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Integrated models of land use and transportation for the autonomous vehicle revolution

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  • Jason Hawkins
  • Khandker Nurul Habib

Abstract

The advent of the autonomous vehicle (AV) will affect not only the transportation system, but also future patterns of land development. Integrated land use and transportation models will be critical tools in assessing the path forward with this technology. Key questions with respect to land use impacts of AVs arise from potential changes in sensitivity to travel and reduced demand for parking. It is an open question whether AVs will induce urban sprawl, or whether spatial economies of agglomeration will mitigate any reductions in travel time sensitivity. The deployment of shared fleets of AVs would likely reduce parking demand, producing yet to be explored impacts on property development within existing urban footprints. We perform a critical assessment of currently operational models and their ability to represent the adoption of AVs. We identify the representation of time in such models as a vital component requiring additional development to model this new technology. Existing model applications have focused on the discrete addition of new infrastructure or policy at a fixed point in time, whereas AV adoption will occur incrementally through time. Stated adaptation surveys are recommended as tools to quantify preferences and develop relevant model inputs. It is argued that existing models that assume comparatively static equilibrium have been convenient in the past, but are insufficient to model technology adoption. In contrast, dynamic model frameworks lack sufficient structure to maintain reasonability under large perturbations from base conditions. The ongoing advancement of computing has allowed models to move away from being mechanistic aggregate tools, towards behaviourally rich depictions of individual persons and firms. However, much work remains to move from projections of existing conditions into the future, to the evolution of the spatial economy as it evolves through time in response to new technologies and exogenous stresses. Principles from complex and evolutionary systems theory will be important in the development of models with the capacity to consider such dynamics.

Suggested Citation

  • Jason Hawkins & Khandker Nurul Habib, 2019. "Integrated models of land use and transportation for the autonomous vehicle revolution," Transport Reviews, Taylor & Francis Journals, vol. 39(1), pages 66-83, January.
  • Handle: RePEc:taf:transr:v:39:y:2019:i:1:p:66-83
    DOI: 10.1080/01441647.2018.1449033
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    Citations

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    Cited by:

    1. Tan Yigitcanlar & Federico Cugurullo, 2020. "The Sustainability of Artificial Intelligence: An Urbanistic Viewpoint from the Lens of Smart and Sustainable Cities," Sustainability, MDPI, vol. 12(20), pages 1-24, October.
    2. Almlöf, Erik & Nybacka, Mikael & Pernestål, Anna & Jenelius, Erik, 2022. "Will leisure trips be more affected than work trips by autonomous technology? Modelling self-driving public transport and cars in Stockholm, Sweden," Transportation Research Part A: Policy and Practice, Elsevier, vol. 165(C), pages 1-19.
    3. Dannemiller, Katherine A. & Mondal, Aupal & Asmussen, Katherine E. & Bhat, Chandra R., 2021. "Investigating autonomous vehicle impacts on individual activity-travel behavior," Transportation Research Part A: Policy and Practice, Elsevier, vol. 148(C), pages 402-422.
    4. Devon McAslan & Farah Najar Arevalo & David A. King & Thaddeus R. Miller, 2021. "Pilot project purgatory? Assessing automated vehicle pilot projects in U.S. cities," Palgrave Communications, Palgrave Macmillan, vol. 8(1), pages 1-16, December.
    5. Kassens-Noor, Eva & Dake, Dana & Decaminada, Travis & Kotval-K, Zeenat & Qu, Teresa & Wilson, Mark & Pentland, Brian, 2020. "Sociomobility of the 21st century: Autonomous vehicles, planning, and the future city," Transport Policy, Elsevier, vol. 99(C), pages 329-335.
    6. Rounaq Basu & Joseph Ferreira, 2020. "A LUTI microsimulation framework to evaluate long-term impacts of automated mobility on the choice of housing-mobility bundles," Environment and Planning B, , vol. 47(8), pages 1397-1417, October.
    7. Chung, Sai-Ho, 2021. "Applications of smart technologies in logistics and transport: A review," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 153(C).
    8. Jiang, Like & Chen, Haibo & Paschalidis, Evangelos, 2023. "Diffusion of connected and autonomous vehicles concerning mode choice, policy interventions and sustainability impacts: A system dynamics modelling study," Transport Policy, Elsevier, vol. 141(C), pages 274-290.
    9. Guo, Yuntao & Souders, Dustin & Labi, Samuel & Peeta, Srinivas & Benedyk, Irina & Li, Yujie, 2021. "Paving the way for autonomous Vehicles: Understanding autonomous vehicle adoption and vehicle fuel choice under user heterogeneity," Transportation Research Part A: Policy and Practice, Elsevier, vol. 154(C), pages 364-398.
    10. Li, Qing & Liao, Feixiong, 2020. "Incorporating vehicle self-relocations and traveler activity chains in a bi-level model of optimal deployment of shared autonomous vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 140(C), pages 151-175.
    11. Nadafianshahamabadi, Razieh & Tayarani, Mohammad & Rowangould, Gregory, 2021. "A closer look at urban development under the emergence of autonomous vehicles: Traffic, land use and air quality impacts," Journal of Transport Geography, Elsevier, vol. 94(C).
    12. Shamshiripour, Ali & Rahimi, Ehsan & (Kouros) Mohammadian, Abolfazl & Auld, Joshua, 2020. "Investigating the influence of latent lifestyles on productive travels: Insights into designing autonomous transit system," Transportation Research Part A: Policy and Practice, Elsevier, vol. 141(C), pages 469-484.
    13. Mohammed Al-Turki & Nedal T. Ratrout & Syed Masiur Rahman & Imran Reza, 2021. "Impacts of Autonomous Vehicles on Traffic Flow Characteristics under Mixed Traffic Environment: Future Perspectives," Sustainability, MDPI, vol. 13(19), pages 1-22, October.

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