Enhancing the performance of existing urban traffic light control through extremum-seeking |
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| Institution: | 1. Department of Mechanical Engineering, The University of Melbourne, Parkville, Victoria 3010, Australia;2. School of Mathematical Sciences, Monash University, Clayton, Victoria 3800, Australia;1. Department of Informatics, Bioengineering, Robotics and Systems Engineering, University of Genova, Italy;2. Delft Center for Systems and Control, Delft University of Technology, The Netherlands;1. Department of Epidemiology, Health Economics and Prevention, University of Lille, 59000 Lille, France;2. EA 2694, University of Lille 2, DRCI, Lille University Hospital, 59000 Lille, France;1. The University of Queensland, Brisbane St Lucia, QLD 4072, Australia;2. Transportation Center Northwestern University, 600 Foster Street, Evanston, IL 60208, USA;1. Southwest Jiaotong University, School of Transportation and Logistics, Chengdu, PR China;2. State University of New York (SUNY) at New Paltz, Department of Geography, New Paltz, NY, USA;3. Imperial College London, Department of Civil and Environmental Engineering, South Kensington, SW7 2AZ, United Kingdom |
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| Abstract: | Urban traffic light controllers are responsible for maintaining good performance within the transport network. Most existing and proposed controllers have design parameters that require some degree of tuning, with the sensitivity of the performance measure to the parameter often high. To date, tuning has been largely treated as a manual calibration exercise but ignores the effects of changes in traffic condition, such as demand profile evolution due to urban population growth. To address this potential shortcoming, we seek to use a newly developed extremum-seeker to calibrate the parameters of existing urban traffic light controllers in real-time such that a certain performance measure is optimised. The results are demonstrated for three categories of traffic controllers on a microscopic urban traffic simulation. It is demonstrated that the extremum-seeking scheme is able to seek the optimal parameters, with respect to a certain performance measure, for each of these traffic light controllers in an urban, uni-modal traffic environment. |
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| Keywords: | Extremum-seeking Adaptive control Traffic control Online calibration |
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