%0 Conference Paper %F Oral %T Traffic Uncertainty in On-Demand High-Capacity Ride-Pooling %+ IRT SystemX %+ Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich) %+ MOIA GmbH %A Hörl, Sebastian %A Zwick, Felix %< avec comité de lecture %Z VWM %B 101st Annual Meeting of the Transportation Research Board (TRB) %C Washington D.C., United States %8 2022-01-09 %D 2022 %K ride-sharing %K on-demand mobility %K MATSim %K simulation %K uncertainty %Z Computer Science [cs]/Modeling and Simulation %Z Engineering Sciences [physics]/Civil Engineering/Infrastructures de transport %Z Physics [physics]/Physics [physics]/Data Analysis, Statistics and Probability [physics.data-an]Conference papers %X On-demand ride-pooling has been studied frequently in recent literature. However, real-world applications of large-scale ride-pooling systems are rare and the breakthrough of comprehensive systems is yet to come. In this study, we simulate a ride-pooling service based on real-world demand data from Hamburg, Germany and evaluate the impact of traffic uncertainty on the system performance using a state-of-the-art ride-pooling algorithm. We propose strategies to remedy customer constraint violations on wait and travel times due to wrongly estimated travel times. We show that uncertainty leads to a trade-off between violating customer constraints and rejecting requests after prior acceptance. %G English %2 https://hal.science/hal-03405574/document %2 https://hal.science/hal-03405574/file/202107_TRB__Traffic_uncertainties_in_on_demand_high_capacity_ride_pooling.pdf %L hal-03405574 %U https://hal.science/hal-03405574 %~ GENIECIVIL %~ TDS-MACS %~ IRT-SYSTEMX