If you are late, everyone is late
late passenger arrival and ride-pooling systems' performance
Rafal Kucharski (TU Delft - Transport and Planning)
Andres Fielbaum (TU Delft - Learning & Autonomous Control)
J. Alonso-Mora (TU Delft - Learning & Autonomous Control)
O. Cats (TU Delft - Transport and Planning)
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Abstract
Sharing rides in on-demand systems allow passengers to reduce their fares and service providers to increase revenue, though at the cost of adding uncertainty to the system. Notably, the uncertainty of ride-pooling systems stems not only from travel times but also from unique features of sharing, such as the dependency on other passengers' arrival time at their pick up points. In this work, we theoretically and experimentally analyse how late arrivals at pick up locations impact shared rides' performance. We find that the total delay is equally distributed among sharing passengers. However, delay composition gradually shifts from on-board delay only for the first passenger to waiting delay at the origin for the last passenger. Sadly, trips with more passengers are more adversely impacted. Strategic behaviour analysis reveals Nash equilibria that might emerge. We analyse the system-wide effects and find that when lateness increases passengers refrain from sharing and eventually opt-out.