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Multiagent-Based Simulation of Temporal-Spatial Characteristics of Activity-Travel Patterns Using Interactive Reinforcement Learning
Joint Authors
Wang, Wei
Ding, Haoyang
Yang, Min
Chen, Jian
Yang, Yingxiang
Source
Mathematical Problems in Engineering
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-01-30
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
We propose a multiagent-based reinforcement learning algorithm, in which the interactions between travelers and the environment are considered to simulate temporal-spatial characteristics of activity-travel patterns in a city.
Road congestion degree is added to the reinforcement learning algorithm as a medium that passes the influence of one traveler’s decision to others.
Meanwhile, the agents used in the algorithm are initialized from typical activity patterns extracted from the travel survey diary data of Shangyu city in China.
In the simulation, both macroscopic activity-travel characteristics such as traffic flow spatial-temporal distribution and microscopic characteristics such as activity-travel schedules of each agent are obtained.
Comparing the simulation results with the survey data, we find that deviation of the peak-hour traffic flow is less than 5%, while the correlation of the simulated versus survey location choice distribution is over 0.9.
American Psychological Association (APA)
Yang, Min& Yang, Yingxiang& Wang, Wei& Ding, Haoyang& Chen, Jian. 2014. Multiagent-Based Simulation of Temporal-Spatial Characteristics of Activity-Travel Patterns Using Interactive Reinforcement Learning. Mathematical Problems in Engineering،Vol. 2014, no. 2014, pp.1-11.
https://search.emarefa.net/detail/BIM-510840
Modern Language Association (MLA)
Yang, Min…[et al.]. Multiagent-Based Simulation of Temporal-Spatial Characteristics of Activity-Travel Patterns Using Interactive Reinforcement Learning. Mathematical Problems in Engineering No. 2014 (2014), pp.1-11.
https://search.emarefa.net/detail/BIM-510840
American Medical Association (AMA)
Yang, Min& Yang, Yingxiang& Wang, Wei& Ding, Haoyang& Chen, Jian. Multiagent-Based Simulation of Temporal-Spatial Characteristics of Activity-Travel Patterns Using Interactive Reinforcement Learning. Mathematical Problems in Engineering. 2014. Vol. 2014, no. 2014, pp.1-11.
https://search.emarefa.net/detail/BIM-510840
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-510840