Optimizing Ride-Pooling Revenue: Pricing Strategies and Driver-Traveller Dynamics
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arXiv
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| Autores principales: | , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Acceso en línea: | |
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| _version_ | 1866917618396430336 |
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| author | Akhtar, Usman Ghasemi, Farnoud Kucharski, Rafal |
| author_facet | Akhtar, Usman Ghasemi, Farnoud Kucharski, Rafal |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_13384 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Optimizing Ride-Pooling Revenue: Pricing Strategies and Driver-Traveller Dynamics Akhtar, Usman Ghasemi, Farnoud Kucharski, Rafal Multiagent Systems cs.MA 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. |
| title | Optimizing Ride-Pooling Revenue: Pricing Strategies and Driver-Traveller Dynamics |
| topic | Multiagent Systems cs.MA |
| url | https://arxiv.org/abs/2403.13384 |