Traffic Responsive Signal Timing Plan Generation Based on Neural Network
| Autor: | Mudasser F. Wyne, Azzam ul-Asar, Riaz ul-Hasnain, M. Sadeeq Ullah, Jamal Ahmed |
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| Rok vydání: | 2009 |
| Předmět: |
Artificial neural network
Computer science business.industry Computer Science::Neural and Evolutionary Computation Real-time computing Mode (statistics) Particle swarm optimization Signal timing Highway Capacity Manual Control theory Learning rule Decision Sciences (miscellaneous) Artificial intelligence Cluster analysis business Information Systems |
| Zdroj: | International Journal of Intelligent Information Technologies. 5:84-101 |
| ISSN: | 1548-3665 1548-3657 |
| DOI: | 10.4018/jiit.2009070104 |
| Popis: | This article proposes a neural network based traffic signal controller, which eliminates most of the problems associated with the Traffic Responsive Plan Selection (TRPS) mode of the closed loop system. Instead of storing timing plans for different traffic scenarios, which requires clustering and threshold calculations, the proposed approach uses an Artificial Neural Network (ANN) model that produces optimal plans based on optimized weights obtained through its learning phase. Clustering in a closed loop system is root of the problems and therefore has been eliminated in the proposed approach. The Particle Swarm Optimization (PSO) technique has been used both in the learning rule of ANN as well as generating training cases for ANN in terms of optimized timing plans, based on Highway Capacity Manual (HCM) delay for all traffic demands found in historical data. The ANN generates optimal plans online to address real time traffic demands and thus is more responsive to varying traffic conditions. |
| Databáze: | OpenAIRE |
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