The rapid development of automated vehicles and the introduction of shared mobility services hold great potential for the development of automated public transport systems. However, their expected performance under alternative conditions and with alternative design factors remains unknown. In this study, the operation of a new automated mobility service was simulated and evaluated. The proposed transport system was defined as an automated demand-responsive transport system (ADRTS), which consisted of a demand-responsive public transportation service providing sharable rides without fixed routes or timetables in automated vehicles. Requests for the ADRTS were combined if they shared the same pickup and drop-off locations, subject to vehicle capacity limitations. Rides were launched within a predefined maximum vehicle dwell time, and routes were chosen without detours. The proposed system was tested in a field operation pilot project of the operation of automated vehicles in Wageningen in the Netherlands under conditions with different demand patterns, vehicle capacities, and operational factors. The simulation model determined the minimal and optimal fleet size for operation of the shuttle service when total operational and travel costs were minimized and maximum passenger waiting time requirements were satisfied. The results indicated that the most effective way to reduce the system cost per passenger of the ADRTS in the presented case study was to increase the demand level, increase the share of passengers who arrive independently, and use adequate vehicle sizes and short vehicle dwell times.
Designing an Automated Demand-Responsive Transport System: Fleet Size and Performance Analysis for a Campus–Train Station Service
Transportation Research Record
Transportation Research Record: Journal of the Transportation Research Board ; 2542 , 1 ; 75-83
2016-01-01
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Designing robust routes for demand-responsive transport systems
Online Contents | 2014
|Designing robust routes for demand-responsive transport systems
Elsevier | 2014
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