PostCorona Shared Mobility

NCN Opus Personal Grant UMO-2020/37/B/HS4/01847

drawing

Modelling and controlling virus spread processes in shared mobility networks 2021-2024, 1mln PLN funded by National Science Centre under scheme OPUS 19

We anticipate substantial changes to post-corona urban mobility, when safety concerns will drive individual, as well as, public decision makers. Travellers’ choices are likely to shift towards modes of low exposure to viruses. Consequently, the sustainable mobility paradigm needs to drift into ’sustainable, yet safe’, unleashing a novel trade-off dilemmas spanned between: cost-comfort-safety for individuals and sustainability-efficiency-safety for policymakers. Outcomes of those decision patterns are likely to disturb landscape of urban mobility. When sustainable mass transit modes start being avoided by risk averse travellers, it may have devastating consequences on performance of transport systems (congestion and traffic delays) and its externalities (emissions, pressure on public space, etc.), which shall be counteracted. Notably, due to recent, disruptive changes in urban mobility, the, so-called, shared mobility (where two or more travellers share the same vehicle to reach the destination), provided via two-sided platforms (like Uber and Lyft), has proven to be an appealing alternative. Whether it will remain attractive solution for emerging mobility problems remains unknown. In particular, it is not known:

a) how travellers willingness-to-share will change;

b) how viruses spread through the shareability graph;

c) how can we redesign shared rides system to control spreading and make sharing rides safe.

This calls for a new set of models, theories and analyses to understand how shared rides can contribute to post-corona urban mobility. To this end, in this project we aim to:

  • WP1:forecast demand for post-corona shared mobility Data-driven travel behaviour modelling. Series of stated preference experiments to estimate the post-corona willingness-to-share among the virus-aware travellers. Predict a presumably non-deterministic, heterogeneous travellers’ reaction to applied measures and virus exposure.

  • WP2: model virus spreading on shared mobility networks Epidemic simulations with stochastic, time evolving contact networks. Reproduce and understand contact networks emerging from shared mobility to better model and predict spreading processes. Analyse structure of underlying network connectivity and identify hubs, communities, size and depth of diffusion trees and giant components.

  • WP3: propose efficient strategies to trace and control it Control, trace and halt spreading with a proactive strategic, tactical and operational system management to make sharing safe again. Demand management to keep system attractive, yet controlling the contact to prevent a future outbreaks.

Two PhD students involved: Michal Bujak and Farnoud Ghasemi

Two PostDocs involved: Olha Shulika and Usman Akhtar

Publications linked to the project

  1. JoTG
    Spatiotemporal variability of ride-pooling potential – Half a year New York City experiment
    Shulika, Olha, Bujak, Michal, Ghasemi, Farnoud, and Kucharski, Rafal
    Journal of Transport Geography 2024
  2. SNAM
    Network structures of urban ride-pooling problems and their properties
    Bujak, Michal, and Kucharski, Rafal
    Social Network Analysis and Mining 2023
  3. arXiv
    Exploring shareability networks of probabilistic ride-pooling problems
    Bujak, Michal, and Kucharski, Rafał
    arXiv preprint arXiv:2206.12259 2022
  4. arXiv
    Modelling the Rise and Fall of Two-Sided Mobility Markets with Microsimulation
    Ghasemi, Farnoud, and Kucharski, Rafał
    arXiv preprint arXiv:2208.02496 2022
  5. SciRep
    Modelling virus spreading in ride-pooling networks
    Kucharski, Rafał, Cats, Oded, and Sienkiewicz, Julian
    Scientific Reports 2021
  6. arXiv
    Ride-pooling service assessment with rational, heterogeneous, non-deterministic travellers
    Bujak, Michal, and Kucharski, Rafal
    arXiv preprint arXiv:2307.10827 2023
  7. arXiv
    Can we start sharing our rides again? The postpandemic ride-pooling market
    Shulika, Olha, and Kucharski, Rafał
    arXiv preprint arXiv:2209.02229 2022
  8. arXiv
    Optimizing Ride-Pooling Revenue: Pricing Strategies and Driver-Traveller Dynamics
    Akhtar, Usman, Ghasemi, Farnoud, and Kucharski, Rafal
    arXiv preprint arXiv:2403.13384 2024
  9. arXiv
    Ride Acceptance Behaviour Investigation of Ride-sourcing Drivers Through Agent-based Simulation
    Ghasemi, Farnoud, Ashkrof, Peyman, and Kucharski, Rafal
    arXiv preprint arXiv:2310.05588 2023
  10. arXiv
    Dynamics of the Ride-Sourcing Market: A Coevolutionary Model of Competition between Two-Sided Mobility Platforms
    Ghasemi, Farnoud, Drabicki, Arkadiusz, and Kucharski, Rafał
    arXiv preprint arXiv:2310.05543 2023
  11. The Implications of Drivers’ Ride Acceptance Decisions on the Operations of Ride-Sourcing Platforms
    Ashkrof, Peyman, Ghasemi, Farnoud, Kucharski, Rafał, Correia, Gonçalo Homem de Almeida, Cats, Oded, and Arem, Bart
    Available at SSRN 4760834
  12. MoMaS: Two-sided Mobility Market Simulation Framework for Modeling Platform Growth Trajectories
    Kucharski, Rafal, and Ghasemi, Farnoud
    2024
  13. Modelling the Rise and Fall of Two-sided Markets
    Ghasemi, Farnoud, and Kucharski, Rafal
    In Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems 2024