Browse by author
Lookup NU author(s): Dr Tessa Sayers
Full text for this publication is not currently held within this repository. Alternative links are provided below where available.
The paper presents insights into the process of optimising the parameters of a road-user responsive traffic signal controller with respect to several conflicting objectives. A multi-objective genetic algorithm (MOGA) was used to identify the parameter sets lying on the pareto-optimal front. This resulted in a collection of parameter settings that could be used to set the relative priority given by the signal controller to different road user groups (e.g. vehicles and pedestrians) when allocating green time dynamically in response to data from vehicle detectors and pedestrian push-button detectors. Issues covered in the paper include the choice and treatment of performance measures, the implementation of Pareto ranking to assign fitness, the use of niching to prevent convergence on a single area in the solution space and the use of stochastic simulation to obtain fitness values, with particular reference to the need to ensure robust results. Finally, the results of the use of the MOGA in this project will be presented.
Author(s): Sayers T
Editor(s): Köksalan, M., Zionts, S.
Publication type: Conference Proceedings (inc. Abstract)
Publication status: Published
Conference Name: 15th International Conference on Multiple Criteria Decision Making (MCDM)
Year of Conference: 2001
Library holdings: Search Newcastle University Library for this item
Series Title: Lecture Notes in Economics and Mathematical Systems