Urban Traffic Intersection Incident Prediction Using AI Algorithm
- Yaguang Kong 0, Huakui Chen
- Corresponding Author
- Yaguang Kong
0Hangzhou Dianzi University
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- https://doi.org/10.2991/jcis.2006.302How to use a DOI?
- Incident Detection, Neural Network, Fuzzy Logic
- 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.
- 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 - NaN/NaN DA - NaN/NaN 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 - KongNaN/NaN ER -