Optimising traffic light systems using particle swarm optimisation / Amanina Rozani
Particle Swarm Optimisation (PSO) is a commonly used method to solve optimisation problems. These problems typically aim to maximise or minimise a subject. The PSO method was proposed by Kennedy and Eberhart, inspired by the movement of animals in swarms. This method assumes that every swarm particl...
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| Format: | Thesis |
| Language: | English |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://ir.uitm.edu.my/id/eprint/95190/1/95190.pdf |
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| Summary: | Particle Swarm Optimisation (PSO) is a commonly used method to solve optimisation problems. These problems typically aim to maximise or minimise a subject. The PSO method was proposed by Kennedy and Eberhart, inspired by the movement of animals in swarms. This method assumes that every swarm particle is able to update its position until an optimum point is achieved. A real-life problem that could employ the particle swarm optimisation technique is the everyday challenge of traffic congestions. One solution to reduce traffic congestions is to implement proper traffic light cycles that could potentially increase road capacity and decrease journey time. This project aims to produce optimised green light durations of traffic lights using the particle swarm optimisation method with varying number of iterations. The durations that were produced with the implementation of PSO in MATLAB were incorporated into the traffic lights of a road network in a traffic simulator, SUMO. These cycles were compared using the outcomes of these simulations based on road capacity, total journey time, and total stop and wait time. By the end of the research, it was found that 6 of the 10 produced cycles were able to optimise the traffic conditions of the traffic simulation. |
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