Pre-design method for advanced public transport systems

Pre-design method for advanced public transport systems

Thanks to vehicle automation, a new generation of urban transport systems that can supply car-like quality of service with Public Transport-like impacts was made possible. They are called Advanced Public Transport Systems and consist of small automated collective vehicles running on demand. A pre-de...

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Bibliographic Details
Published in:Public transport Vol. 2; no. 1-2; pp. 5 - 23
Main Authors: Alessandrini, Adriano, Filippi, Francesco, Stam, Daniele, Tripodi, Antonino
Format: Journal Article
Language:English
Published: Berlin/Heidelberg Springer-Verlag 01-05-2010
Springer Nature B.V
Subjects:
Automation
Automotive Engineering
Business and Management
CAE) and Design
Computer-Aided Engineering (CAD
Design techniques
Operations Research/Decision Theory
Original Paper
Public transportation
Studies
Transportation
Vehicles
Occupancy Rate
Vehicle Capacity
Demand Level
Public Transport System
Average Wait Time
Online Access:Get full text
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Summary:Thanks to vehicle automation, a new generation of urban transport systems that can supply car-like quality of service with Public Transport-like impacts was made possible. They are called Advanced Public Transport Systems and consist of small automated collective vehicles running on demand. A pre-design method for a first dimensioning of such systems was developed by simulating nearly 3 000 scenarios with Dial-A-Ride software and performing statistical regressions on the results. The method needs as input: network length, expected demand, vehicle top speed, maximum waiting time, and vehicle capacity. In six steps the method gives: number of vehicles, average waiting time, vehicle⋅kilometers, commercial speed, occupancy rate, and costs. The regressions are given for 20-place vehicles, 15 km/h top speed, and 1 000 s waiting time CTS. All the R 2 coefficients are higher than 0.75 and in most cases than 0.85. Empirical validations, made by comparing pre-design regressions with other system data, showed that the method gives accurate results.
ISSN:1866-749X
1613-7159
DOI:10.1007/s12469-010-0020-y