A Rear-End Collision Avoidance Scheme for Intelligent Transportation System

oleh: Chen Chen, Liu Hongyun, Xiang Hongyu, Li Meilian, Pei Qingqi, Wang Shengda

Format: Article
Diterbitkan: EDP Sciences 2016-01-01

Deskripsi

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.