# US 2023/0054889 A1 · Automatically tracking a trajectory of a vehicle > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2023/0054889 A1 - Document ID: US20230054889A1 - Status: Published application - Kind: A1 - Application number: 17/789,859 - Filed: 2020-12-30 - Published: 2023-02-23 - Earliest claimed: 2020-01-03 - Assignees: Valerann Ltd. - Applicants: Valerann Ltd. - Inventors: Ran KATZIR; Michael VARDI; Lior SIMCHON; Ido GLANZ; Shahar BAHIRI; Avi TEL-OR - Web page: https://patentgrep.com/patent/US20230054889A1 ## CPC - G08G 1/04: using optical or ultrasonic detectors - G08G 1/056: with provision for distinguishing direction of travel - G08G 1/0116: {from roadside infrastructure, e.g. beacons} - G08G 1/0133: {for classifying traffic situation} - G08G 1/0141: {for traffic information dissemination} - G08G 1/017: identifying vehicles (G08G1/015, G08G1/054 take precedence) - G08G 1/02: using treadles built into the road (pads or other sensitive devices responsive to passage of vehicles E01F11/00) - G08G 1/042: using inductive or magnetic detectors - G08G 1/096775: {where the origin of the information is a central station} - G08G 1/205: {Indicating the location of the monitored vehicles as destination, e.g. accidents, stolen, rental} - 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 A system and a method for automatically tracking location of a vehicle by receiving a plurality of feature vectors transmitted from a plurality of stationary sensors installed along a road. The feature vectors are related to a plurality of vehicles which are in a range of detection of the plurality of the stationary sensors. The method may include clustering a group of feature vectors from the plurality of feature vectors to a monitored vehicle based on a predetermined driving model, determining parameters of the monitored vehicle, calculating a next expected location of the monitored vehicle, receiving a feature vector, matching the feature vector to the monitored vehicle and tracking a trajectory of the monitored vehicle. ## Claims ### Claim 1 A method for automatically tracking a trajectory of a vehicle comprising: receiving a plurality of feature vectors transmitted from a plurality of stationary sensors installed along a road, wherein the feature vectors are related to a plurality of vehicles which are in a range of detection of said plurality of the stationary sensors; clustering a group of feature vectors from the plurality of feature vectors to a monitored vehicle based on a predetermined driving model; determining parameters of the monitored vehicle; calculating a next expected location of the monitored vehicle; receiving a feature vector; matching the feature vector to the monitored vehicle; and tracking a trajectory of the monitored vehicle. ### Claim 2 (depends on 1) The method of claim 1, further comprises identifying a driving pattern of the monitored vehicle based on the trajectory of the monitored vehicle. ### Claim 3 (depends on 1) The method of claim 1, wherein tracking a trajectory of the monitored vehicle comprises tracking a trajectory of the monitored vehicle with relation to one or more lanes defined along the road. ### Claim 4 (depends on 2) The method of claim 2, further comprises determining whether the driving pattern is in compliance with one or more predetermined rules. ### Claim 5 (depends on 2) The method of claim 2, further comprises determining a toll based on the driving pattern. ### Claim 6 (depends on 1) The method of claim 1, wherein the plurality of stationary sensors are located in a predetermined order along the road. ### Claim 7 (depends on 1) The method of claim 1, wherein clustering a group of feature vectors comprises: clustering two or more feature vectors if a distance between the two or more feature vectors is less than a predetermined distance. ### Claim 8 (depends on 1) The method of claim 1, wherein determining parameters of the monitored vehicle comprises calculating a position of the monitored vehicle in real time. ### Claim 9 (depends on 1) The method of claim 1, wherein determining parameters of the monitored vehicle comprises calculating a speed of the monitored vehicle in real time. ### Claim 10 (depends on 1) The method of claim 1, wherein determining parameters of the monitored vehicle comprises calculating an acceleration rate of the monitored vehicle in real time. ### Claim 11 (depends on 1) The method of claim 1, wherein the plurality of feature vectors comprise measurements detected by one or more sensors from the plurality of stationary sensors, wherein the one or more sensors are from a group consisting of a magnetic sensor, a vibration sensor, an acoustic sensor, a radar and a light sensor. ### Claim 12 (depends on 1) The method of claim 1, further comprises determining an identity of the monitored vehicle by matching the monitored vehicle with information related to the monitored vehicle received from an external source. ### Claim 13 (depends on 1) The method of claim 1, wherein tracking the trajectory of the monitored vehicle comprises analyzing the trajectory of the monitored vehicle for identifying road related information. ### Claim 14 A system for automatically tracking a trajectory of a vehicle comprising: a plurality of stationary sensors installed along a road, to transmit a plurality of feature vectors wherein the feature vectors are related to a plurality of vehicles which are in a range of detection of said plurality of the stationary sensors; a remote processing facility comprising a processor to: receive the plurality of feature vectors; cluster a group of feature vectors from the plurality of feature vectors to a monitored vehicle based on a predetermined driving model; determine parameters of the monitored vehicle; calculate a next expected location of the monitored vehicle; receive a feature vector; match the feature vector to the monitored vehicle; and track a trajectory of the monitored vehicle. ### Claim 15 (depends on 14) The system of claim 14, wherein the remote processing facility is to identify a driving pattern of the monitored vehicle based on the trajectory of the monitored vehicle. ### Claim 16 (depends on 14) The method of claim 14, wherein the remote processing facility is to track a trajectory of the monitored vehicle with relation to one or more lanes defined along the road. ### Claim 17 (depends on 15) The system of claim 15, wherein the remote processing facility is to determine whether the driving pattern is in compliance with one or more predetermined rules. ### Claim 18 (depends on 15) The system of claim 15, wherein the remote processing facility is to determine a toll based on the driving pattern. ### Claim 19 (depends on 14) The system of claim 14, wherein the plurality of stationary sensors are located in a predetermined order along the road. ### Claim 20 (depends on 14) The system of claim 14, wherein the remote processing facility is to cluster a group of feature vectors by clustering two or more feature vectors if a distance between the two or more feature vectors is less than a predetermined distance. ### Claim 21 (depends on 14) The system of claim 14, wherein the remote processing facility is to determine parameters of the monitored vehicle by calculating a position of the monitored vehicle in real time. ### Claim 22 (depends on 14) The system of claim 14, wherein the remote processing facility is to determine parameters of the monitored vehicle by calculating a speed of the monitored vehicle in real time. ### Claim 23 (depends on 14) The system of claim 14, wherein the remote processing facility is to determine parameters of the monitored vehicle by calculating an acceleration rate of the monitored vehicle in real time. ### Claim 24 (depends on 14) The system of claim 14, wherein the plurality of feature vectors comprise measurements detected by one or more sensors from the plurality of stationary sensors, wherein the one or more sensors are from a group consisting of a magnetic sensor, a vibration sensor, an acoustic sensor, a radar and a light sensor. ### Claim 25 (depends on 14) The system of claim 14, wherein the remote processing facility is to determine an identity of the monitored vehicle by matching the monitored vehicle with information related to the monitored vehicle received from an external source. ### Claim 26 (depends on 14) The system of claim 14, wherein tracking the trajectory of the monitored vehicle comprises analyzing the trajectory of the monitored vehicle for identifying road related information.