Granted Patent B2

US 12,480,861 · App. 18/113,343 · Granted Nov 25, 2025

Inventors: Yuelei Gao (Beijing, CN); Yun Zhao (Beijing, CN); Zhihua Yu (Beijing, CN); Yanfu Zhang (Beijing, CN); Zhenmin Zhu (Beijing, CN)

Assignee: Apollo Intelligent Driving Technology (Beijing) Co., Ltd.

G01N19/02

Abstract

Claims (82)

1 . A method for determining a road surface adhesion coefficient, comprising:

determining, based on M state parameters of a vehicle on a target road section, M road surface adhesion coefficient estimation results respectively corresponding to the M state parameters, M being an integer greater than 1;

selecting N road surface adhesion coefficient estimation results from the M road surface adhesion coefficient estimation results according to a traveling work condition of the vehicle on the target road section, N being a positive integer smaller than or equal to M; and

determining the road surface adhesion coefficient of the target road section based on the N road surface adhesion coefficient estimation results;

wherein the M state parameters comprise at least one of: a vehicle state parameter corresponding to a wheel longitudinal force, a vehicle state parameter corresponding to a wheel lateral force, or a vehicle state parameter corresponding to a traction coefficient,

wherein the vehicle state parameter corresponding to the traction coefficient comprises a number of pulses of a driven wheel and a number of pulses of a non-driven wheel,

wherein the determining, based on the M state parameters of the vehicle on the target road section, the M road surface adhesion coefficient estimation results respectively corresponding to the M state parameters comprises:

determining the traction coefficient based on the number of pulses of the driven wheel and the number of pulses of the non-driven wheel; and

determining a road surface adhesion coefficient estimation result corresponding to the traction coefficient based on the traction coefficient and a drive mode of the vehicle;

wherein the vehicle state parameter corresponding to the wheel longitudinal force comprises a vehicle speed, a wheel speed and a wheel acceleration,

wherein the determining, based on the M state parameters of the vehicle on the target road section, the M road surface adhesion coefficient estimation results respectively corresponding to the M state parameters comprises:

determining a slip rate curve based on the vehicle speed and the wheel speed of the vehicle at each time point during traveling on the target road section;

determining a wheel acceleration peak based on the wheel acceleration of the vehicle at the each time point during traveling on the target road section;

determining a slip rate corresponding to the wheel acceleration peak from the slip rate curve; and

determining a road surface adhesion coefficient estimation result corresponding to the wheel longitudinal force based on the slip rate corresponding to the wheel acceleration peak,

wherein the vehicle state parameter corresponding to the wheel lateral force comprises a wheel sideslip angle and the wheel lateral force, and

wherein the determining, based on the M state parameters of the vehicle on the target road section, the M road surface adhesion coefficient estimation results respectively corresponding to the M state parameters comprises:

determining, in a situation where the traveling work condition of the vehicle is in a linear region, a road surface adhesion coefficient estimation result corresponding to the wheel lateral force based on the wheel sideslip angle and the wheel lateral force of the vehicle on the target road section and a least squares method.

2 . The method according to claim 1 , wherein the determining, based on the M state parameters of the vehicle on the target road section, the M road surface adhesion coefficient estimation results respectively corresponding to the M state parameters further comprises:

determining, in a situation where the traveling work condition of the vehicle is in a non-linear region, a road surface adhesion coefficient estimation result corresponding to the wheel lateral force based on the wheel sideslip angle and the wheel lateral force of the vehicle on the target road section and a lateral tire kinetic model.

3 . The method according to claim 1 , further comprising:

determining a safety margin of the vehicle based on the road surface adhesion coefficient of the target road section and an adhesion coefficient used by the vehicle.

4 . The method according to claim 3 , further comprising:

controlling the vehicle to travel based on the safety margin.

5 . An apparatus for determining a road surface adhesion coefficient, comprising:

at least one processor; and

a storage device,

wherein the storage device stores instructions executable by the at least one processor, and the instructions, when executed by the at least one processor, cause the at least one processor to perform operations comprising:

determining, based on M state parameters of a vehicle on a target road section, M road surface adhesion coefficient estimation results respectively corresponding to the M state parameters, M being an integer greater than 1;

selecting N road surface adhesion coefficient estimation results from the M road surface adhesion coefficient estimation results according to a traveling work condition of the vehicle on the target road section, N being a positive integer smaller than or equal to M; and

determining the road surface adhesion coefficient of the target road section based on the N road surface adhesion coefficient estimation results,

wherein the M state parameters comprise at least one of: a vehicle state parameter corresponding to a wheel longitudinal force, a vehicle state parameter corresponding to a wheel lateral force, or a vehicle state parameter corresponding to a traction coefficient,

wherein the vehicle state parameter corresponding to the traction coefficient comprises a number of pulses of a driven wheel and a number of pulses of a non-driven wheel,

wherein the determining, based on the M state parameters of the vehicle on the target road section, the M road surface adhesion coefficient estimation results respectively corresponding to the M state parameters comprises:

determining the traction coefficient based on the number of pulses of the driven wheel and the number of pulses of the non-driven wheel; and

determining a road surface adhesion coefficient estimation result corresponding to the traction coefficient based on the traction coefficient and a drive mode of the vehicle,

wherein the vehicle state parameter corresponding to the wheel longitudinal force comprises a vehicle speed, a wheel speed and a wheel acceleration,

wherein the determining, based on the M state parameters of the vehicle on the target road section, the M road surface adhesion coefficient estimation results respectively corresponding to the M state parameters comprises:

