Reinforcement learning-based route guidance system with dynamic traffic condition

This paper proposes a method of using reinforcement learning to solve dynamic route planning problems, and the change from static learning rate to dynamic learning rate is capable of dealing with emergent congestion. Firstly, some conventional algorithms and reinforcement learning methods are introd...

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Bibliographic Details
Main Author: Li, Yuzhen
Other Authors: Wang Dan Wei
Format: Thesis-Master by Coursework
Language:English
Published: Nanyang Technological University 2022
Subjects:
Online Access:https://hdl.handle.net/10356/155442
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Institution: Nanyang Technological University
Language: English
Description
Summary:This paper proposes a method of using reinforcement learning to solve dynamic route planning problems, and the change from static learning rate to dynamic learning rate is capable of dealing with emergent congestion. Firstly, some conventional algorithms and reinforcement learning methods are introduced in chapter 2. Chapter 3 will discuss the software tool used for creating environment simulation and some basis of reinforcement learning. Then, the comparison of conventional reinforcement learning and proposed method is shown in detail on chapter 4. Lastly, chapter 6 is aimed at discussing some problems of proposed method and future works how to solve this problem.