Sliding mode trajectory voting strategy module and driving control system and method thereof

• US 9,321,458 B2
• Filed: 12/17/2013
• Issued: 04/26/2016
• Est. Priority Date: 12/17/2013
• Status: Active Grant

• Current Assignee: Automotive Research & Testing Center
• Original Assignee: Automotive Research & Testing Center
• Inventors: Wang, Tong-Wen, Hsu, Wei-Feng, Tseng, Po-Kai
• Primary Examiner(s): Black, Thomas G
• Assistant Examiner(s): Lewandroski, Sara
• Application Number:
  US14/108,355
• Publication Number:
  US 20150166061A1
• Time in Patent Office: 861 Days
• Field of Search: 701/23, 701/25, 701/26, 701/27, 701/410, 701/411, 701/416, 701/423, 701/533, 701/519, 701/301, 701/41, 701/44, 701/117
• US Class Current: 1/1
• CPC Class Codes: B60W 2540/30 Driving style
• CPC Class Codes: B60W 2552/00 Input parameters relating to infrastructure
• CPC Class Codes: B60W 2552/30 Road curve radius
• CPC Class Codes: B60W 30/02 Control of vehicle driving stability

Abstract

The present invention provided a sliding mode trajectory voting strategy module. The sliding mode trajectory voting strategy module integrates a reaction time and a relative distance into an obstacle feature sliding surface by utilize sliding mode control theory, and calculates the obstacle feature sliding surface and a road curvature value in combination with fuzzy theory to obtain an orientation angle of a safety path.

Claims

1. A sliding mode trajectory voting strategy module comprising:

a fuzzification interface inputting a road curvature information and a road risk assessment information and performing a fuzzy analysis based on a plurality of predetermined membership functions;

a fuzzy inference interface integrating the road curvature information and the road risk assessment information based on a sliding mode control theory and performing a simulation on the road curvature information and the road risk assessment information to obtain a route voting result; and

a defuzzification interface defuzzifing the route voting result according to a fuzzy logic rule table to obtain an orientation angle of a safe path;

wherein the sliding mode control theory is utilized to integrate a reaction time and a relative distance in the road curvature information and the road risk assessment information into an obstacle feature sliding surface, the obstacle feature sliding surface S_t=sign(Y_t)(τ

_t+λ

d_t), wherein τ

represents the reaction time, λ

represents an obstacle feature constant, d represents the relative distance, Y represents a horizontal coordinate of a target obstacle, and the subscript i represents the target obstacle.

2. The sliding mode trajectory voting strategy module of claim 1, wherein each of the predetermined membership functions is a triangle equation.

3. The sliding mode trajectory voting strategy module of claim 1, wherein the fuzzy inference interface uses a road curvature value and the obstacle feature sliding surface as antecedents of a fuzzy rule, and uses the orientation angle of the safe path as a consequent of the fuzzy rule, the road curvature value K=1/r, wherein r is a curvature radius of a road.

4. The sliding mode trajectory voting strategy module of claim 3, wherein the road curvature information comprises lateral motion and longitudinal motion of the target vehicle, and the road risk assessment information comprises an obstacle feature, a road feature, and a human-vehicle interaction feature.