Seminar über aktuelle Fragen zur Dynamik komplexer Fluide: Evaluation of Real Life Taxi Data regarding Demand Responsive Ride Pooling
Seminar über aktuelle Fragen zur Dynamik komplexer Fluide
- Datum: 15.11.2019
- Uhrzeit: 10:15 - 11:15
- Vortragende(r): Michael Sternbach
- MPI-DS
- Ort: Max-Planck-Institut für Dynamik und Selbstorganisation (MPIDS)
- Raum: SR 0.77
- Gastgeber: DCF
- Kontakt: stephan.herminghaus@ds.mpg.de
Demand-responsive ride pooling (DRRP) is a transportation service which offers the door-to-door service like taxis while transporting more than customers at the same time, similar a bus. Simulations with real-world taxi data show that DRRP can serve taxi customers more efficiently than regular taxis with just minor decrease of service quality. The efficiency of the DRRP system can be described as the ratio of mean passengers per vehicle to the mean detour of passengers. To efficiently operate a DRRP system the number of deployed vehicles and the detour they are allowed to take needs to be adapted to the customer environment.
The mean passenger number per vehicle can be calculated as the ratio of vehicles in operation and the average number of customers served by the system at the same time. The latter is a function of the mean detour of the customers and the ratio of served customers which both are functions of the number of deployed vehicles. For high numbers of vehicles, the mean detour of the customers and the ratio of served customers become constant.
An upper limit for the detour of the customers can be calculated from the mean field theory by [1] (MFT) as function of the mean number of passengers who simultaneously occupy one vehicle. If the waiting time of customers is unlimited and the influence of empty vehicles is minor, the MFT can predict the mean waiting time of the customers.
[1] Herminghaus, S. (2019). Mean field theory of demand responsive ride pooling systems. Transportation Research Part A: Policy and Practice, 119, 15-28.
The mean passenger number per vehicle can be calculated as the ratio of vehicles in operation and the average number of customers served by the system at the same time. The latter is a function of the mean detour of the customers and the ratio of served customers which both are functions of the number of deployed vehicles. For high numbers of vehicles, the mean detour of the customers and the ratio of served customers become constant.
An upper limit for the detour of the customers can be calculated from the mean field theory by [1] (MFT) as function of the mean number of passengers who simultaneously occupy one vehicle. If the waiting time of customers is unlimited and the influence of empty vehicles is minor, the MFT can predict the mean waiting time of the customers.
[1] Herminghaus, S. (2019). Mean field theory of demand responsive ride pooling systems. Transportation Research Part A: Policy and Practice, 119, 15-28.