determining a slip rate curve based on the vehicle speed and the wheel speed of the vehicle at each time point during traveling on the target road section;

determining a wheel acceleration peak based on the wheel acceleration of the vehicle at the each time point during traveling on the target road section;

determining a slip rate corresponding to the wheel acceleration peak from the slip rate curve; and

determining a road surface adhesion coefficient estimation result corresponding to the wheel longitudinal force based on the slip rate corresponding to the wheel acceleration peak;

wherein the vehicle state parameter corresponding to the wheel lateral force comprises a wheel sideslip angle and the wheel lateral force, and

wherein the determining, based on the M state parameters of the vehicle on the target road section, the M road surface adhesion coefficient estimation results respectively corresponding to the M state parameters comprises:

determining, in a situation where the traveling work condition of the vehicle is in a linear region, a road surface adhesion coefficient estimation result corresponding to the wheel lateral force based on the wheel sideslip angle and the wheel lateral force of the vehicle on the target road section and a least squares method.

6 . The apparatus according to claim 5 , wherein the determining, based on the M state parameters of the vehicle on the target road section, the M road surface adhesion coefficient estimation results respectively corresponding to the M state parameters further comprises:

determining, in a situation where the traveling work condition of the vehicle is in a non-linear region, a road surface adhesion coefficient estimation result corresponding to the wheel lateral force based on the wheel sideslip angle and the wheel lateral force of the vehicle on the target road section and a lateral tire kinetic model.

7 . The apparatus according to claim 5 , wherein the operations comprise:

determining a safety margin of the vehicle based on the road surface adhesion coefficient of the target road section and an adhesion coefficient used by the vehicle.

8 . The apparatus according to claim 7 , wherein the operations further comprise:

controlling the vehicle to travel based on the safety margin.

9 . A non-transitory computer readable storage medium, storing a computer instruction, wherein the computer instruction when executed by a computer causes the computer to perform operations comprising:

determining, based on M state parameters of a vehicle on a target road section, M road surface adhesion coefficient estimation results respectively corresponding to the M state parameters, M being an integer greater than 1;

selecting N road surface adhesion coefficient estimation results from the M road surface adhesion coefficient estimation results according to a traveling work condition of the vehicle on the target road section, N being a positive integer smaller than or equal to M; and

determining a road surface adhesion coefficient of the target road section based on the N road surface adhesion coefficient estimation results,

wherein the M state parameters comprise at least one of: a vehicle state parameter corresponding to a wheel longitudinal force, a vehicle state parameter corresponding to a wheel lateral force, or a vehicle state parameter corresponding to a traction coefficient,

wherein the vehicle state parameter corresponding to the traction coefficient comprises a number of pulses of a driven wheel and a number of pulses of a non-driven wheel,

wherein the determining, based on the M state parameters of the vehicle on the target road section, the M road surface adhesion coefficient estimation results respectively corresponding to the M state parameters comprises:

determining the traction coefficient based on the number of pulses of the driven wheel and the number of pulses of the non-driven wheel; and

determining a road surface adhesion coefficient estimation result corresponding to the traction coefficient based on the traction coefficient and a drive mode of the vehicle;

wherein the vehicle state parameter corresponding to the wheel longitudinal force comprises a vehicle speed, a wheel speed and a wheel acceleration,

wherein the determining, based on the M state parameters of the vehicle on the target road section, the M road surface adhesion coefficient estimation results respectively corresponding to the M state parameters comprises:

determining a slip rate curve based on the vehicle speed and the wheel speed of the vehicle at each time point during traveling on the target road section;

determining a wheel acceleration peak based on the wheel acceleration of the vehicle at the each time point during traveling on the target road section;

determining a slip rate corresponding to the wheel acceleration peak from the slip rate curve; and

determining a road surface adhesion coefficient estimation result corresponding to the wheel longitudinal force based on the slip rate corresponding to the wheel acceleration peak,

wherein the vehicle state parameter corresponding to the wheel lateral force comprises a wheel sideslip angle and the wheel lateral force,

wherein the determining, based on the M state parameters of the vehicle on the target road section, the M road surface adhesion coefficient estimation results respectively corresponding to the M state parameters comprises:

determining, in a situation where the traveling work condition of the vehicle is in a linear region, a road surface adhesion coefficient estimation result corresponding to the wheel lateral force based on the wheel sideslip angle and the wheel lateral force of the vehicle on the target road section and a least squares method.

10 . The apparatus according to claim 5 , further comprising an autonomous driving vehicle.

11 . The method according to claim 1 , wherein the M state parameters comprise two or three of:

the vehicle state parameter corresponding to a wheel longitudinal force;

the vehicle state parameter corresponding to a wheel lateral force; and

a vehicle state parameter corresponding to a traction coefficient.

12 . The apparatus according to claim 5 , wherein the M state parameters comprise two or three of:

the vehicle state parameter corresponding to a wheel longitudinal force;

the vehicle state parameter corresponding to a wheel lateral force; and

a vehicle state parameter corresponding to a traction coefficient.

13 . The non-transitory computer readable storage medium according to claim 9 , wherein the M state parameters comprise two or three of:

the vehicle state parameter corresponding to a wheel longitudinal force;

the vehicle state parameter corresponding to a wheel lateral force; and

a vehicle state parameter corresponding to a traction coefficient.

Assignments (1)

Priority Claims (1)

Continuity (1)

References Cited (14)