Finding the relevance of staff-based vehicle relocations in one-way carsharing systems through the use of a simulation-based optimization tool

Abstract

To cite this article: Gonçalo Gonçalves Duarte Santos & Gonçalo Homem de Almeida Correia (2019) Finding the relevance of staff-based vehicle relocations in one-way carsharing systems through the use of a simulation-based optimization tool,

Enhanced Mobility With Connectivity and Automation: A Review of Shared Autonomous Vehicle Systems

“…In terms of unbalanced demand distribution, both systems face the same problem of vehicle rebalancing. Two major rebalancing strategies have been investigated in the literature of carsharing with conventional vehicles including (1) operator-based vehicle relocation and (2) user-based vehicle relocation, which could potentially be adapted in addressing the same problem in the SAV system, see [63], [102]- [105]. However, the relocation of SAVs still have differences with that of conventional sharing vehicles, in that the SAVs are fully compliant and always cooperative [106].…”

A mathematical programming model for optimal fleet management of electric car-sharing systems with Vehicle-to-Grid operations

“…According to Jorge et al (2014), real-time relocation operations combined with optimization techniques may significantly increase CSS profits. More recently, Santos and Correia (2019) proposed a carpooling of staff operator strategy for the one-way station-based CSS relocation with extra-cost reduction. Additionally, they state that the high costs of relocations would have more effect on CSSs operator profits only through future vehicle automation.…”

An agent-based model for assessing the financial viability of autonomous mobility on-demand systems used as first and last-mile of public transport trips: A case-study in Rotterdam, the Netherlands

“…However, the existing conventional Mobility-on-Demand (MoD) systems (US Department of Transport, 2020) suffer from multiple operational challenges. The rebalancing problem when vehicles end up clustered at a certain location is one of these challenges (Santos & de Almeida Correia, 2019), (Kek, Cheu, Meng, & Fung, 2009), (Fagnant & Kockelman, 2014), (Lu, Correia, Zhao, Liang, & Lv, 2021), (Jorge, Correia, & Barnhart, 2014). A promising solution to this problem, which is nowadays getting much attention in research, could be the use of automated or autonomous vehicles (AVs) (SAE-level 4 and 5 (SAE International, 2014)).…”