TY - JOUR
T1 - Estimation of Environmental Rebound Effect Induced by Shared Automated Passenger Transport Service in a Mid-Size European City via Microsimulation
AU - Garus, Ada
AU - Alonso Oreña, Borja
AU - Alonso Raposo, María
AU - Mourtzouchou, Andromachi
AU - Cordera Piñera, Ruben
AU - Lima Azevedo, Carlos
AU - dell’Olio, Luigi
AU - Seshadri, Ravi
AU - Moraes Monteiro, Mayara
AU - Ciuffo, Biagio
N1 - Publisher Copyright:
© National Academy of Sciences: Transportation Research Board 2024.
PY - 2024
Y1 - 2024
N2 - 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.
AB - 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.
KW - Activity-based modeling
KW - Air quality and green house gas mitigation
KW - Connected and automated vehicles
KW - Transportation and sustainability
KW - Transportation energy
KW - Travel demand modeling
U2 - 10.1177/03611981231223752
DO - 10.1177/03611981231223752
M3 - Journal article
AN - SCOPUS:85184234999
SN - 0361-1981
VL - 2678
SP - 966
EP - 978
JO - Transportation Research Record
JF - Transportation Research Record
IS - 8
ER -