# US 12,008,905 B2 · Curb detection system for commercial vehicles > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 12,008,905 B2 - Document ID: US12008905B2 - Status: Granted - Kind: B2 - Application number: 17/372,720 - Filed: 2021-07-12 - Published: 2022-03-24 - Granted: 2024-06-11 - Earliest claimed: 2020-09-18 - Assignees: Stoneridge Electronics AB - Applicants: Stoneridge Electronics AB - Inventors: John Couperthwaite - Web page: https://patentgrep.com/patent/US12008905B2 ## CPC - G08G 1/165: {for passive traffic, e.g. including static obstacles, trees} - B60W 30/09: Taking automatic action to avoid collision, e.g. braking and steering - B60W 30/095: Predicting travel path or likelihood of collision - B60W 30/18145: {Cornering} - B60W 50/14: Means for informing the driver, warning the driver or prompting a driver intervention - G01S 15/86: Combinations of sonar systems with lidar systems; Combinations of sonar systems with systems not using wave reflection - G01S 15/89: for mapping or imaging - G01S 15/931: of land vehicles - G06F 16/2379: {Updates performed during online database operations; commit processing} - G06F 16/29: Geographical information databases - G08G 1/09626: {where the origin of the information is within the own vehicle, e.g. a local storage device, digital map} - G08G 1/096716: {where the received information does not generate an automatic action on the vehicle control} - G08G 1/096758: {where no selection takes place on the transmitted or the received information} - G08G 1/096775: {where the origin of the information is a central station} - G08G 1/096791: {where the origin of the information is another vehicle} - H04L 67/12: specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks - H04W 4/029: Location-based management or tracking services - H04W 4/38: for collecting sensor information - H04W 4/90: Services for handling of emergency or hazardous situations, e.g. earthquake and tsunami warning systems [ETWS] - B60Q 9/008: {for anti-collision purposes} - B60W 2050/0031: {Mathematical model of the vehicle} - B60W 2300/14: Tractor-trailers, i.e. combinations of a towing vehicle and one or more towed vehicles, e.g. caravans; Road trains - B60W 2552/45: Pedestrian sidewalk - B60W 2556/40: High definition maps - B60Y 2200/147: Trailers, e.g. full trailers or caravans - 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 - G01S: RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - H04L: TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION (arrangements common to telegraphic and telephonic communication H04M) - H04W: WIRELESS COMMUNICATION NETWORKS (broadcast communication H04H; communication systems using wireless links for non-selective communication, e.g. wireless extensions H04M1/72) - B60Q: ARRANGEMENT OF SIGNALLING OR LIGHTING DEVICES, THE MOUNTING OR SUPPORTING THEREOF OR CIRCUITS THEREFOR, FOR VEHICLES IN GENERAL - B60Y: INDEXING SCHEME RELATING TO ASPECTS CROSS-CUTTING VEHICLE TECHNOLOGY ## Abstract A feature avoidance system for a vehicle including at least one ultrasonic sensor disposed on a vehicle and communicatively coupled to a vehicle controller. A dynamic vehicle model is stored in the controller. The dynamic vehicle model is a computer model of current and expected dynamic vehicle component positioning. An analysis module configured cause at least one of the controller and a remote processing system to identify a feature at least partially via data from the at least one ultrasonic sensor, compare a predicted feature position and an estimated vehicle component position, and generate an output in response to the predicted feature position and the estimated vehicle component position intersecting. ## Claims ### Claim 1 A feature avoidance system for a vehicle comprising: at least one ultrasonic sensor disposed on a vehicle and communicatively coupled to a vehicle controller; a wheel position sensor configured to detect or determine a position of a wheel, wherein the position of the wheel is provided on a trailer articulatable relative to a tractor; a dynamic vehicle model stored in said controller, the dynamic vehicle model being a computer model of current and expected dynamic vehicle component positioning including the position of the wheel, wherein the dynamic vehicle model is configured to be adjusted based upon the detected or determined position of the wheel; an analysis module configured to cause at least one of the controller and a remote processing system to identify a feature at least partially via data from