9th Joint International Conference on Information Sciences (JCIS-06)

Urban Traffic Intersection Incident Prediction Using AI Algorithm

Authors
Yaguang Kong 0, Huakui Chen
Corresponding Author
Yaguang Kong
0Hangzhou Dianzi University
Available Online October 2006.
DOI
https://doi.org/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.
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Proceedings
9th Joint International Conference on Information Sciences (JCIS-06)
Part of series
Advances in Intelligent Systems Research
Publication Date
October 2006
ISBN
978-90-78677-01-7
DOI
https://doi.org/10.2991/jcis.2006.302How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

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