Optimizing Ride-Pooling Revenue: Pricing Strategies and Driver-Traveller Dynamics
CoRR(2024)
Abstract
Ride-pooling, to gain momentum, needs to be attractive for all the parties
involved. This includes also drivers, who are naturally reluctant to serve
pooled rides. This can be controlled by the platform's pricing strategy, which
can stimulate drivers to serve pooled rides. Here, we propose an agent-based
framework, where drivers serve rides that maximise their utility. We simulate a
series of scenarios in Delft and compare three strategies. Our results show
that drivers, when they maximize their profits, earn more than in both the
solo-rides and only-pooled rides scenarios. This shows that serving pooled
rides can be beneficial as well for drivers, yet typically not all pooled rides
are attractive for drivers. The proposed framework may be further applied to
propose discriminative pricing in which the full potential of ride-pooling is
exploited, with benefits for the platform, travellers, and (which is novel
here) to the drivers.
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