the at least one ultrasonic sensor, wherein the feature is identified from the ultrasonic sensor data using a simultaneous localization and mapping (SLAM) modeling technique to model the environment, compare a predicted feature position and an estimated position of the wheel along a predicted wheel placement path, and generate an output in response to the estimated position of the wheel of the predicted wheel placement path intersecting with the predicted feature position. ### Claim 2 (depends on 1) The feature avoidance system of claim 1, wherein the feature is identified without assistance of image data. ### Claim 3 (depends on 1) The feature avoidance system of claim 1, wherein the feature is identified exclusively using sensor data from the at least one ultrasonic sensor. ### Claim 4 (depends on 1) The feature avoidance system of claim 1, wherein the feature is identified using a combination of ultrasonic sensor data and at least one of map data and GPS data. ### Claim 5 (depends on 1) The feature avoidance system of claim 1, wherein the response includes an operator alert. ### Claim 6 (depends on 1) The feature avoidance system of claim 1, wherein the response includes an activation of a driver assistance system. ### Claim 7 (depends on 1) The feature avoidance system of claim 1, wherein the dynamic vehicle model is a robot operating systems (ROS) control model incorporating a steering angle of the vehicle, an Ackerman profile of the vehicle, and vehicle movement data. ### Claim 8 (depends on 1) The feature avoidance system of claim 1, wherein the analysis module is further configured to apply the position of the identified feature to one of a map data and a GPS data thereby generating updated map data and to store the updated map data and GPS data in a database. ### Claim 9 (depends on 8) The feature avoidance system of claim 8, wherein the database is remotely accessible by at least a second vehicle. ### Claim 10 (depends on 1) The feature avoidance system of claim 1, wherein the feature is at least one curb. ### Claim 11 (depends on 1) The feature avoidance system of claim 1, wherein the analysis module is configured to cause the controller to perform each of identifying the feature at least partially via data from the at least one ultrasonic sensor, comparing the predicted feature position and the estimated position of the wheel, and generating the output in response to the predicted feature position and the estimated position of the wheel intersecting. ### Claim 12 A method for detecting and avoiding feature collisions in a commercial vehicle comprising: detecting or determining a position of a wheel with a wheel position sensor; adjusting a dynamic vehicle model based upon the detected or determined position of the wheel; generating a three-dimensional map of an environment based on sensor measurements from at least one ultrasonic sensor; locating the position of a wheel within the three-dimensional map; identifying at least one feature within the three-dimensional map distinct from the position of the wheel; comparing a predicted position of the at least one feature and an estimated position of the wheel at a future time; and generating an output in response to the predicted feature position and the estimated position of the wheel intersecting. ### Claim 13 (depends on 12) The method of claim 12, wherein the three-dimensional map is generated using a using a simultaneous localization and mapping (SLAM) system. ### Claim 14 (depends on 12) The method of claim 12, wherein the at least one feature is a curb. ### Claim 15 (depends on 12) The method of claim 12, wherein the position of the wheel is provided on a trailer articulatable relative to a tractor. ### Claim 16 (depends on 15) The method of claim 15, wherein the wheel includes a tire. ### Claim 17 (depends on 12) The method of claim 12, wherein the at least one feature within the three-dimensional map distinct from the position of the wheel is identified using a combination of the sensor measurements from the at least one ultrasonic sensor and at least one of map data and GPS data. ### Claim 18 (depends on 12) The method of claim 12, further comprising applying a position of the at least one feature within the three-dimensional map distinct from the position of the wheel to one of map data and GPS data and storing the updated one of map data and GPS data in a database. ### Claim 19 (depends on 18) The method of claim 18, wherein the database is remotely accessible via at least one other commercial vehicle.