# US 12,762,946 B2 · System and method for determining road work zone start location > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 12,762,946 B2 - Document ID: US12762946B2 - Status: Granted - Kind: B2 - Application number: 18/077,734 - Filed: 2022-12-08 - Published: 2024-06-13 - Granted: 2026-10-13 - Earliest claimed: 2022-12-08 - Assignees: HERE Global B.V. - Applicants: HERE Global B.V. - Inventors: Leon Stenneth; Bruce Bernhardt; Advait Mohan Raut; Jingwei Xu; Alex Averbuch; Weimin Huang - Web page: https://patentgrep.com/patent/US12762946B2 ## CPC - G08G 1/0112: {from the vehicle, e.g. floating car data [FCD]} - G06V 20/58: Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads - G06Q 50/08: Construction - 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}) - G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING - G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR ## Abstract The disclosure provides a system, a method, and a computer program product for detecting a road work zone. The method comprises detecting a road object based on sensor data and map data. The method may include determining a first location associated with the road object based on location of a vehicle capturing the road object at a time of road object sighting and the sensor data. The method may include, based on image data captured by the vehicle at the time of road object sighting, determining a road object type and supplemental information associated with the road object. The method further includes, detecting the road work zone based on the first location, the road object type, and the supplemental information. ## Claims ### Claim 1 A method for detecting a road work zone, comprising: detecting a road object based on sensor data and map data; determining a first location associated with the road object based on a location of a vehicle capturing the road object at a time of the road object sighting and the sensor data, wherein the road object is a road work sign indicating a distance to a start of the road work zone; based on determining that a map matching of the first location to a road or a link is successful, using a computer vision system to process image data to detect a road object type and supplemental information associated with the road object, wherein the image data was captured by the vehicle at the time of the road object sighting, and wherein the supplemental information comprises the distance to the start of the road work zone indicated on the road work sign; detecting the road work zone based on the first location, the road object type, and the supplemental information; and initiating a transitioning of an autonomous vehicle from an autonomous driving mode to a manual driving mode based on the detected work zone. ### Claim 2 (depends on 1) The method of claim 1, wherein the supplemental information further comprises unit information associated with the road object type, wherein the unit information indicates a unit of distance measurement associated with the distance to the start of the road work zone, and wherein the computer vision system is further used to process the image data to detect the unit information. ### Claim 3 (depends on 2) The method of claim 2, wherein detecting the road work zone further comprises: projecting the supplemental information from the first location along a route of the vehicle, until a distance measure associated with the distance information is reached; identifying a second location based on the projection; and determining the second location as a start location of the detected road work zone. ### Claim 4 (depends on 3) The method of claim 3, further comprising: clustering a plurality of locations associated with a plurality of road observations for the road object, wherein each location in the plurality of locations is the corresponding second location for that road observation; determining a centroid location for the cluster of the plurality of locations; and determining start location of the detected work zone based on the determined centroid. ### Claim 5 (depends on 4) The method of claim 4, wherein the plurality of locations is on the same route, same direction and within a distance threshold. ### Claim 6 (depends on 4) The method of claim 4, wherein the centroid is a mean location of the plurality of locations in a same cluster. ### Claim 7 (depends on 4) The method of claim 4, wherein the clustering is done using a DB-SCAN algorithm. ### Claim 8 (depends on 1) The method of claim 1, wherein the road object type is a start of construction indication sign. ### Claim 9 A system for detecting a road work zone, the system comprising: at least one non-transitory memory configured to store computer executable instructions; and at least one processor configured to execute the computer executable instructions to: detect a road object based on sensor data and map data; determine a first location associated with the road object based on location of a vehicle capturing the road object at a time of road object sighting and the sensor data, wherein the road object is a road work sign indicating a distance to a start of the road work zone; based on determining that a map matching of the first location to a road or a link is successful, use a computer vision system to process image data to detect a road object type and supplemental information associated with the road object, wherein the image data was captured by the vehicle at the time of the road object sighting, and wherein the supplemental information comprises the distance to the start of the road work zone indicated on the road work sign; detect the road work zone based on the first location, the road object type, and the supplemental information; and initiate a transitioning of an autonomous vehicle from an autonomous driving mode to a manual driving mode based on the detected work zone. ### Claim 10 (depends on 9) The system of claim 9, wherein the supplemental information further comprises unit information associated with the road object type, wherein the unit information indicates a unit of distance measurement associated with the distance to the start of the road work zone, and wherein the computer vision system is further used to process the image data to detect the unit information. ### Claim 11 (depends on 10) The system of claim 10, wherein the at least one processor is configured to execute the computer executable instructions to: project the supplemental information from the first location along a route of the vehicle, until a distance measure associated with the distance information is reached; identify a second location based on the projection; and determine the second location as a start location of the detected road work zone. ### Claim 12 (depends on 11) The system of claim 11, wherein the at least one processor is configured to execute the computer executable instructions to: cluster a plurality of locations associated with a plurality of road observations for the road object, wherein each location in the plurality of locations is the corresponding second location for that road observation; determine a centroid location for the cluster of the plurality of locations; and determine a start location of the detected road work zone based on the determined centroid. ### Claim 13 (depends on 12) The system of claim 12, wherein the plurality of locations is on a same route, a same direction and within a distance threshold. ### Claim 14 (depends on 12) The system of claim 12, wherein the centroid is a mean location of the plurality of locations in a same cluster. ### Claim 15 (depends on 12) The system of claim 12, wherein the clustering is done using a DB-SCAN algorithm. ### Claim 16 (depends on 9) The system of claim 9, wherein the road object type is a start of construction indication sign. ### Claim 17 A computer programmable product comprising a non-transitory computer readable medium having stored thereon computer executable instruction which when executed by one or more processors, cause the one or more processors to carry out operations for detecting a road work zone, the operations comprising: detecting a road object based on sensor data and map data; determining a first location associated with the road object based on location of a vehicle capturing the road object at a time of road object sighting and the sensor data, wherein the road object is a road work sign indicating a distance to a start of the road work zone; based on determining that a map matching of the first location to a road or a link is successful, using a computer vision system to process image data to detect a road object type and supplemental information associated with the road object, wherein the image data was captured by the vehicle at the time of the road object sighting, and wherein the supplemental information comprises the distance to the start of the road work zone indicated on the road work sign; detecting the road work zone based on the first location, the road object type, and the supplemental information; and initiating a transitioning of an autonomous vehicle from an autonomous driving mode to a manual driving mode based on the detected work zone. ### Claim 18 (depends on 17) The computer programmable product of claim 17, wherein the supplemental information further comprises unit information associated with the road object type, wherein the unit information indicates a unit of distance measurement associated with the distance to the start of the road work zone, and wherein the computer vision system is further used to process the image data to detect the unit information. ### Claim 19 (depends on 17) The computer programmable product of claim 17, wherein detecting the road work zone further comprises: projecting the supplemental information from the first location along a route of the vehicle, until a distance measure associated with the distance information is reached; identifying a second location based on the projection; and determining the second location as a start location of the detected road work zone. ### Claim 20 (depends on 17) The computer programmable product of claim 17, wherein the operations further comprise: clustering a plurality of locations associated with a plurality of road observations for the road object, wherein each location in the plurality of locations is the corresponding second location for that road observation; determining a centroid location for the cluster of the plurality of locations; and determining start location of the detected work zone based on the determined centroid.