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MaaSSim.md

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tags:: Platform

  • Related
    • [[Simulation]]
  • GitHub: RafalKucharskiPK/
  • MaaSSim
  • Paper: MaaSSim paper.pdf
  • Potential things to study
    • {{embed ((65ad7314-8680-4bf0-b12d-2f5d3ecf19b3))}}
  • Concepts/Tags
    • Platform Profit Maximization
    • Platform Attractiveness for Supply
      • For drivers
    • Platform Attractiveness for Demand
      • For travellers
  • Presentation
    • Key features of a two-sided mobility platform (non-deterministic, adaptive, heterogeneous behaviour of agents interacting with each other) are explicitly handled via userdefined and flexible python functions.
    • Trace emerging complex dynamics.
    • Instead, the explicit objective of MaaSSim is to support researchers with modelling and reproducing the emerging novel phenomena taking place in the context of two-sided mobility platforms and analyse their disruptive potential for urban transport systems.
  • Later TODO
    • Look at the sources 12 - 36
  • Other [[Mobility Simulations]] collapsed:: true
    • 🔸 Team SimPy . [[SimPy]]—discrete event simulation for Python; 2021. Available from: https://pypi.org/ project/simpy/. #simulation id:: 65ad7282-beec-4b7d-b6e0-e4cfe54495d7
    • Maciejewski M, Bischoff J. Large-scale microscopic simulation of taxi services. Procedia Computer Science. 2015; 52:358–364. https://doi.org/10.1016/j.procs.2015.05.107
    • Martinez LM, Correia GH, Viegas JM. An agent-based simulation model to assess the impacts of introducing a shared-taxi system: an application to Lisbon (Portugal). Journal of Advanced Transportation. 2015; 49(3):475–495. https://doi.org/10.1002/atr.1283
    • Dynamic Ride-Sharing: a Simulation Study in Metro Atlanta. collapsed:: true
      • Agatz N, Erera AL, Savelsbergh MWP, Wang X.
      • Procedia—Social and Behavioral Sciences. 2011; 17:532–550. https://doi.org/10.1016/j. sbspro.2011.04.530
    • Stars: Simulating taxi ride sharing at scale. collapsed:: true
    • Agent based model for dynamic ridesharing. collapsed:: true
    • Djavadian S, Chow JY. An agent-based day-to-day adjustment process for modeling ‘Mobility as a Service’with a two-sided flexible transport market. Transportation research part B: methodological. 2017; 104:36–57. https://doi.org/10.1016/j.trb.2017.06.015
    • Nahmias-Biran Bh, Oke JB, Kumar N, Basak K, Araldo A, Seshadri R, et al. From traditional to automated mobility on demand: a comprehensive framework for modeling on-demand services in SimMobility. Transportation Research Record. 2019; 2673(12):15–29. https://doi.org/10.1177/ 0361198119853553
    • Ruch C, Ho¨ rl S, Frazzoli E. Amodeus, a simulation-based testbed for autonomous mobility-on-demand systems. In: 2018 21st International Conference on Intelligent Transportation Systems (ITSC). IEEE; 2018. p. 3639–3644.
    • AxhausenWK, Horni A, Nagel K. The multi-agent transport simulation MATSim. Ubiquity Press; 2016.
    • Adnan M, Pereira FC, Azevedo CML, Basak K, Lovric M, Raveau S, et al. Simmobility: A multi-scale integrated agent-based simulation platform. In: 95th Annual Meeting of the Transportation Research Board Forthcoming in Transportation Research Record; 2016.