US 2026/0200476 A1 · Exhaustive Driving Analytical Systems and Modelers

Abstract

Systems and methods for predicting vehicle events before they occur using navigation and sensor data are provided. The system receives navigation data associated with a planned route and sensor data from vehicle sensors including camera, position, and motion data. Based on this information, the system predicts a future vehicle event before the event occurs. The system determines a time-to-impact for the predicted event and calculates an expected reaction time using a driving error model. By comparing the time-to-impact to the expected reaction time, the system determines a threshold time for intervention. The system generates a vehicle instruction based on the threshold, which may include autonomous driving instructions, driver alerts, or instructions to transition to autonomous control. The system may utilize machine learning algorithms trained to recognize event signatures and patterns, enabling prediction of events such as highway exits, lane changes, and turns at intersections before they begin.

Claims20

Dependent claims

A method comprising:

receiving, by a computing device, navigation data associated with a planned route of a vehicle;
receiving, from one or more sensors associated with the vehicle, sensor data comprising at least one of camera data, position data, or motion data;
predicting, based on the navigation data and the sensor data, a future vehicle event before the future vehicle event actually occurs;
determining, based on the predicted future vehicle event, a time to impact for the future vehicle event;
determining, based on a driving error model, an expected reaction time to determine a threshold amount of time for intervention;
and
generating, based on the threshold time for intervention, a vehicle instruction for the future vehicle event.

4 more elements

A safety analytic processing platform comprising:

at least one processor;
a communication interface communicatively coupled to the at least one processor;
and
memory storing computer-readable instructions that, when executed by the at least one processor, cause the computing platform to:
receive, by a computing device, navigation data associated with a planned route of a vehicle;
receive, from one or more sensors associated with the vehicle, sensor data comprising at least one of camera data, position data, or motion data;
predict, based on the navigation data and the sensor data, a future vehicle event before the future vehicle event actually occurs;
determine, based on the predicted future vehicle event, a time to impact for the future vehicle event;
determine, based on a driving error model, an expected reaction time to determine a threshold time for intervention;
and
generate, based on the threshold time for intervention, a vehicle instruction for the future vehicle event.

8 more elements

One or more non-transitory computer-readable media storing instructions that, when executed by a computing platform comprising at least one processor, a communication interface, and memory, cause the computing platform to:

receive, by a computing device, navigation data associated with a planned route of a vehicle;
receive, from one or more sensors associated with the vehicle, sensor data comprising at least one of camera data, position data, or motion data;
predict, based on the navigation data and the sensor data, a future vehicle event before the future vehicle event actually occurs;
determine, based on the predicted future vehicle event, a time-to-impact for the future vehicle event;
determine, based on a driving error model, an expected reaction time to determine a threshold time for intervention;
and
generate, based on the threshold time for intervention, a vehicle instruction for the future vehicle event.

4 more elements

Dependencies are inferred from the claim text.

Exhaustive Driving Analytical Systems and Modelers

Life of this patent

Exhaustive Driving Analytical Systems and Modelers

Life of this patent

Abstract

Claims20