Urban Traffic Intersection Incident Prediction Using AI Algorithm

DOI

10.2991/jcis.2006.302How to use a DOI?

Keywords

Incident Detection, Neural Network, Fuzzy Logic

Abstract

Automatic incident detection and characterization is urgently require in the development of advanced technologies used for reducing non-recurrent traffic congestion on urban traffic. This paper presents a new method using data mining to identify automatically freeway incidents. As a component of a real-time traffic adaptive control system for signal control, the algorithm feeds an incident report to the system’s optimization manager, which uses the information to determine the appropriate signal control strategy. Off-line tests were conducted to substantiate the performance of the proposed incident detection algorithm based on simulated data. The test results indicate the feasibility of achieving real-time incident detection utilizing the proposed method.

Copyright

© 2006, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Yaguang Kong
AU  - Huakui Chen
PY  - 2006/10
DA  - 2006/10
TI  - Urban Traffic Intersection Incident Prediction Using AI Algorithm
BT  - Proceedings of the 9th Joint International Conference on Information Sciences (JCIS-06)
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/jcis.2006.302
DO  - 10.2991/jcis.2006.302
ID  - Kong2006/10
ER  -