Artificial Bee Colony-Based Algorithm for Optimising Traffic Signal Timings
This study proposed Artificial Bee Colony (ABC) algorithm for finding optimal setting of traffic signals in coordinated signalized networks for given fixed set of link flows. For optimizing traffic signal timings in coordinated signalized networks, ABC wi
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stract This study proposed Artificial Bee Colony (ABC) algorithm for finding optimal setting of traffic signals in coordinated signalized networks for given fixed set of link flows. For optimizing traffic signal timings in coordinated signalized networks, ABC with TRANSYT-7F (ABCTRANS) model is developed. The ABC algorithm is a new population-based metaheuristic approach, and it is inspired by the foraging behavior of honeybee swarm. TRANSYT-7F traffic model is used to estimate total network performance index (PI). The ABCTRANS is tested on medium sized signalized road network. Results showed that the proposed model is slightly better in signal timing optimization in terms of final values of PI when it is compared with TRANSYT-7F in which Genetic Algorithm (GA) and Hillclimbing (HC) methods are exist. Results also showed that the ABCTRANS model improves the medium sized network’s PI by 2.4 and 2.7 % when it is compared with GA and HC methods.
1 Introduction In urban networks, traffic signals are used to control vehicle movements so as to reduce congestion, improve safety, and enable specific strategies such as minimizing delays, improving environmental pollution, etc. [1]. Signal systems that M. Dell’Orco (&) M. Marinelli Technical University of Bari, D.I.C.A.T.E.Ch., Bari, Italy e-mail: [email protected] M. Marinelli e-mail: [email protected] Ö. Baskan Pamukkale University, Department of Civil Engineering, Denizli, Turkey e-mail: [email protected]
V. Snášel et al. (eds.), Soft Computing in Industrial Applications, Advances in Intelligent Systems and Computing 223, DOI: 10.1007/978-3-319-00930-8_29, Springer International Publishing Switzerland 2014
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control road junctions are operated according to the type of junction. Although the optimization of signal timings for an isolated junction is relatively easy, the optimization of signal timings in coordinated road networks requires further research due to the ‘‘offset’’ term. Early methods such as that of Webster [2] only considered an isolated signalized junction. Later, fixed time strategies were developed that optimizing a group of signalized junctions using historical flow data [3]. For the Area Traffic Control (ATC), TRANSYT-7F is one of the most useful network study software tools for optimizing signal timing and also the most widely used program of its type. It simulates traffic in a network of signalized intersections to produce a cyclic flow profile of arrivals at each intersection that is used to compute a Performance Index (PI) for a given signal timing and staging plan. Optimization in TRANSYT-7F consists of a series of trial simulation runs, using the TRANSYT-7F simulation engine. Each simulation run is assigned a unique signal timing plan by the optimization processor. The optimizer applies the Hill-Climbing (HC) or Genetic Algorithm (GA) searching strategies. Although the GA is mathematically better suited for determining the absolute or global optimal solution, relative to HC optimization, it generally require
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