# US 12,459,486 B2 · Methods and systems for reducing vehicle delay based on movement prediction > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 12,459,486 B2 - Document ID: US12459486B2 - Status: Granted - Kind: B2 - Application number: 18/661,265 - Filed: 2024-05-10 - Published: 2025-02-20 - Granted: 2025-11-04 - Earliest claimed: 2023-08-17 - Assignees: TORC Robotics, Inc. - Applicants: Torc Robotics, Inc. - Inventors: Rikki Valverde; Lorenzo Tarsitano - Web page: https://patentgrep.com/patent/US12459486B2 ## CPC - B60W 10/024: {including control of torque converters} - B60W 30/18154: {Approaching an intersection} - B60W 50/0097: {Predicting future conditions} - B60W 60/00274: {considering possible movement changes} - B60W 2050/0088: {Adaptive recalibration} - B60W 2420/403: Image sensing, e.g. optical camera - B60W 2510/0275: Clutch torque - B60W 2554/20: Static objects - B60W 2554/4045: Intention, e.g. lane change or imminent movement - B60W 2555/60: Traffic rules, e.g. speed limits or right of way - B60W 2556/10: Historical data - 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 ## Abstract A method may include monitoring, by a processor associated with an autonomous vehicle, a status of a traffic light. The method may include monitoring, by the processor, a movement status of at least one vehicle within a same lane as the autonomous vehicle, the at least one vehicle having a stationary position in relation to the traffic light. The method may include executing, by the processor, a computer model to predict a change of movement status for the at least one vehicle in accordance with the status of the traffic light. The method may include in response to the computer model predicting a change of movement status for the at least one vehicle from the stationary position to a moving status, instructing, by the processor, the autonomous vehicle to increase a torque value of the autonomous vehicle at a predetermined time before the change of the movement status. ## Claims ### Claim 1 A system for reducing autonomous vehicle delay, the system comprising: a sensor configured to detect a movement status of at least one vehicle; and a computing device comprising a processor and a non-transitory computer readable storage in communication with the sensor, the processor configured to: receive, from the sensor, sensor data representing the movement status of the at least one vehicle; execute an artificial intelligence module to process the sensor data to predict a change of movement status for the at least one vehicle based on the movement status of the at least one vehicle; and initiate an autonomous vehicle movement corresponding to the change of movement status for the at least one vehicle. ### Claim 2 (depends on 1) The system of claim 1, wherein the sensor is further configured to detect a status of a traffic light, and wherein the processor is further configured to receive sensor data representing the status of the traffic light. ### Claim 3 (depends on 1) The system of claim 1, wherein the processor is further configured to process location data and historical data to predict the change of movement status. ### Claim 4 (depends on 1) The system of claim 1, wherein the autonomous vehicle movement is engaging a powertrain of the autonomous vehicle. ### Claim 5 (depends on 1) The system of claim 1, wherein the artificial intelligence module comprises at least one of: a logistic regression, a decision tree, a neural network, a linear model, or a Bayesian model. ### Claim 6 (depends on 5) The system of claim 5, wherein the artificial intelligence module is trained on a data set of factors collected across a plurality of prior trials. ### Claim 7 (depends on 6) The system of claim 6, wherein the data set from the plurality of prior trials comprises at least one of: a status of a traffic light, a vehicle movement history, a speed limit, a direction of the at least one vehicle, objects in front of the at least one vehicle, a predicted lane change or turn for the at least one vehicle, or a braking status of the at least one vehicle. ### Claim 8 An autonomous vehicle comprising: a powertrain comprising a transmission and a brake; a sensor disposed on the autonomous vehicle configured to detect a movement status of at least one vehicle; and a computing device comprising a processor and a non-transitory computer readable storage in communication with the sensor, the processor configured to: receive, from the sensor, sensor data representing the movement status of the at least one vehicle; execute an artificial intelligence module to predict a change of the movement status for the at least one vehicle based on the sensor data; and engage the transmission of the powertrain and disengage the brake of the powertrain to initiate an autonomous vehicle movement corresponding to the change of movement status for the at least one vehicle. ### Claim 9 (depends on 8) The autonomous vehicle of claim 8, wherein the sensor is further configured to detect a status of a traffic light, and wherein the processor is further configured to receive sensor data representing the status of the traffic light. ### Claim 10 (depends on 8) The autonomous vehicle of claim 8, wherein the processor is further configured to process location data and historical data to predict the change of movement status. ### Claim 11 (depends on 8) The autonomous vehicle of claim 8, wherein the artificial intelligence module comprises at least one of: a logistic regression, a decision tree, a neural network, a linear model, or a Bayesian model. ### Claim 12 (depends on 8) The autonomous vehicle of claim 8, wherein the artificial intelligence module is trained on a data set of factors collected across a plurality of prior trials. ### Claim 13 (depends on 12) The autonomous vehicle of claim 12, wherein the processor is further configured to detect a change in brake lights of the at least one vehicle from the sensor data to detect the change in movement status of the at least one vehicle. ### Claim 14 (depends on 8) The autonomous vehicle of claim 8, further comprising increasing a torque value at a predetermined time before the initiation of the movement of the autonomous vehicle. ### Claim 15 A computer-implemented method for reducing autonomous vehicle delay, the method comprising: receiving, from a sensor, sensor data representing a status of at least one vehicle; executing an artificial intelligence module to predict a change of movement status for the at least one vehicle based on the sensor data; and initiating an autonomous vehicle movement corresponding to the change of movement status for the at least one vehicle. ### Claim 16 (depends on 15) The method of claim 15, further comprising receiving sensor data representing a status of a traffic light and processing the sensor data to predict the change of movement status for the at least one vehicle. ### Claim 17 (depends on 15) The method of claim 15, further comprising processing location data and historical data to predict the change of movement status. ### Claim 18 (depends on 15) The method of claim 15, wherein the initiated movement is engaging a powertrain of the autonomous vehicle. ### Claim 19 (depends on 15) The method of claim 15, wherein the artificial intelligence module comprises at least one of: a logistic regression, a decision tree, a neural network, a linear model, or a Bayesian model. ### Claim 20 (depends on 19) The method of claim 19, wherein the artificial intelligence module is configured to predict a plurality of predetermined attributes of the at least one vehicle relative to the autonomous vehicle.