A Comparative Study of Algorithms for Intelligent Traffic Signal Control
- URL: http://arxiv.org/abs/2109.00937v1
- Date: Thu, 2 Sep 2021 13:26:49 GMT
- Title: A Comparative Study of Algorithms for Intelligent Traffic Signal Control
- Authors: Hrishit Chaudhuri, Vibha Masti, Vishruth Veerendranath and Dr. S
Natarajan
- Abstract summary: Methods have been explored to effectively optimise traffic signal control to minimise waiting times and queue lengths.
The methods were tested on a simulation of a real-world intersection in Bangalore, India.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: In this paper, methods have been explored to effectively optimise traffic
signal control to minimise waiting times and queue lengths, thereby increasing
traffic flow. The traffic intersection was first defined as a Markov Decision
Process, and a state representation, actions and rewards were chosen.
Simulation of Urban MObility (SUMO) was used to simulate an intersection and
then compare a Round Robin Scheduler, a Feedback Control mechanism and two
Reinforcement Learning techniques - Deep Q Network (DQN) and Advantage
Actor-Critic (A2C), as the policy for the traffic signal in the simulation
under different scenarios. Finally, the methods were tested on a simulation of
a real-world intersection in Bengaluru, India.
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