Optimizing Traffic Signal Settings in Smart Cities

Abstract

Traffic signals play a critical role in smart cities for mitigating traffic congestions and reducing the emission in metropolitan areas. This paper proposes a bi-level optimization framework to settle the optimal traffic signal setting problem. The upper-level problem determines the traffic signal settings to minimize the drivers' average travel time, while the lower-level problem aims for achieving the network equilibrium using the settings calculated at the upper level. Genetic algorithm is employed with the integration of microscopic-traffic-simulation based dynamic traffic assignment (DTA) to decouple the complex bi-level problem into tractable single-level problems which are solved sequentially. Case studies on a synthetic traffic network and a real-world traffic subnetwork are conducted to examine the effectiveness of the proposed model and relevant solution methods. Additional strategies are provided for the extension of the proposed model and the acceleration solution process in large-area traffic network applications.Index Terms-Smart cities, traffic signal setting, bi-level optimization, dynamic traffic assignment.

Interdependence between transportation system and power distribution system: a comprehensive review on models and applications

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“…In what follows we will review some of the trends that have been done in this regard. Shahidehpour et al in [28] have proposed a bi-level optimization framework to settle the optimal traffic signal setting problem. The upper-level problem determines the traffic signal settings to optimize the overall trip time; on the other hand, the lower level problem is for achieving the network equilibrium using the settings calculated at the upper level.…”