We design a survey-and-scenario-based method for investigating the demand of real people for ride-pooling services in Berlin. We deploy it among public transport users to study where, why, how, and when they would use ride-pooling. In particular, we learn about their socio-demographic features, trip purposes, and deciding factors, as well as their preferences for service waiting times and fares. Our results inform service operators about dispatching decisions, allow for encoding user behavior in utility functions for reasoning, and enable the design of fair pricing schemes to improve service accessibility.
Learning Demands for Ride-pooling Services: A Case Study in Berlin
2024 IEEE Intelligent Vehicles Symposium (IV) ; 2995-3000
02.06.2024
1531050 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Springer Verlag | 2024
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