Using reinforcement learning to minimize the probability of delay occurrence in transportation

• Main Authors: CAO, Zhiguang, Guo, Hongliang, Song, Wen, Gao, Kaizhou, Chen, Zhengghua, Zhang, Le, Zhang, Xuexi
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2020
• Subjects: Reinforcement learning; Transportation; Arriving on time; Vehicle routing; Q-learning; Databases and Information Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/8158; https://ink.library.smu.edu.sg/context/sis_research/article/9161/viewcontent/Using_Reinforcement_Learning_to_Minimize_the_Probability_of_Delay_Occurrence_in_Transportation__1_.pdf
• Institution: Singapore Management University

Reducing traffic delay is of crucial importance for the development of sustainable transportation systems, which is a challenging task in the studies of stochastic shortest path (SSP) problem. Existing methods based on the probability tail model to solve the SSP problem, seek for the path that minim...