Analyzing Transport Policies in Developing Countries with ABM (2404.19745v1)
Abstract: Deciphering travel behavior and mode choices is a critical aspect of effective urban transportation system management, particularly in developing countries where unique socio-economic and cultural conditions complicate decision-making. Agent-based simulations offer a valuable tool for modeling transportation systems, enabling a nuanced understanding and policy impact evaluation. This work aims to shed light on the effects of transport policies and analyzes travel behavior by simulating agents making mode choices for their daily commutes. Agents gather information from the environment and their social network to assess the optimal transport option based on personal satisfaction criteria. Our findings, stemming from simulating a free-fare policy for public transit in a developing-country city, reveal a significant influence on decision-making, fostering public service use while positively influencing pollution levels, accident rates, and travel speed.
- N. F. M. Ali, A. F. M. Sadullah, A. P. Majeed, M. A. M. Razman, M. A. Zakaria, and A. F. A. Nasir, “Travel mode choice modeling: Predictive efficacy between machine learning models and discrete choice model,” The Open Transportation Journal, vol. 15, no. 1, 2021.
- A. Kangur, W. Jager, R. Verbrugge, and M. Bockarjova, “An agent-based model for diffusion of electric vehicles,” Journal of Environmental Psychology, vol. 52, pp. 166–182, 2017.
- N. F. M. Ali, A. F. M. Sadullah, A. P. A. Majeed, M. A. M. Razman, and R. M. Musa, “The identification of significant features towards travel mode choice and its prediction via optimised random forest classifier: An evaluation for active commuting behavior,” Journal of Transport & Health, vol. 25, p. 101362, 2022.
- Y. E. Hawas, M. N. Hassan, and A. Abulibdeh, “A multi-criteria approach of assessing public transport accessibility at a strategic level,” Journal of Transport Geography, vol. 57, pp. 19–34, 2016.
- H. C. Williams, “On the formation of travel demand models and economic evaluation measures of user benefit,” Environment and planning A, vol. 9, no. 3, pp. 285–344, 1977.
- G. O. Kagho, M. Balac, and K. W. Axhausen, “Agent-based models in transport planning: Current state, issues, and expectations,” Procedia Computer Science, vol. 170, pp. 726–732, 2020.
- O. T. Faboya, B. Ryan, G. P. Figueredo, and P.-O. Siebers, “Using agent-based modelling for investigating modal shift: the case of university travel,” Computers & Industrial Engineering, vol. 139, p. 106077, 2020.
- B. Chen and H. H. Cheng, “A review of the applications of agent technology in traffic and transportation systems,” IEEE Transactions on intelligent transportation systems, vol. 11, no. 2, pp. 485–497, 2010.
- J. X. Hagen, C. F. Pardo, and J. B. Valente, “Motivations for motorcycle use for urban travel in latin america: A qualitative study,” Transport Policy, vol. 49, pp. 93–104, 2016.
- T. Eccarius and C.-C. Lu, “Adoption intentions for micro-mobility–insights from electric scooter sharing in taiwan,” Transportation research part D: transport and environment, vol. 84, p. 102327, 2020.
- A. Y. Suatmadi, F. Creutzig, and I. M. Otto, “On-demand motorcycle taxis improve mobility, not sustainability,” Case Studies on Transport Policy, vol. 7, no. 2, pp. 218–229, 2019.
- BNN-Breaking-News. (2023) Colombian president gustavo petro unveils bold plan for free mass transit for low-income citizens. [Online]. Available: https://bnnbreaking.com/world/colombia/colombian-president-gustavo-petro-unveils-bold-plan-for-free-mass-transit-for-low-income-citizens/
- M. A. Janssen and W. Jager, “Simulating market dynamics: Interactions between consumer psychology and social networks,” Artificial life, vol. 9, no. 4, pp. 343–356, 2003.
- K. Carley, “A theory of group stability,” American sociological review, pp. 331–354, 1991.
- K. Salazar-Serna, L. H. X. Ng, K. Carley, L. Cadavid, and C. J. Franco, “Simulating the social influence in transport mode choices,” in 2023 Winter Simulation Conference (WSC). IEEE, 2023, pp. 3154–3165.
- K. Salazar-Serna and J. Diaz. (2023) Survey summary: Mobility in cali 2023. [Online]. Available: https://public.tableau.com/app/profile/jes.s.d.az.blanco/viz/Encuestas_16844425109290/Surveysummary
- W. Jager and M. Janssen, “An updated conceptual framework for integrated modeling of human decision making: The consumat ii,” in paper for workshop complexity in the Real World@ ECCS, 2012, pp. 1–18.
- K. Salazar-Serna, L. Cadavid, C. J. Franco, and K. M. Carley, “Simulating transport mode choices in developing countries,” in International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction and Behavior Representation in Modeling and Simulation. Springer, 2023, pp. 209–218.
- K. M. Carley, “Validating computational models,” Paper available at http://www. casos. cs. cmu. edu/publications/papers. php, 1996.
- B. D. Romanowska Iza, Stefani Crabtree and K. Harris. (2019) Agent-based modeling for archaeologists. a step-by-step guide for using agent-based modeling in archaeological research (part i of iii). [Online]. Available: https://static.cambridge.org/content/id/urn:cambridge.org:id:article:S2326376819000068/resource/name/S2326376819000068sup002.pdf
- M. Cabrera. (2022) Movilidad urbana: ¿pública o privada? [Online]. Available: https://cambiocolombia.com/opinion/puntos-de-vista/movilidad-urbana-publica-o-privada