IP Library Granted Patent US 12,371,027
Granted Patent B2
US 12,371,027 · App. 16/947,867 · Granted Jul 29, 2025

Vehicular driving assist system with traffic jam probability determination

Inventors: Jigneshkumar Natvarlal Vasoya (Gujarat, IN); Kirti Hiranand Balani (Maharashtra, IN); Vishalkumar Madhusudan Mehta (Gujarat, IN); Pushpendra Kushwaha (Uttar pradesh, IN)
Assignee: Magna Electronics Inc.
B60W40/04G06N7/00G08G1/0133B60W2420/403B60W2420/408B60W2552/05B60W2552/10B60W2554/406B60W2554/408
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Quick Facts
Patent No.
US 12,371,027
App. No.
16/947,867
Granted
Jul 29, 2025
Kind
B2
Abstract

A vehicular driving assist system includes at least one sensor disposed at a vehicle and having a field of sensing exterior of the vehicle. An ECU includes circuitry and associated software, with the circuitry including a data processor for processing sensor data captured by the sensor to detect presence of objects in the field of sensing of the sensor. The ECU, responsive to processing by the data processor at the ECU of sensor data captured by the sensor, determines traffic attributes for a plurality of traffic lanes of a road the vehicle is travelling along. The ECU, responsive to determining the traffic attributes determines a predicted traffic value based on the traffic attributes and an output from a trained prediction model. The ECU, responsive to determining the predicted value, determines a traffic jam probability for at least one traffic lane based on the predicted value and the respective traffic attributes.

Claims (55)

1. A vehicular driving assist system, the vehicular driving assist system comprising:

at least one sensor disposed at a vehicle equipped with the vehicular driving assist system, the at least one sensor having a field of sensing exterior and at least forward of the equipped vehicle, the at least one sensor capturing sensor data;

an electronic control unit (ECU) comprising electronic circuitry and associated software;

wherein the electronic circuitry of the ECU comprises a data processor for processing sensor data captured by the at least one sensor to detect presence of objects in the field of sensing of the at least one sensor;

wherein the ECU, responsive to processing by the data processor at the ECU of sensor data captured by the at least one sensor, determines traffic attributes for each traffic lane of a plurality of traffic lanes forward of the equipped vehicle on a road along which the equipped vehicle is travelling;

wherein the ECU, responsive to determining the traffic attributes, determines a predicted traffic value based on (i) the traffic attributes and (ii) a model output from a trained traffic prediction model;

wherein the ECU, responsive to determining the predicted traffic value, determines a traffic jam probability for each traffic lane of the road ahead of the equipped vehicle based on the predicted traffic value and the respective traffic attributes;

wherein the ECU determines a traffic lane of the plurality of traffic lanes with the lowest traffic jam probability; and

wherein the ECU generates an output based on the determination of the traffic lane with the lowest determined traffic jam probability, and wherein the output comprises one selected from the group consisting of (i) a notification to a driver of the vehicle of the traffic lane with the lowest determined traffic jam probability and (ii) a command to maneuver the vehicle into the traffic lane with the lowest determined traffic jam probability.

2. The vehicular driving assist system of claim 1 , wherein the trained traffic prediction model comprises a trained linear regression prediction model.

3. The vehicular driving assist system of claim 1 , wherein the traffic attributes comprise at least one selected from the group consisting of (i) traffic density, (ii) traffic flow rate, (iii) traffic collective velocity and (iv) traffic normalized longitudinal distance.

4. The vehicular driving assist system of claim 1 , wherein the trained traffic prediction model is trained on annotated data, and wherein the annotated data is categorized into traffic scenarios.

5. The vehicular driving assist system of claim 4 , wherein the traffic scenarios comprise at least two selected from the group consisting of (i) no traffic, (ii) slow moving traffic, (iii) stop and go traffic and (iv) stopped traffic.

6. The vehicular driving assist system of claim 4 , wherein the annotated data comprises subjective observations from at least one traffic observer.

