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Spatial, Social and Data Gaps in On-Demand Mobility Services: Towards a Supply-Oriented MaaS

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  • Ronit Purian
  • Daniel Polani

Abstract

After a decade of on-demand mobility services that change spatial behaviors in metropolitan areas, the Shared Autonomous Vehicle (SAV) service is expected to increase traffic congestion and unequal access to transport services. A paradigm of scheduled supply that is aware of demand but not on-demand is proposed, introducing coordination and social and behavioral understanding, urban cognition and empowerment of agents, into a novel informational framework. Daily routines and other patterns of spatial behaviors outline a fundamental demand layer in a supply-oriented paradigm that captures urban dynamics and spatial-temporal behaviors, mostly in groups. Rather than real-time requests and instant responses that reward unplanned actions, and beyond just reservation of travels in timetables, the intention is to capture mobility flows in scheduled travels along the day considering time of day, places, passengers etc. Regulating goal-directed behaviors and caring for service resources and the overall system welfare is proposed to minimize uncertainty, considering the capacity of mobility interactions to hold value, i.e., Motility as a Service (MaaS). The principal-agent problem in the smart city is a problem of collective action among service providers and users that create expectations based on previous actions and reactions in mutual systems. Planned behavior that accounts for service coordination is expected to stabilize excessive rides and traffic load, and to induce a cognitive gain, thus balancing information load and facilitating cognitive effort.

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  • Ronit Purian & Daniel Polani, 2023. "Spatial, Social and Data Gaps in On-Demand Mobility Services: Towards a Supply-Oriented MaaS," Papers 2303.03881, arXiv.org.
    • Handle: RePEc:arx:papers:2303.03881
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    2. Hall, Jonathan D. & Palsson, Craig & Price, Joseph, 2018. "Is Uber a substitute or complement for public transit?," Journal of Urban Economics, Elsevier, vol. 108(C), pages 36-50.
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