Modeling of passengers’ choice using intelligent agents with reinforcement learning in shared interests systems; A basic approach

• Autorzy: Vikharev Sergey , Lyapustin Maxim , Mironov Danil , Nizovtseva Irina , Sinitsyn Vladimir

Identyfikatory

DOI

10.20858/tp.2019.14.2.4

• Języki publikacji: EN

Abstrakty

EN

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.

Słowa kluczowe

EN

intelligent agents; transport choosing model; passenger satisfaction index; transport quality

PL

inteligentni agenci; wybór modelu transportu; wskaźnik satysfakcji pasażera; jakość transportu

• Wydawca: Wydawnictwo Politechniki Śląskiej
• Czasopismo: Transport Problems
• Rocznik: 2019
• Tom: T. 14, z. 2
• Strony: 43--53
• Opis fizyczny: Bibliogr. 13 poz.

Twórcy

autor

Vikharev Sergey

• Ural Federal University 19 Mira, Ekaterinburg, 620002, Russia

autor

Lyapustin Maxim

• Ural Federal University 19 Mira, Ekaterinburg, 620002, Russia

autor

Mironov Danil

• Ural Federal University 19 Mira, Ekaterinburg, 620002, Russia

autor

Nizovtseva Irina

• Ural Federal University 19 Mira, Ekaterinburg, 620002, Russia

autor

Sinitsyn Vladimir

• Ural Federal University 19 Mira, Ekaterinburg, 620002, Russia

Bibliografia

• 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. 410-416.
• 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.

Uwagi

PL

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).