Abstract
In this paper, a rear-end collision control model is proposed using the fuzzy logic control scheme for the autonomous or cruising vehicles in Intelligent Transportation Systems (ITSs). Through detailed analysis of the car-following cases, our controller is established on some reasonable control rules. In addition, to refine the initialized fuzzy rules considering characteristics of the rear-end collisions, the genetic algorithm is introduced to reduce the computational complexity while maintaining accuracy. Numerical results indicate that our Genetic algorithm-optimized Fuzzy Logic Controller (GFLC) outperforms the traditional fuzzy logic controller in terms of better safety guarantee and higher traffic efficiency.
Highlights
A Rear-End Collision Avoidance Scheme for Intelligent Transportation SystemChen Chen , Hongyun Liu, Hongyu Xiang, Meilian Li1, Qingqi Pei and Shengda Wang2 1State Key Laboratory of Integrated Service Networks Xidian University, Xi’an 710071, China 2Jilin Electric Power Company Limited Communication Branch Transport Department, Changchun 130021, China
According to the investigations and statistics, of all the traffic accidents that ever took place, about 60 to 70 percent were caused by vehicle collisions, rear-end collisions [1]
Since the effect of a fuzzy logic-based controllers (FLC) relies on the number of fuzzy rules, an excessive number of such will directly impair its effectiveness
Summary
Chen Chen , Hongyun Liu, Hongyu Xiang, Meilian Li1, Qingqi Pei and Shengda Wang2 1State Key Laboratory of Integrated Service Networks Xidian University, Xi’an 710071, China 2Jilin Electric Power Company Limited Communication Branch Transport Department, Changchun 130021, China
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