Traffic signal timing optimisation based on genetic algorithm approach, including drivers' routing

Department of Civil and Environmental Engineering, Imperial College, Exhibition Road, SW7 2BU London, UK
Transportation Research Part B Methodological (Impact Factor: 2.94). 05/2004; 38(4):329-342. DOI: 10.1016/S0191-2615(03)00015-8
Source: RePEc

ABSTRACT The genetic algorithm approach to solve traffic signal control and traffic assignment problem is used to tackle the optimisation of signal timings with stochastic user equilibrium link flows. Signal timing is defined by the common network cycle time, the green time for each signal stage, and the offsets between the junctions. The system performance index is defined as the sum of a weighted linear combination of delay and number of stops per unit time for all traffic streams, which is evaluated by the traffic model of TRANSYT [User guide to TRANSYT, version 8, TRRL Report LR888, Transport and Road Research Laboratory, Crowthorne, 1980]. Stochastic user equilibrium assignment is formulated as an equivalent minimisation problem and solved by way of the Path Flow Estimator (PFE). The objective function adopted is the network performance index (PI) and its use for the Genetic Algorithm (GA) is the inversion of the network PI, called the fitness function. By integrating the genetic algorithms, traffic assignment and traffic control, the GATRANSPFE (Genetic Algorithm, TRANSYT and the PFE), solves the equilibrium network design problem. The performance of the GATRANSPFE is illustrated and compared with mutually consistent (MC) solution using numerical example. The computation results show that the GA approach is efficient and much simpler than previous heuristic algorithm. Furthermore, results from the test road network have shown that the values of the performance index were significantly improved relative to the MC.

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Available from: Halim Ceylan, Jul 02, 2015
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