Author Information
Genetic vs. particle swarm optimization techniques for traffic light signals timing
Journal Title, Volume, Page:
2014 6th International Conference on Computer Science and Information Technology (CSIT); 03/2014
Year of Publication:
2014
Preferred Abstract (Original):
A good controlling for the traffic lights on the network road may
solve the traffic congestion in the cities. This paper deals with the
optimization of traffic light signals timing. We used four different
heuristic optimization techniques, three types of Genetic algorithm and
particle of swarm algorithm. Techniques were applied on a case study of
network road which contains 13 traffic lights. We used SUMO (Simulation
of Urban MObility) to simulate the network. Heuristic optimization
techniques themselves need to be calibrated. Calibrating them using the
real problem is time consuming because simulation is computation
demanding. We tried to calibrate them using a function that is assumed
to have similar response surface but lighter computation demand, then
use the calibrated technique to optimize the traffic light signals
timing. After some comparing processes of optimization results, we
discovered that one type of GA and PS at determined parameters are more
suitable to produce the minimum total travel time.
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