Title: Ant colony optimisation for vehicle traffic systems: applications and challenges

Authors: Mohammad Reza Jabbarpour; Hossein Malakooti; Rafidah Md Noor; Nor Badrul Anuar; Norazlina Khamis

Addresses: Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur, 50603, Malaysia ' Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur, 50603, Malaysia ' Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur, 50603, Malaysia ' Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur, 50603, Malaysia ' Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur, 50603, Malaysia

Abstract: Ant-based algorithms simulate the cooperative behaviour of real ants in finding food resources. A significant number of studies have focused on the self-organised behaviour of ants in the natural environment to develop effective systems for dynamic problems. Ant-based systems have special properties such as scalability, adaptability, and dynamicity, which are the main requirements for solving vehicle traffic congestion problem. Thus, ant-based algorithms are now being adopted by vehicle traffic systems (VTSs) to guide vehicles to less congested paths. However, literature shows that comprehensive reviews are lacking in this field. The main contribution of this paper is the review and classification of the most relevant systems based on novel taxonomy. A survey that includes statistical analyses on ant-based VTS was conducted to identify the limitations and evaluation process of VTS. This paper concludes by proposing a general framework in applying ant colony optimisation to VTS.

Keywords: ant colony optimisation; ACO; vehicle traffic; traffic systems; VTS; swarm intelligence; multi-agent systems; MAS; agent-based systems; vehicle guidance.

DOI: 10.1504/IJBIC.2014.059970

International Journal of Bio-Inspired Computation, 2014 Vol.6 No.1, pp.32 - 56

Received: 30 Sep 2013
Accepted: 20 Dec 2013
Published online: 27 Sep 2014 *

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