1. [1] N. Leng and F. Corman, "The role of information availability to passengers in public transport disruptions: An agent-based simulation approach", Transportation Research Part A: Policy and Practice, vol. 133, pp. 214-236, 2020. [ DOI:10.1016/j.tra.2020.01.007] 2. [2] O. Dib, M.-A. Manier, L. Moalic, and A. Caminada, "A multimodal transport network model and efficient algorithms for building advanced traveler information systems", Transportation research procedia, vol. 22, pp. 134-143, 2017. [ DOI:10.1016/j.trpro.2017.03.020] 3. [3] M. Jakimavičius, V. Palevičius, J. Antuchevičiene, and T. Karpavičius, "Internet GIS-Based Multimodal Public Transport Trip Planning Information System for Travelers in Lithuania", ISPRS International Journal of Geo-Information, vol. 8, no. 8, p. 319, 2019. [ DOI:10.3390/ijgi8080319] 4. [4] O. Kem, F. Balbo, and A. Zimmermann, "Traveler-oriented advanced traveler information system based on dynamic discovery of resources: potentials and challenges", Transportation research procedia, vol. 22, pp. 635-644, 2017. [ DOI:10.1016/j.trpro.2017.03.059] 5. [5] P.C Bouman, "Passengers, Crowding and Complexity: Models for passenger oriented public transport", Erasmus University Rotterdam, 2017. 6. [6] J. Peng, J. Zhi-cai, and G. Lin-jie, "Application of the Expanded Theory of Planned Behavior in Intercity Travel Behavior," Discrete Dynamics in Nature and Society, vol. 2014, p. 308674, Mar. 2014, doi: 10.1155/2014/308674. [ DOI:10.1155/2014/308674] 7. [7] J. Scheiner, "Why is there change in travel behaviour? In search of a theoretical framework for mobility biographies," Erdkunde, vol. 72, no. 1, pp. 41-62, 2018. [ DOI:10.3112/erdkunde.2018.01.03] 8. [8] K. Maat, B. Van Wee, and D. Stead, "Land use and travel behaviour: expected effects from the perspective of utility theory and activity-based theories," Environment and Planning B: Planning and Design, vol. 32, no. 1, pp. 33-46, 2005. [ DOI:10.1068/b31106] 9. [9] J. Hong, P. (Vonu) Thakuriah, P. Mason, and C. Lido, "The role of numeracy and financial literacy skills in the relationship between information and communication technology use and travel behaviour," Travel Behaviour and Society, vol. 21, pp. 257-264, Oct. 2020, doi: 10.1016/j.tbs.2020.07.007. [ DOI:10.1016/j.tbs.2020.07.007] 10. [10] R. Tsuchiya, Y. Sugiyama, K. Yamauchi, K. Fujinami, R. Arisawa, and T. Nakagawa, "Route-choice support system for passengers in the face of unexpected disturbance of train operations", WIT Transactions on the Built Environment, vol. 88, pp. 189-197, 2006. [ DOI:10.2495/CR060191] 11. [11] M. van Essen, T. Thomas, E. van Berkum, and C. Chorus, "Travelers' compliance with social routing advice: evidence from SP and RP experiments", Transportation, vol. 47, no. 3, pp. 1047-1070, 2020. [ DOI:10.1007/s11116-018-9934-z] 12. [12] Y. Ge, P. Jabbari, D. MacKenzie, and J. Tao, "Effects of a public real-time multi-modal transportation information display on travel behavior and attitudes", Journal of Public Transportation, vol. 20, no. 2, p. 3, 2017. [ DOI:10.5038/2375-0901.20.2.3] 13. [13] B. Van Wee, K. Geurs, and C. Chorus, "Information, communication, travel behavior and accessibility", Journal of Transport and Land Use, vol. 6, no. 3, pp. 1-16, 2013. [ DOI:10.5198/jtlu.v6i3.282] 14. [14] J. N. Fotis, "The Use of social media and its impacts on consumer behaviour: the context of holiday travel", PhD diss., Bournemouth University, 2015. 15. [15] M. Meng, A. A. Memon, Y. D. Wong, and S.