01590394

Component

Studying driver awareness of information, particularly risk perception, is vital to understanding driving behavior and improving traffic safety. In the dynamic interaction of a driver-vehicle-environment system, drivers’ risk perception changes dynamically. This study focused on drivers’ risk perception at unsignalized intersections in China and analyzed drivers’ crossing behavior. Based on cognitive psychology theory and an adaptive neuro-fuzzy inference system, quantitative models of drivers’ risk perception were established for the crossing processes between two straight-moving vehicles from the orthogonal direction. The acceptable risk perception levels of drivers were identified using a self-developed data analysis method. Based on game theory, the relationship among the quantitative value of drivers’ risk perception, acceptable risk perception level, and vehicle motion state was analyzed. The models of drivers’ crossing behavior were then established. Finally, the behavior models were validated using data collected from real-world vehicle movements and driver decisions. The results showed that the developed behavior models had both high accuracy and good applicability. This study would provide theoretical and algorithmic references for the microscopic simulation and active safety control system of vehicles.

This paper was sponsored by TRB committee AND30 Standing Committee on Simulation and Measurement of Vehicle and Operator Performance.

01584066

16-3831

English

16p

2016

Transportation Research Board 95th Annual Meeting

Web

Figures; Photos; References (26) ; Tables

Behavior; Drivers; Game theory; Highway safety; Risk assessment; Turning traffic; Unsignalized intersections

China

Highways; Safety and Human Factors; I83: Accidents and the Human Factor

Transportation Research Board Annual Meeting 2016 Paper #16-3831

TRIS, TRB, ATRI

Jan 12 2016 5:40PM