IDEAS home Printed from https://ideas.repec.org/p/uto/dipeco/201708.html
   My bibliography  Save this paper

An Agent-Based Simulation of Urban Passenger Mobility and Related Policies. The Case Study of an Italian Small City

Author

Listed:

Abstract

In this paper we present an agent-based model which reproduces transport choices of a sample of 5,000 citizens of the city of Varese (Northern Italy) and the corresponding PM emissions of their daily commutes. The aim of the model is testing the impact of public policies willing to foster commuting choices with lower PM emissions. Our model, taking inspiration from other existing works, considers the commuters‘ decisions on the transport mode to be used. A set of preferences, one for each transport mode - private car, bicycle, public transport - is assigned to every agent. Throughout the process, agents decide about the means for commuting on the basis of the relative price of the different means of transport, of the social influence and of the intensity of the policies applied. The initial distribution of preferences for each transport mode are inspired to empirical data on Varese commuters. Results suggest that preference-based policies are more effective if compared to price-based ones. However, the application of a mix of different policies seems to give the best outputs: the same amount of resources in terms of policy intensity produce much better results if they are allocated at the same time to two policies, then to one only.

Suggested Citation

  • Maggi,Elena & Vallino,Elena, 2017. "An Agent-Based Simulation of Urban Passenger Mobility and Related Policies. The Case Study of an Italian Small City," Department of Economics and Statistics Cognetti de Martiis. Working Papers 201708, University of Turin.
  • Handle: RePEc:uto:dipeco:201708
    as