7. The vehicular driving assist system of claim 1 , wherein the ECU performs data transformation on the model output from the trained traffic prediction model, and wherein the data transformation comprises a multi-variable quadratic linear equation.

8. The vehicular driving assist system of claim 7 , wherein the multi-variable quadratic linear equation comprises a three variable quadratic linear equation.

9. The vehicular driving assist system of claim 1 , wherein the trained traffic prediction model is trained with weight least square fitting using an orthogonal-triangular decomposition algorithm.

10. The vehicular driving assist system of claim 1 , wherein the ECU, responsive to determining the traffic jam probability for each traffic lane ahead of the equipped vehicle, determines an overall traffic jam probability for the road ahead of the equipped vehicle.

11. The vehicular driving assist system of claim 10 , wherein the ECU determines the overall traffic jam probability from an average traffic jam probability of each traffic lane of the road.

12. The vehicular driving assist system of claim 1 , wherein the ECU determines the traffic jam probability for each traffic lane based at least in part on (i) a vehicle-to-vehicle communication from another vehicle forward of the equipped vehicle or (ii) a vehicle-to-infrastructure communication from infrastructure forward of the equipped vehicle.

13. The vehicular driving assist system of claim 1 , wherein the output comprises the command to maneuver the equipped vehicle into the traffic lane with the lowest determined traffic jam probability.

14. The vehicular driving assist system of claim 1 , wherein the at least one sensor comprises at least one forward viewing camera.

15. The vehicular driving assist system of claim 1 , wherein the at least one sensor comprises at least one forward sensing radar sensor.

16. The vehicular driving assist system of claim 1 , wherein the at least one sensor comprises at least one forward sensing lidar sensor.

17. The vehicular driving assist system of claim 1 , wherein the ECU determines the traffic jam probability for each traffic lane based on the predicted traffic value, the respective traffic attributes, and a traffic normalized longitudinal distance.

18. A vehicular driving assist system, the vehicular driving assist system comprising:

at least one sensor disposed at a vehicle equipped with the vehicular driving assist system, wherein the at least one sensor comprises at least one camera, and wherein the at least one sensor has a field of sensing exterior and at least forward of the equipped vehicle, the at least one sensor capturing sensor data;

an electronic control unit (ECU) comprising electronic circuitry and associated software;

wherein the electronic circuitry of the ECU comprises a data processor for processing sensor data captured by the at least one sensor to detect presence of objects in the field of sensing of the at least one sensor;

wherein the ECU, responsive to processing by the data processor at the ECU of sensor data captured by the at least one sensor, determines traffic attributes for each traffic lane of a plurality of traffic lanes forward of the equipped vehicle on a road along which the equipped vehicle is travelling;

wherein the traffic attributes comprise at least two selected from the group consisting of (i) traffic density, (ii) traffic flow rate, (iii) traffic collective velocity and (iv) traffic normalized longitudinal distance;

wherein the ECU, responsive to determining the traffic attributes, determines a predicted traffic value based on (i) the traffic attributes and (ii) a model output from a trained traffic prediction model;

wherein the ECU, responsive to determining the predicted traffic value, determines a traffic jam probability for each traffic lane of the road ahead of the equipped vehicle based on the predicted traffic value and the respective traffic attributes;

wherein the ECU determines a traffic lane of the plurality of traffic lanes with the lowest traffic jam probability; and

wherein the ECU generates an output based on the determination of the traffic lane with the lowest determined traffic jam probability, and wherein the output comprises one selected from the group consisting of (i) a notification to a driver of the vehicle of the traffic lane with the lowest determined traffic jam probability and (ii) a command to maneuver the vehicle into the traffic lane with the lowest determined traffic jam probability.

19. The vehicular driving assist system of claim 18 , wherein the at least one sensor further comprises at least one radar sensor.

20. The vehicular driving assist system of claim 18 , wherein the ECU, responsive to determining the traffic jam probability for each traffic lane ahead of the equipped vehicle, determines an overall traffic jam probability for the road ahead of the equipped vehicle.

