Estimation of Environmental Rebound Effect Induced by Shared Automated Passenger Transport Service in a Mid-Size European City via Microsimulation

Ada Garus*, Borja Alonso Oreña, María Alonso Raposo, Andromachi Mourtzouchou, Ruben Cordera Piñera, Carlos Lima Azevedo, Luigi dell’Olio, Ravi Seshadri, Mayara Moraes Monteiro, Biagio Ciuffo

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review


The introduction of autonomous vehicles will revolutionize transport in urban and rural areas. Nevertheless, before we allow autonomous vehicles to roam our streets, we should strive to predict the impact that they could have and prevent as many negative externalities as possible. Moreover, it is expected that the ability to let go of the wheel and multitask could substantially decrease the in-vehicle value of time, triggering travel behavioral changes, which could in turn have a negative impact on the environmental sustainability of the transport system. Thus, we tried to estimate the environmental rebound effect linked to behavioral changes caused by shared autonomous vehicle deployment. This study presents results of a simulation of the transport system of Santander (Spain), performed by linking the activity-based demand estimation developed in SimMobility to microsimulation in Aimsun and its battery consumption and pollutant emissions models. The results yielded by the study present the magnitude to which identified travel behavioral changes could affect the environmental performance of the transport system, as well as the overall outcome of all identified behavioral changes. The outcomes show that the rebound effect could increase the CO2 emissions by almost 40% compared with a scenario with no behavioral changes. We believe this topic to be particularly interesting for policy makers, urban planners and regional authorities.

Original languageEnglish
Book seriesTransportation Research Record
Publication statusAccepted/In press - 2024


  • activity-based modeling
  • air quality and green house gas mitigation
  • connected and automated vehicles
  • transportation and sustainability
  • transportation energy
  • travel demand modeling


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