    Download full text from publisher

    File URL: http://www.est.unito.it/do/home.pl/Download?doc=/allegati/wp2017dip/wp_8_2017.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Nicole Ronald & Russell Thompson & Stephan Winter, 2015. "Simulating Demand-responsive Transportation: A Review of Agent-based Approaches," Transport Reviews, Taylor & Francis Journals, vol. 35(4), pages 404-421, July.
    2. Weber, Martin, 1987. "Decision making with incomplete information," European Journal of Operational Research, Elsevier, vol. 28(1), pages 44-57, January.
    3. W. Brian Arthur, 2010. "Complexity, the Santa Fe approach, and non-equilibrium economics," History of Economic Ideas, Fabrizio Serra Editore, Pisa - Roma, vol. 18(2), pages 149-166.
    4. Yoram Shiftan & John Suhrbier, 2002. "The analysis of travel and emission impacts of travel demand management strategies using activity-based models," Transportation, Springer, vol. 29(2), pages 145-168, May.
    5. Maggi, Elena & Vallino, Elena, 2016. "Understanding urban mobility and the impact of public policies: The role of the agent-based models," Research in Transportation Economics, Elsevier, vol. 55(C), pages 50-59.
    6. Dablanc, Laetitia, 2007. "Goods transport in large European cities: Difficult to organize, difficult to modernize," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(3), pages 280-285, March.
    7. Wander Jager & Marco A. Janssen, 2002. "Stimulating diffusion of green products," Journal of Evolutionary Economics, Springer, vol. 12(3), pages 283-306.
    8. Flachsland, Christian & Brunner, Steffen & Edenhofer, Ottmar & Creutzig, Felix, 2011. "Climate policies for road transport revisited (II): Closing the policy gap with cap-and-trade," Energy Policy, Elsevier, vol. 39(4), pages 2100-2110, April.
    9. Hu, Xiaojun & Chang, Shiyan & Li, Jingjie & Qin, Yining, 2010. "Energy for sustainable road transportation in China: Challenges, initiatives and policy implications," Energy, Elsevier, vol. 35(11), pages 4289-4301.
    10. Graham-Rowe, Ella & Skippon, Stephen & Gardner, Benjamin & Abraham, Charles, 2011. "Can we reduce car use and, if so, how? A review of available evidence," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(5), pages 401-418, June.
    11. Lynne Hamill & Nigel Gilbert, 2009. "Social Circles: A Simple Structure for Agent-Based Social Network Models," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 12(2), pages 1-3.
    12. Ihab Kaddoura, 2015. "Marginal Congestion Cost Pricing in a Multi-agent Simulation Investigation of the Greater Berlin Area," Journal of Transport Economics and Policy, University of Bath, vol. 49(4), pages 560-578, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Davide Natalini & Giangiacomo Bravo, 2013. "Encouraging Sustainable Transport Choices in American Households: Results from an Empirically Grounded Agent-Based Model," Sustainability, MDPI, vol. 6(1), pages 1-20, December.
    2. Wolf, Ingo & Schröder, Tobias & Neumann, Jochen & de Haan, Gerhard, 2015. "Changing minds about electric cars: An empirically grounded agent-based modeling approach," Technological Forecasting and Social Change, Elsevier, vol. 94(C), pages 269-285.
    3. Chavez-Baeza, Carlos & Sheinbaum-Pardo, Claudia, 2014. "Sustainable passenger road transport scenarios to reduce fuel consumption, air pollutants and GHG (greenhouse gas) emissions in the Mexico City Metropolitan Area," Energy, Elsevier, vol. 66(C), pages 624-634.
    4. Priscila Pereira Suzart Carvalho & Ricardo Araújo Kalid & Jorge Laureano Moya Rodríguez & Sandro Breval Santiago, 2019. "Interactions among stakeholders in the processes of city logistics: a systematic review of the literature," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(2), pages 567-607, August.
    5. Auke Hoekstra & Maarten Steinbuch & Geert Verbong, 2017. "Creating Agent-Based Energy Transition Management Models That Can Uncover Profitable Pathways to Climate Change Mitigation," Complexity, Hindawi, vol. 2017, pages 1-23, December.
    6. Sung-Bae Cho & Jin-Young Kim, 2021. "Clustered embedding using deep learning to analyze urban mobility based on complex transportation data," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-19, April.
    7. Kamruzzaman, Md. & Baker, Douglas & Washington, Simon & Turrell, Gavin, 2013. "Residential dissonance and mode choice," Journal of Transport Geography, Elsevier, vol. 33(C), pages 12-28.
    8. Rudolf Vetschera, 2003. "Experimentation and Learning in Repeated Cooperation," Computational and Mathematical Organization Theory, Springer, vol. 9(1), pages 37-60, May.
    9. Bhardwaj, Chandan & Axsen, Jonn & Kern, Florian & McCollum, David, 2020. "Why have multiple climate policies for light-duty vehicles? Policy mix rationales, interactions and research gaps," Transportation Research Part A: Policy and Practice, Elsevier, vol. 135(C), pages 309-326.
    10. Xingping Zhang & Rao Rao & Jian Xie & Yanni Liang, 2014. "The Current Dilemma and Future Path of China’s Electric Vehicles," Sustainability, MDPI, vol. 6(3), pages 1-27, March.
    11. Dias, Luis C. & Climaco, Joao N., 2005. "Dealing with imprecise information in group multicriteria decisions: a methodology and a GDSS architecture," European Journal of Operational Research, Elsevier, vol. 160(2), pages 291-307, January.
    12. Jun Guan Neoh & Maxwell Chipulu & Alasdair Marshall, 2017. "What encourages people to carpool? An evaluation of factors with meta-analysis," Transportation, Springer, vol. 44(2), pages 423-447, March.
    13. Teixeira, João Filipe & Silva, Cecília & Moura e Sá, Frederico, 2023. "Factors influencing modal shift to bike sharing: Evidence from a travel survey conducted during COVID-19," Journal of Transport Geography, Elsevier, vol. 111(C).
    14. D’Orazio, Paola & Valente, Marco, 2019. "The role of finance in environmental innovation diffusion: An evolutionary modeling approach," Journal of Economic Behavior & Organization, Elsevier, vol. 162(C), pages 417-439.
    15. Breitmoser, Yves & Schweighofer-Kodritsch, Sebastian, 2019. "Obviousness around the clock," Discussion Papers, Research Unit: Market Behavior SP II 2019-203, WZB Berlin Social Science Center.
    16. Mustajoki, Jyri & Hamalainen, Raimo P. & Lindstedt, Mats R.K., 2006. "Using intervals for global sensitivity and worst-case analyses in multiattribute value trees," European Journal of Operational Research, Elsevier, vol. 174(1), pages 278-292, October.
    17. Behiri, Walid & Belmokhtar-Berraf, Sana & Chu, Chengbin, 2018. "Urban freight transport using passenger rail network: Scientific issues and quantitative analysis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 115(C), pages 227-245.
    18. Pedro A. P. Dias & Hugo Yoshizaki & Patricia Favero & Jose Geraldo Vidal Vieira, 2019. "Daytime or Overnight Deliveries? Perceptions of Drivers and Retailers in São Paulo City," Sustainability, MDPI, vol. 11(22), pages 1-16, November.
    19. Yang, Chao & Chen, Mingyang & Yuan, Quan, 2021. "The geography of freight-related accidents in the era of E-commerce: Evidence from the Los Angeles metropolitan area," Journal of Transport Geography, Elsevier, vol. 92(C).
    20. Daniele Crotti & Elena Maggi, 2023. "Social Responsibility and Urban Consolidation Centres in Sustainable Freight Transport Markets," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 9(2), pages 829-850, July.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:uto:dipeco:201708. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Piero Cavaleri or Marina Grazioli (email available below). General contact details of provider: https://edirc.repec.org/data/detorit.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.