Robust Reinforcement Learning Strategies with Evolving Curriculum for Efficient Bus Operations in Smart Cities

Robust Reinforcement Learning Strategies with Evolving Curriculum for Efficient Bus Operations in Smart Cities

Public transit systems are critical to the quality of urban life, and enhancing their efficiency is essential for building cost-effective and sustainable smart cities. Historically, researchers sought reinforcement learning (RL) applications to mitigate bus bunching issues with holding strategies. N...

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Bibliographic Details
Main Authors: Yuhan Tang, Ao Qu, Xuan Jiang, Baichuan Mo, Shangqing Cao, Joseph Rodriguez, Haris N Koutsopoulos, Cathy Wu, Jinhua Zhao
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Smart Cities
Subjects:
bus oeration
deep reinforcement learning
intelligent transportation systems
curriculum learning
smart cities
Online Access:https://www.mdpi.com/2624-6511/7/6/141
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