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Cambridge, MA, USA
May 20, 2013 to May 24, 2013
pp: 459-465
ABSTRACT
The problem of how to adjust speed of vehicles so that they can arrive at the intersection when the light is green can be solved by means of Green Light Optimal Speed Advisory (GLOSA). The existing GLOSA approaches are single segment, that is, they consider traffic lights independently by providing vehicles with the optimal speed for the segment ahead of the nearest traffic lights. In this article we introduce a new approach-a multi segment GLOSA-according to which several lights in sequence on a vehicle's route are taken into account. The speed optimisation process is performed using a genetic algorithm. We assume that a vehicle has access to all traffic light phase schedules that it will encounter on its route. The route is composed of segments divided by traffic lights. The proposed GLOSA provides a driver with speed advisory for each segment according to selected preferences like minimisation of total traveling time or fuel consumption. We demonstrate, that in free-flow conditions such multi-segment GLOSA results in much better results when compared with single-segment approach.
INDEX TERMS
Genetic Algorithms, Traffic lights, GLOSA, Smart City, Optimisation,
CITATION
Marcin Seredynski, Wojciech Mazurczyk, Djamel Khadraoui, "Multi-segment Green Light Optimal Speed Advisory", IPDPSW, 2013, 2013 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum (IPDPSW), 2013 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum (IPDPSW) 2013, pp. 459-465, doi:10.1109/IPDPSW.2013.157
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