IP Library Granted Patent US 12,145,627
Granted Patent B2
US 12,145,627 · App. 17/784,531 · Granted Nov 19, 2024

System and method for predicting the trajectory of a vehicle

Inventors: David Gonzalez Bautista (Saint Cyr l'ecole, FR); Vicente Milanes (Boulogne-Billancourt, FR); Francisco Martin Navas Matos (Paris, FR)
Assignee: AMPERE S.A.S.
B60W60/0027B60W30/18163B60W40/105B60W2554/4041B60W2554/4046
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Quick Facts
Patent No.
US 12,145,627
App. No.
17/784,531
Granted
Nov 19, 2024
Kind
B2
Abstract

A method predicts the trajectory of an ego vehicle travelling in a main lane. A lane change by the ego vehicle from the main lane to an adjacent lane is determined according to an estimate of the dynamic behavior of a group of vehicles travelling in the adjacent lane. The group of vehicles includes at least one main vehicle which is located near the ego vehicle and a secondary vehicle which is located behind the ego vehicle.

Claims (20)

1. A method for predicting a trajectory of an ego vehicle travelling in a main lane, the method comprising:

determining a lane change by the ego vehicle from the main lane to an adjacent lane according to an estimate of the dynamic behavior of a group of vehicles travelling in the adjacent lane, said group of vehicles comprising at least one main vehicle located near the ego vehicle and a secondary vehicle located behind said ego vehicle;

gathering position, orientation, and speed information of the ego vehicle and of the vehicles of the group of vehicles; and

establishing a dynamic model per pair of consecutive vehicles travelling in the adjacent lane according to the gathered information,

wherein the dynamic model per pair of consecutive vehicles is acquired by determining a second-order transfer function corresponding to the behavior of the ego vehicle relative to each pair of considered consecutive vehicles using an autoregressive exogenous computation model, with the behavior of the ego vehicle depending on its longitudinal model and on its longitudinal controller.

2. The method as claimed in claim 1 , wherein the established dynamic models are confirmed by comparing an error of the autoregressive exogenous computation model with a threshold value dependent on the actual speed of each vehicle at an instant and on the speed of said vehicle at a previous instant.

3. The method as claimed in claim 2 , wherein the movement of the adjacent vehicles is predicted according to the confirmed dynamic model and the initial position of said vehicles, the movement of the ego vehicle is predicted according to the prediction of the movement of the adjacent vehicles and information originating from proprioceptive sensors of the ego vehicle and the lane change by the ego vehicle is determined according to said predictions of the movement of the ego vehicle and of the adjacent vehicles and an overall trajectory of the ego vehicle.

4. The method as claimed in claim 1 , further comprising:

repeating the determining until a lane change possibility is found.

5. A system that predicts a trajectory of an ego vehicle travelling in a main lane, the system being configured to determine a lane change by the ego vehicle from the main lane to an adjacent lane according to an estimate of the dynamic behavior of a group of vehicles travelling in the adjacent lane, said group of vehicles comprising at least one main vehicle located near the ego vehicle and a secondary vehicle located behind said ego vehicle,

wherein the system comprises:

a module for gathering position, orientation, and speed information of the ego vehicle and of the vehicles of the group of vehicles; and

a module for estimating a dynamic model per pair of consecutive vehicles travelling in the adjacent lane according to the gathered information, the dynamic model per pair of consecutive vehicles being acquired by determining a second-order transfer function corresponding to the behavior of the ego vehicle relative to each pair of considered consecutive vehicles using an autoregressive exogenous computation model, with the behavior of the ego vehicle depending on its longitudinal model and on its longitudinal controller.

6. The system as claimed in claim 5 , comprising:

a module for confirming the established dynamic models by comparing an error of the autoregressive exogenous computation model with a threshold value dependent on the actual speed of each vehicle at an instant and on the previous speed at a previous instant;

a module for predicting the movement of the adjacent vehicles according to the confirmed dynamic model and the initial position of said vehicles;

a module for predicting the movement of the ego vehicle according to the prediction of the movement of the adjacent vehicles and information originating from proprioceptive sensors of the ego vehicle; and

a module for determining the lane change by the ego vehicle according to said predictions of the movement of the ego vehicle and of the adjacent vehicles and an overall trajectory of the ego vehicle.

7. An ego motor vehicle, comprising:

the system as claimed in claim 5 .

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 23, 2024
From: RENAULT S.A.S.
To: AMPERE S.A.S.
Reel/Frame 067526/0311 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 25, 2022
From: GONZALEZ BAUTISTA, DAVID; MILANES, VICENTE
To: RENAULT S.A.S.
Reel/Frame 061876/0521 →
Priority Claims (1)
FR 1914342 · Dec 13, 2019 · national
Continuity (1)
Related Publication 20230015485A1 · Jan 19, 2023