Real Time Identification of Road Traffic Control Measures

Khaled Almejalli, Keshav Dahal, M. Alamgir Hossain

Research output: Chapter in Book/Report/Conference proceedingChapter

10 Citations (Scopus)

Abstract

The operator of a traffic control centre has to select, the most appropriate traffic control action or combination of actions in a short time to manage the traffic network when non-recurrent road traffic congestion happens. This is a complex task, which requires expert knowledge, much experience and fast reaction. There are a large number of factors related to a traffic state as well as a large number of possible control actions that need to be considered during the decision making process. The identification of suitable control actions for a given non-recurrent traffic congestion call be tough even for experienced operators. Therefore, simulation models are used in many cases. However, simulating different traffic actions for it number of control measures In a complicated situation is very time-consuming. This chapter presents an intelligent method for the real-time identification of road traffic actions which assists the human operator of the traffic control centre in managing the current traffic state. The proposed system combines three soft-computing approaches, namely fuzzy logic, neural net-works, and genetic algorithms. The system employs a fuzzy-neural network tool with self-organization algorithm for initializing the membership functions, a genetic algorithm (GA) for identifying fuzzy rules, and (lie back-propagation neural network algorithm for fine tuning the system parameters. The proposed system has been tested for a case-study of a small section of the ring-road around Riyadh city in Saudi Arabia. The results obtained for the case study are promising and demonstrate that the proposed approach can provide an effective support for real-time traffic control.
Original languageEnglish
Title of host publicationAdvances in Computational Intelligence in Transport, Logistics, and Supply Chain Management
EditorsAndreas Fink, Franz Rothlauf
PublisherSpringer-Verlag Berlin
Pages63-80
Volume144
ISBN (Print)978-3-540-69024-5
DOIs
Publication statusPublished - 2008
Externally publishedYes

Publication series

NameStudies in Computational Intelligence

Keywords

  • Road traffic control
  • Fuzzy logic
  • Neural networks
  • Genetic algorithms

Cite this

Almejalli, K., Dahal, K., & Hossain, M. A. (2008). Real Time Identification of Road Traffic Control Measures. In A. Fink, & F. Rothlauf (Eds.), Advances in Computational Intelligence in Transport, Logistics, and Supply Chain Management (Vol. 144, pp. 63-80). (Studies in Computational Intelligence). Springer-Verlag Berlin. https://doi.org/10.1007/978-3-540-69390-1