BPCPPDYSOE21 – wissenschaftliches Programm
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SOE: Fachverband Physik sozio-ökonomischer Systeme
SOE 3: Poster
SOE 3.3: Poster
Montag, 22. März 2021, 17:30–19:30, SOEp
Evaluation of demand responsive ride pooling on real life taxi data — •Michael Sternbach1,2,3, Felix Jung1, Puneet Sharma1,2, Stepahn Herminghaus1,2, and Knut Heidemann1,2 — 1Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany — 2Institut for Dynamics and Complex Systems, University of Göttingen, Germany — 3Campus Institute for Dynamics of Biological Networks, Göttingen, Germany
Climate change caused by human greenhouse gas (GHG) emissions is one of the vital challenges of humankind. Passenger cars contribute significantly to human GHG emissions. To reduce this effect, more eco-friendly transport modes are needed. Demand responsive ride pooling (DRRP) offers door-to-door service similar to taxi or personal car while pooling customers with similar routes on the same vehicle, thereby reducing emissions and the number of cars needed. In this study, we measure the performance of a DRRP system on real life taxi request data and evaluate under which conditions e. g. request rate, number of vehicles, allowed detour or waiting time DRRP can operate more efficiently than taxi service at a reasonable service quality. We compare our results to a mean field description of DRRP [1] to analyze the effect of road network structure and spatial request distribution. Our results provide significant insight on the prerequisites for ecological and economic feasibility of DRRP.
[1] Herminghaus, S. (2019). Mean field theory of demand responsive ride pooling systems. Transportation Research Part A: Policy and Practice, 119, 15-28.