Khudhair AL-NADAWI; Laith DAMAN; Hossein NOURKHIZ MAHJOUB - Web page: https://patentgrep.com/patent/US20230053674A1 ## CPC - B60W 40/04: Traffic conditions - G08G 1/0141: {for traffic information dissemination} - B60W 40/105: Speed - G08G 1/0112: {from the vehicle, e.g. floating car data [FCD]} - G08G 1/0133: {for classifying traffic situation} - G08G 1/0145: {for active traffic flow control} - B60W 2050/0052: {Filtering, filters} - B60W 2554/4041: Position - B60W 2554/4049: Relationship among other objects, e.g. converging dynamic objects - B60W 2556/45: External transmission of data to or from the vehicle - 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 - 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 Systems and methods for detecting a traffic event include receiving vehicle data from a plurality of vehicles travelling along a roadway. The method also includes where the roadway is discretized at a cell level into a plurality of cells. The method also includes identifying vehicles of interest that are within a communication range of a host vehicle. Each of the vehicles of interest are associated with a cell of interest from the plurality of cells. Further, the method includes for each cell of interest at each timestep according to a measurement update interval, calculating an average deceleration based on vehicle data transmitted from each of the vehicles of interest associated with the cell of interest. Additionally, the method includes detecting the traffic event based on the average deceleration for each cell of interest at each timestep. ## Claims ### Claim 1 A computer-implemented method for detecting a traffic event on a roadway, comprising: receiving vehicle data from a plurality of vehicles travelling along the roadway, wherein the roadway is discretized at a cell level into a plurality of cells; identifying vehicles of interest that are within a communication range of a host vehicle, wherein each of the vehicles of interest are associated with a cell of interest from the plurality of cells; for each cell of interest at each timestep according to a measurement update interval, calculating an average deceleration based on vehicle data transmitted from each of the vehicles of interest associated with the cell of interest; and detecting a traffic event based on the average deceleration for each cell of interest at each timestep. ### Claim 2 (depends on 1) The computer-implemented method of claim 1, including discretizing the roadway spatially and temporally at the cell level into the plurality of cells. ### Claim 3 (depends on 1) The computer-implemented method of claim 1, wherein the vehicle data transmitted from each of the vehicles of interest includes an instantaneous speed. ### Claim 4 (depends on 3) The computer-implemented method of claim 3, wherein the instantaneous speed is filtered according to a predefined time window applied to consecutive measurement update intervals. ### Claim 5 (depends on 1) The computer-implemented method of claim 1, wherein detecting the traffic event includes comparing the average deceleration of each cell in the cells of interest with a first type threshold, wherein the first type threshold defines a deceleration measurement associated with a first slow-down traffic event. ### Claim 6 (depends on 5) The computer-implemented method of claim 5, wherein the first slow-down traffic event is one of a hard-braking traffic event and a coasting down traffic event. ### Claim 7 (depends on 5) The computer-implemented method of claim 5, further including identifying successive cells in the cells of interest that satisfy the first type threshold at each timestep. ### Claim 8 (depends on 5) The computer-implemented method of claim 5, further including comparing the average deceleration of each cell in the cells of interest with a second type threshold, wherein the second type threshold defines a second deceleration measurement associated with a second slow-down traffic event and identifying successive cells in the cells of interest that satisfy the second type threshold at each timestep. ### Claim 9 (depends on 8) The computer-implemented method of claim 8, wherein the first slow-down traffic event is a hard-braking traffic event and the second slow-down traffic event is a coasting down traffic event. ### Claim 10 (depends on 1) The computer-implemented method of claim 1, including controlling the host vehicle based on a type of the traffic event, wherein the type of the traffic event is one of a hard-braking traffic event and a coasting down traffic event. ### Claim 11 A system for detecting a traffic event on a roadway, comprising: a communication interface for communicating vehicle data from vehicles of interest travelling along the roadway within a communication range; and a processor operatively connected for computer communication with the communication interface, wherein the processor: discretizes the roadway at a cell level into a plurality of cells; receives the vehicle data from the vehicles of interest, wherein each of the vehicles of interest are located within a cell of interest from the plurality of cells; for each of the cells of interest at each timestep, calculating an average deceleration based on vehicle data transmitted from each of the vehicles of interest associated with the cell of interest; and detecting a traffic event based on the average deceleration for each cell of interest at each timestep. ### Claim 12 (depends on 11) The system of claim 11, wherein the vehicle data transmitted from each of the vehicles of interest includes an instantaneous speed and calculating the average deceleration is based on the instantaneous speed of each vehicle of interest located within the cell of interest. ### Claim 13 (depends on 11) The system of claim 11, wherein detecting the traffic event is based on the average deceleration of each cell in the cells of interest, a first type threshold, and a second type threshold, wherein the first type threshold defines a first deceleration measurement associated with a first slow-down traffic event and the second type threshold defines a second deceleration measurement associated with a second slow-down traffic event. ### Claim 14 (depends on 13) The system of claim 13, wherein the first slow-down traffic event is one of a hard-braking traffic event and a coasting down traffic event. ### Claim 15 (depends on 13) The system of claim 13, wherein detecting the traffic event includes identifying successive cells in the cells of interest that satisfy the first type threshold at each timestep and identifying successive cells in the cells of interest that satisfy the second type threshold at each timestep. ### Claim 16 A non-transitory computer-readable storage medium including instructions that when executed by a processor, causes the processor to: receive vehicle data from a plurality of vehicles travelling along a roadway, wherein the roadway is discretized at a cell level into a plurality of cells; identify vehicles of interest that are within a communication range of a host vehicle, wherein each of the vehicles of interest are associated with a cell of interest from the plurality of cells; for each cell of interest at each timestep according to a measurement update interval, calculate an average deceleration based on vehicle data transmitted from each of the vehicles of interest associated with the cell of interest; and detect a traffic event based on the average deceleration for each cell of interest at each timestep. ### Claim 17 (depends on 16) The non-transitory computer-readable storage medium of claim 16, wherein the vehicle data transmitted from each of the vehicles of interest includes an instantaneous speed, and the average deceleration is calculated based on the instantaneous speed of each vehicle of interest located within the cell of interest. ### Claim 18 (depends on 16) The non-transitory computer-readable storage medium of claim 16, further causing the processor to detect detecting the traffic event based on the average deceleration of each cell in the cells of interest, a first type threshold, and a second type threshold, wherein the first type threshold defines a first deceleration measurement associated with a first slow-down traffic event and the second type threshold defines a second deceleration measurement associated with a second slow-down traffic event. ### Claim 19 (depends on 18) The non-transitory computer-readable storage medium of claim 18, wherein the first slow-down traffic event is one of a hard-braking traffic event and a coasting down traffic event. ### Claim 20 (depends on 19) The non-transitory computer-readable storage medium of claim 19, further causing the processor to identify successive cells in the cells of interest that satisfy the first type threshold at each timestep and identifying successive cells in the cells of interest that satisfy the second type threshold at each timestep.