Smart City Solution for Traffic Congestion Problem (A Q-Learning Approach) |
Author(s): |
Kunj Patel , LDRP-Institute of Technology & Research - KSV University, Gandhinagar, India |
Keywords: |
Smart City Solution for Traffic |
Abstract |
Our research focuses on implementing a learning algorithm that will allow traffic control devices to study traffic patterns/behaviours for a given intersection and optimize traffic flow by altering stoplight timing. We do this with a Q-Learning technique, where an intersection is knowledgeable of the presence of vehicles and their speed as they approach the intersection. From this information, the intersection is able to learn a set of state and action policies that allow traffic lights to make optimized decisions based on their current state. Our work seeks to alleviate traffic congestion on roads across the world by making intersections more aware of traffic presence and giving them the ability to take appropriate action to optimize traffic flow and minimize waiting time. |
Other Details |
Paper ID: IJSRDV6I100184 Published in: Volume : 6, Issue : 10 Publication Date: 01/01/2019 Page(s): 239-242 |
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