Applied Intelligence

, Volume 46, Issue 1, pp 113–123 | Cite as

Nested hybrid evolutionary model for traffic signal optimization

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Abstract

A noble Nested Hybrid Evolutionary Model is presented to reduce the wait time of vehicles at traffic signals and improve the mobility within the road network. In effect, it contributes towards achieving green environment and reducing the fuel consumption. The proposed model is based on Bi-level Stackelberg Game in which the upper layer is “traffic signals” which is optimized using evolutionary computational techniques (ACO, GA and a Hybrid of ACO and GA) and the lower layer is “stochastic user equilibrium” for which road network is designed using Petri Net (PN) respectively. A comparative analysis has been carried out and it was found that nested hybrid model outperforms ACO and GA.

Keywords

Computational techniques Problem solving GA Ant Colony Genetic Algorithm Petri Net Game playing Traffic signal Optimization techniques 

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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.Department of Computer ScienceBITRanchiIndia

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