Simulation-Based Assessment of Parking Constraints for Automated Mobility on Demand: A Case Study of Zurich
| Autor: | Miloš Balać, Sebastian Hörl, Emilio Frazzoli, Claudio Ruch, Roman Ehrler |
|---|---|
| Přispěvatelé: | Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), Lucerne School of Engineering and Architecture, IRT SystemX (IRT SystemX) |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Operations research
Computer science parking 010501 environmental sciences 01 natural sciences Field (computer science) Set (abstract data type) mobility-on-demand Idle [SPI.GCIV.IT]Engineering Sciences [physics]/Civil Engineering/Infrastructures de transport On demand 11. Sustainability 0502 economics and business TJ1-1570 Mechanical engineering and machinery AMoD TJ227-240 Simulation based Machine design and drawing 0105 earth and related environmental sciences Motor vehicles. Aeronautics. Astronautics 050210 logistics & transportation 05 social sciences Process (computing) operational policy fleet managment TL1-4050 [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation Work (electrical) Minification [PHYS.PHYS.PHYS-DATA-AN]Physics [physics]/Physics [physics]/Data Analysis Statistics and Probability [physics.data-an] Mobility-on-demand Parking Operational policy Fleet managment |
| Zdroj: | Vehicles Volume 3 Issue 2 Pages 17-286 Vehicles, MDPI, 2021, 3 (2), pp.272-286. ⟨10.3390/vehicles3020017⟩ Vehicles, Vol 3, Iss 17, Pp 272-286 (2021) Vehicles, 3 (S 2) |
| ISSN: | 2624-8921 |
| DOI: | 10.3390/vehicles3020017 |
| Popis: | International audience; In a coordinated mobility-on-demand system, a fleet of vehicles is controlled by a central unit and serves transportation requests in an on-demand fashion. An emerging field of research aims at finding the best way to operate these systems given certain targets, e.g., customer service level or the minimization of fleet distance. In this work, we introduce a new element of fleet operation: the assignment of idle vehicles to a limited set of parking spots. We present two different parking operating policies governing this process and then evaluate them individually and together on different parking space distributions. We show that even for a highly restricted number of available parking spaces, the system can perform quite well, even though the total fleet distance is increased by 20% and waiting time by 10%. With only one parking space available per vehicle, the waiting times can be reduced by 30% with 20% increase in total fleet distance. Our findings suggest that increasing the parking capacity beyond one parking space per vehicle does not bring additional benefits. Finally, we also highlight possible directions for future research such as to find the best distribution of parking spaces for a given mobility-on-demand system and city. |
| Databáze: | OpenAIRE |
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