Assessing the impacts of shared autonomous mobility with M 3ICA: A multi-impact, multi-actor, multi-criteria approach

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Abstract

The impacts of connected cooperative autonomous vehicles on society can be significant. We propose a holistic framework that brings together stakeholder abessment with quantitative evaluation of impacts. In this paper, we apply the first part of the framework, and present our findings from a stakeholder workshop within the context of the H2020 SHOW project. 6 groups of stakeholders in the Linköping pilot site participated in a MAMCA workshop and evaluate scenarios of autonomous mobility. Performance scores of each scenario were calculated using the scores and weights assigned to each criteria by their level of importance for each actor group. The findings show a general positive perception of autonomous mobility, with public actors preferring autonomous shared modes, while users and mobility service providers found modes that supported flexible transport to achieve their objectives better.

Original languageEnglish
Title of host publicationTransportation Research Procedia
PublisherElsevier
Pages2317-2322
Number of pages <span style="color:red"p> <font size="1.5"> ✽ </span> </font>6
Volume72
DOIs
Publication statusPublished - 2023
EventTRA - Transport Research Arena Conference Lisbon 2022 - Lisbon Congress Center, Lisbon, Portugal
Duration: 14 Nov 202217 Nov 2022
https://traconference.eu/

Publication series

NameTransportation Research Procedia
PublisherElsevier
ISSN (Print)2352-1457

Conference

ConferenceTRA - Transport Research Arena Conference Lisbon 2022
Abbreviated titleTRA Lisbon 2022
Country/TerritoryPortugal
CityLisbon
Period14/11/2217/11/22
Internet address

Bibliographical note

Publisher Copyright:
© 2023 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0)

Keywords

  • Performance indicators
  • Shared mobility and CCAM
  • Impact assessment framework
  • Multi-actor multi-criteria analysis

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