MODELING OF PASSENGERS’ CHOICE USING INTELLIGENT AGENTS WITH REINFORCEMENT LEARNING IN SHARED INTERESTS SYSTEMS; A BASIC APPROACH

Publications

Share / Export Citation / Email / Print / Text size:

Transport Problems

Silesian University of Technology

Subject: Economics , Transportation , Transportation Science & Technology

GET ALERTS

eISSN: 2300-861X

DESCRIPTION

12
Reader(s)
45
Visit(s)
0
Comment(s)
0
Share(s)

VOLUME 14 , ISSUE 2 (June 2019) > List of articles

MODELING OF PASSENGERS’ CHOICE USING INTELLIGENT AGENTS WITH REINFORCEMENT LEARNING IN SHARED INTERESTS SYSTEMS; A BASIC APPROACH

Sergey VIKHAREV * / Maxim LYAPUSTIN / Danil MIRONOV / Irina NIZOVTSEVA / Vladimir SINITSYN

Keywords : Intelligent agents; transport choosing model; passenger satisfaction index;  transport quality

Citation Information : Transport Problems. Volume 14, Issue 2, Pages 43-53, DOI: https://doi.org/10.20858/tp.2019.14.2.4

License : (CC BY 4.0)

Received Date : 09-December-2017 / Accepted: 05-June-2019 / Published Online: 14-July-2019

ARTICLE

ABSTRACT

The purpose of this paper is to build a model for assessing the satisfaction of passenger service by the public transport system. The system is constructed using intelligent agents, whose action is based on self-learning principles. The agents are passengers who depend on transport and can choose between two modes: a car or a bus wherein their choice of transport mode for the next day is based on their level of satisfaction and their neighbors’ satisfaction with the mode they used the day before. The paper considers several algorithms of agent behavior, one of which is based on reinforcement learning. Overall, the algorithms take into account the history of the agents’ previous trips and the quality of transport services. The outcomes could be applied in assessing the quality of the transport system from the point of view of passengers.

Content not available PDF Share

FIGURES & TABLES

REFERENCES

1. Sizii, S. & Shichko, A. & Vikharev, S. Organizational processes in networks with shared interests: relevance, statement of the problem, research plan. Bulletin of USURTU. 2009. No. 1-2. P. 34-42.

2. Сай, В. Планетарные структуры управления на железнодорожном транспорте. Москва: ВИНИТИ РАН. 2003. 336 с. [In Russian: Sai, V. Planetary management structure on railway transport. Moscow: VINITI RAN, 2003. 336 p.].

3. Сай, В. & Сизый, С. Образование, функционирование и распад организационных сетей. Екатеринбург: УрГУПС. 2011. 270 с. [In Russian: Sai, V. & Sizii, S. The formation, functioning and dissolution of organizational networks. Ekaterinburg USURTU. 2011. 270 p.].

4. Logistics performance index: Quality of trade and transport-related infrastructure. The World Bank Group. Available at: https://data.worldbank.org/indicator/LP.LPI.INFR.XQ.

5. Sutton, R. & Barto, A. Reinforcement Learning: An Introduction. London: The MIT Press. 2017.

6. Olivkova, I. Evaluation of public transport criteria in terms of passengers’ satisfaction. Transport and Telecommunication. 2016. Vol. 17. No. 1. P. 18-27.

7. Ismail, R. & Hafezi, M.H. & Nor, R.M. & et al. Passengers preference and satisfaction of public transport in Malaysia. Australian Journal of Basic and Applied Sciences. 2012. Vol. 6(8). P. 410416.

8. Hwe, S.K. & Cheung, R.K. & Wan, Y. Merging bus routes in Hong Kong's central business district: Analysis and models. Transportation Research Part A: Policy and Practice. 2006. Vol. 40. No. 10. P. 918-935.

9. Van Lierop, D. & Badami, M.G. & El-Geneidy, A.M. What influences satisfaction and loyalty in public transport? A review of the literature. Routledge. 2018. Vol. 38. No. 1. P. 52-72. 

10. Wang, C. & Weng, J. & Chen, Z. & et al. A method of building bus satisfaction evaluation index system based on passengers' perception. American Society of Civil Engineers (ASCE). 2018. Vol. 2018-January. P. 4675-4683.

11. Weng, J. & Di, X. & Wang, C. & et al. A bus service evaluation method from passenger's perspective based on satisfaction surveys: A case study of Beijing. China. Sustainability MDPI AG. 2018. Vol. 10. No. 8. P. 1-15.

12. Fitzsimmons, E.G. Downside of ride-hailing. More gridlock. The New York Times. March 8, 2017.

13. Crawford-Brown, D.J. The changing influences on commuting mode choice in urban England under Peak Car: A discrete choice modelling approach. Transportation Research Part F: Traffic Psychology and Behavior. October, 2018. Vol. 58. P. 167-176.

EXTRA FILES

COMMENTS