Estamos realizando la búsqueda. Por favor, espere...

Modal choice for the driverless city: scenario simulation based on a stated preference survey

Abstract: The possible future introduction of Autonomous Vehicles (AVs) and Shared Autonomous Vehicles (SAVs) raises questions about how they might affect the demand for transport and especially modal choice. In this research, a stated preference (SP) survey and a modelling process using Mixed Logit are proposed to simulate the future market share of AVs/SAVs and how their introduction into the system could change the modal choice, especially in relation to active and public transport modes. An efficient SP survey design has been developed based on the state-of-the-art information and carried out in 2020 among citizens of two medium-sized Southern European cities within a car-intensive region. The design considered different trip purposes (compulsory, leisure), different trip distances, and attributes not taken into account before, such as comfort and the physical characteristics of the terrain for the active modes. The model results suggest that AVs and SAVs were the preferred transport modes for most respondents, accounting for more than 58% of the market share in the scenarios presented. Also, we detected some socioeconomic differences in the propensity to use this mode of transport showing that men living in high-income households and car users were more prone to use autonomous alternatives. The models allowed us to simulate different scenarios, such as experiencing higher costs for using the AV alternative. Policies imposing a higher cost for the AV alternative but lower costs and waiting times for the SAV and public transport alternatives could decrease the AV?s market share favouring more sustainable modes. The above scenario showed that achieving a more sustainable future mobility system considering AVs requires an in-depth transport demand knowledge and adequate transport policies.

 Autoría: Cordera R., González-González E., Nogués S., Arellana J., Moura J.L.,

 Fuente: Journal of Advanced Transportation, 2022, 1108272

 Editorial: Institute for Transportation

 Fecha de publicación: 07/06/2022

 Nº de páginas: 12

 Tipo de publicación: Artículo de Revista

 DOI: 10.1155/2022/1108272

 ISSN: 0197-6729,2042-3195

 Proyecto español: PID2019-110355RB-I00