Citation

J. Highway Transp. Res. Dev. (English ed.) 2017; 11(2): 103-110.

Copyright

(Copyright © 2017, Research Institute of Highway, Ministry of Transport in association with the American Society of Civil Engineers)

DOI

10.1061/JHTRCQ.0000573

PMID

unavailable

Abstract

The key to improving performance requirements for longitudinal collision avoidance systems under collaborative vehicles is the accurate judgment and the estimation of vehicle driving state and appropriate safety distance model. In order to improve performance requirements of longitudinal collision avoidance systems under collaborative vehicles, the longitudinal safety distance model based on vehicle driving state estimation is proposed, first through the establishment of the vehicle kinematics mode which considers the vehicle front and rear axle centre position and the state equation of vehicle running state parameter estimation, using the extended kalman filter to realize the accurate estimation of vehicle driving state parameters; then based on the accurate estimation of vehicle driving state parameters, according to the front vehicle's different state. The longitudinal safety distance models are built when the front vehicle is stationary, in uniform motion and braking. The simulation platforms of vehicle state estimation and longitudinal safety distance model are built based on Matlab/Simulink. The simulation results show the accuracy of vehicle driving state parameters estimation and the effectiveness of longitudinal collision avoidance safety distance model.

Language: en