A Rear-End Collision Avoidance Scheme for Intelligent Transportation System

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 rule...

Full description

Saved in:
Bibliographic Details
Published in:MATEC web of conferences 2016-01, Vol.81, p.2001
Main Authors: Chen, Chen, Liu, Hongyun, Xiang, Hongyu, Li, Meilian, Pei, Qingqi, Wang, Shengda
Format: Article
Language:English
Subjects:
Car following
Collision avoidance
Fuzzy control
Fuzzy logic
Genetic algorithms
Intelligent transportation systems
Mathematical models
Traffic safety
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
ISSN:2261-236X
2274-7214
2261-236X
DOI:10.1051/matecconf/20168102001