Berlin 2018 – wissenschaftliches Programm
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SOE: Fachverband Physik sozio-ökonomischer Systeme
SOE 7: Poster
SOE 7.24: Poster
Montag, 12. März 2018, 17:00–20:00, Poster E
Phase transitions in demand driven public transport systems — •Nils Beyer1, Debsankha Manik1, Andreas Sorge1, and Marc Timme1,2,3 — 1Network Dynamics, Max Planck Institute for Dynamics and Self-Organization, 37077 Goettingen — 2Chair for Network Dynamics, Center for Advancing Electronics (cfaed) and Institute for Theoretical Physics, 01062 Dresden — 3Max Planck Institute for the Physics of Complex Systems, Dresden, 01062
Private cars are a significant source of pollution, energy consumption, congestion, the need for parking space and rising CO2 emissions [1]. Consequently a major challenge of our society in the upcoming decades will be to organize more economic and ecofriendly mobility options. A demand driven public door to door transportation service could be the answer to these problems.
Alonso-Mora et al. developed an algorithm that allows for efficient ride-sharing using only a quarter of the cars currently needed to service New York’s taxi customers in their simulations [2]. The influences on the fraction of rides that can be shared in an urban environment has been analyzed by R.Tachet et al. [3]
To offer this service, one not only needs an efficient algorithm to organize taxis or buses, but also basic knowledge of the scaling in the system, as it should function over a range of temporal demand and different topologies. This work uses a discrete event based simulation framework (d3t) [4] to analyze how detours and customer waiting times scale with the amount of buses and customer requests. We start with simple taxi systems and move on to more sophisticated dispatching policies, including the possibility of ride sharing. The main finding is a second order phase transition in the amount of people who cannot be efficiently served by the system.
[1] OECD/ITF (2017), ITF Transport Outlook 2017, OECD Publishing, Paris. http://dx.doi.org/10.1787/9789282108000-en
[2] Alonso-Mora, Javier, et al. "On-demand high-capacity ride-sharing via dynamic trip-vehicle assignment." Proceedings of the National Academy of Sciences (2017): 201611675.
[3] R.Tachet et al. "Scaling law of urban ride sharing." Scientific reports 7 (2017).
[4] A. Sorge et al. "Towards a unifying framework for demand-driven directed transport (D3T)." (WSC ’15). IEEE Press, Piscataway, NJ, USA, 2800-2811.