-H. Lam, "Impact of traveller information on mode choice behaviour", presented at Proceedings of the Institution of Civil Engineers-Transport, Thomas Telford Ltd, 2018. [ DOI:10.1680/jtran.16.00058] 16. [16] A. M. Al-Adamat, J. A. Al-Gasawneh, and N. A. Sourak, "The Mediating Effect of Perceived Value on the Relationship between Online Promotion and Travel Intention", Test Engineering and Management, vol. 83, pp. 14911 - 14920, 2020. 17. [17] C. Pronello, J. P. R. V. Simão, and V. Rappazzo, "The effects of the multimodal real time information systems on the travel behaviour", Transportation research procedia, vol. 25, pp. 2677-2689, 2017. [ DOI:10.1016/j.trpro.2017.05.172] 18. [18] J. Barceló, J. Casas, J. Ferrer, and D. García, "Modelling advanced transport telematic applications with microscopic simulators: The case of AIMSUN2", in Traffic and Mobility, Springer, pp. 205-221, 1999. [ DOI:10.1007/978-3-642-60236-8_14] 19. [19] T. Arentze and H. Timmermans, Albatross: a learning based transportation oriented simulation system. Citeseer, 2000. 20. [20] Q. Han, T. Arentze, H. Timmermans, D. Janssens, and G. Wets, "The effects of social networks on choice set dynamics: Results of numerical simulations using an agent-based approach", Transportation Research Part A: Policy and Practice, vol. 45, no. 4, pp. 310-322, May 2011. [ DOI:10.1016/j.tra.2011.01.008] 21. [21] M. Paulsen, T. K. Rasmussen, and O. A. Nielsen, "Modelling railway-induced passenger delays in multi-modal public transport networks: an agent-based Copenhagen case study using empirical train delay data", presented at the 14th Conference on Advanced Systems in Public Transport and TransitData 2018. 22. [22] I. Kaddoura and K. Nagel, "Using real-world traffic incident data in transport modeling", Procedia computer science, vol. 130, pp. 880-885, 2018. [ DOI:10.1016/j.procs.2018.04.084] 23. [23] A. Stahel, F. Ciari, and K. W. Axhausen, "Modeling impacts of weather conditions in agent-based transport microsimulations", presented at the TRB 93rd Annual Meeting Compendium of Papers, Washington, 2014. 24. [24] C. Heyndrickx, F. Rodric, P. M. Bösch, and F. Ciari, "Benefits of informing travellers in case of extreme precipitation events: A model based case study for Zurich using MATSim", Arbeitsberichte Verkehrs-und Raumplanung, vol. 1108, 2015. 25. [25] J. Hong, P. (Vonu) Thakuriah, P. Mason, and C. Lido, "The role of numeracy and financial literacy skills in the relationship between information and communication technology use and travel behaviour", Travel Behaviour and Society, vol. 21, pp. 257-264, Oct. 2020. [ DOI:10.1016/j.tbs.2020.07.007] 26. [26] M. Balmer, N. Cetin, K. Nagel, and B. Raney, "Towards truly agent-based traffic and mobility simulations", Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems, New York, 2004. 27. [27] D. Charypar and K. Nagel, "Generating complete all-day activity plans with genetic algorithms", Transportation, vol. 32, no. 4, pp. 369-397, 2005. [ DOI:10.1007/s11116-004-8287-y] 28. [28] H. Zheng et al., "A primer for agent-based simulation and modeling in transportation applications", United States: Federal Highway Administration, 2013. 29. [29] K. W Axhausen, A. Horni, and K. Nagel, "The multi-agent transport simulation MATSim". Ubiquity Press, 2016. [ DOI:10.5334/baw] 30. [30] L. Zhang and D. Levinson, "Agent-based approach to travel demand modeling: Exploratory analysis," Transp. Res. Rec., vol. 1898, no. 1, pp. 28-36, 2004. [ DOI:10.3141/1898-04]
|