21. The vehicular driving assist system of claim 18 , wherein the ECU determines the traffic jam probability for each traffic lane based at least in part on (i) a vehicle-to-vehicle communication from another vehicle forward of the equipped vehicle or (ii) a vehicle-to-infrastructure communication from infrastructure forward of the equipped vehicle.

22. The vehicular driving assist system of claim 18 , wherein the output comprises the command to maneuver the equipped vehicle into the traffic lane with the lowest determined traffic jam probability.

23. A vehicular driving assist system, the vehicular driving assist system comprising:

at least one sensor disposed at a vehicle equipped with the vehicular driving assist system, wherein the at least one sensor comprises at least one selected from the group consisting of (i) at least one lidar sensor and (ii) at least one radar sensor, and wherein the at least one sensor has a field of sensing exterior and at least forward of the equipped vehicle, the at least one sensor capturing sensor data;

an electronic control unit (ECU) comprising electronic circuitry and associated software;

wherein the electronic circuitry of the ECU comprises a data processor for processing sensor data captured by the at least one sensor to detect presence of objects in the field of sensing of the at least one sensor;

wherein the ECU, responsive to processing by the data processor at the ECU of sensor data captured by the at least one sensor, determines traffic attributes for each traffic lane of a plurality of traffic lanes forward of the equipped vehicle on a road along which the equipped vehicle is travelling;

wherein the traffic attributes comprise at least two selected from the group consisting of (i) traffic density, (ii) traffic flow rate, (iii) traffic collective velocity and (iv) traffic normalized longitudinal distance;

wherein the ECU, responsive to determining the traffic attributes, determines a predicted traffic value based on (i) the traffic attributes and (ii) a model output from a trained traffic prediction model;

wherein the ECU, responsive to determining the predicted traffic value, determines a traffic jam probability for each traffic lane of the road ahead of the equipped vehicle based on the predicted traffic value and the respective traffic attributes;

wherein the ECU determines a traffic lane of the plurality of traffic lanes with the lowest traffic jam probability; and

wherein the ECU generates an output based on the determination of the traffic lane with the lowest determined traffic jam probability, and wherein the output comprises one selected from the group consisting of (i) a notification to a driver of the vehicle of the traffic lane with the lowest determined traffic jam probability and (ii) a command to maneuver the vehicle into the traffic lane with the lowest determined traffic jam probability.

24. The vehicular driving assist system of claim 23 , wherein the at least one sensor comprises the at least one radar sensor.

25. The vehicular driving assist system of claim 23 , wherein the at least one sensor comprises the at least one lidar sensor.

26. The vehicular driving assist system of claim 23 , wherein the at least one sensor further comprises at least one camera.

27. The vehicular driving assist system of claim 23 , wherein the ECU, responsive to determining the traffic jam probability for each traffic lane ahead of the equipped vehicle, determines an overall traffic jam probability for the road ahead of the equipped vehicle.

28. The vehicular driving assist system of claim 23 , wherein the ECU determines the traffic jam probability for each traffic lane based at least in part on (i) a vehicle-to-vehicle communication from another vehicle forward of the equipped vehicle or (ii) a vehicle-to-infrastructure communication from infrastructure forward of the equipped vehicle.

29. The vehicular driving assist system of claim 23 , wherein the output comprises the command to maneuver the equipped vehicle into the traffic lane with the lowest determined traffic jam probability.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 21, 2020
From: VASOYA, JIGNESHKUMAR NATVARLAL; BALANI, KIRTI HIRANAND; MEHTA, VISHALKUMAR MADHUSUDAN; KUSHWAHA, PUSHPENDRA
To: MAGNA ELECTRONICS INC.
Reel/Frame 053558/0746 →
Continuity (2)
Provisional Application 62890708 · Aug 23, 2019
Related Publication 20210053572A1 · Feb 25, 2021
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