Abstract
This paper proposes a novel solution to the traffic signal optimization problem by reducing the wait time of individual vehicle users at intersections within the urban transportation system. Optimized signal timings, not only reduce the wait time of vehicle users but also improve the mobility within the system. In effect, it also reduces the ever increasing emissions and fuel consumption. A novel synchronous discrete distance-time model is proposed to frame the problem on the basis of 2-layer Stackelberg game. Thereafter, the upper layer optimization is solved using evolutionary computation techniques (ACO, GA and a Hybrid of ACO and GA). A comparative analysis done over the aforementioned techniques indicates that the hybrid algorithm exhibits better performance for the proposed model.
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Sahana, S.K., Kumar, K. (2015). Hybrid Synchronous Discrete Distance Time Model for Traffic Signal Optimization. In: Jain, L., Behera, H., Mandal, J., Mohapatra, D. (eds) Computational Intelligence in Data Mining - Volume 1. Smart Innovation, Systems and Technologies, vol 31. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2205-7_3
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DOI: https://doi.org/10.1007/978-81-322-2205-7_3
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