A preliminary study of the potential impact of autonomous vehicles on residential location in Rome

Carrese, Stefano; Nigro, Marialisa; Patella, Sergio Maria; Toniolo, Eleonora

doi:10.1016/j.retrec.2019.02.005

Cited by 41 publications

(22 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the last simulated scenario, both accessibility to population and jobs and trip times could be significantly degraded in urban areas, which could imply moderate sprawl effects, especially on jobs. However, mobility could be hampered even more in the most peripheral areas, a phenomenon that was also detected by Carrese et al [28] in Rome. This implies that if vehicles were autonomous, and even if they were shared sequentially, their possible negative effects on mobility and accessibility could be felt, especially by the share loss of other transport modes between segments of users who previously had no access to or used cars to a lesser extent, and by the effect of empty journeys between different services.…”

Section: Discussionsupporting

confidence: 52%

“…However, these authors did not find substantial changes in the value of trip time and, therefore, in the capacity of AVs to change residential location patterns. In a similar vein, using data collected with an SP survey, Carrese et al [28] estimated a modal choice model that included the use of private vehicles, carsharing, or ridesharing and a binomial residential choice model between no change of location and changing residential location to the suburbs of the study area (Rome, Italy). These models combined with a transport simulation model allowed to simulate the consequences of various scenarios with different ridesharing penetration.…”

Section: Autonomous Vehicles and Location Of Population And Activitiesmentioning

confidence: 99%

See 1 more Smart Citation

Modeling the Impacts of Autonomous Vehicles on Land Use Using a LUTI Model

et al. 2021

View full text Add to dashboard Cite

Autonomous vehicles (AVs) can generate major changes in urban systems due to their ability to use road infrastructures more efficiently and shorten trip times. However, there is great uncertainty about these effects and about whether the use of these vehicles will continue to be private, in continuity with the current paradigm, or whether they will become shared (carsharing/ridesharing). In order to try to shed light on these matters, the use of a scenario-based methodology and the evaluation of the scenarios using a land use–transport interaction model (LUTI model TRANSPACE) is proposed. This model allows simulating the impacts that changes in the transport system can generate on the location of households and companies oriented to local demand and accessibility conditions. The obtained results allow us to state that, if AVs would generate a significant increase in the capacity of urban and interurban road infrastructures, the impacts on mobility and on the location of activities could be positive, with a decrease in the distances traveled, trip times, and no evidence of significant urban sprawl processes. However, if these increases in capacity are accompanied by a large augment in the demand for shared journeys by new users (young, elderly) or empty journeys, the positive effects could disappear. Thus, this scenario would imply an increase in trip times, reduced accessibilities, and longer average distances traveled, all of which could cause the unwanted effect of expelling activities from the consolidated urban center.

show abstract

Section: Discussionsupporting

confidence: 52%

Section: Autonomous Vehicles and Location Of Population And Activitiesmentioning

confidence: 99%

Modeling the Impacts of Autonomous Vehicles on Land Use Using a LUTI Model

et al. 2021

View full text Add to dashboard Cite

show abstract

“…implemented an agent-based simulation in a scenario where shared AVs are popular, and the results indicated that commuters may relocate to better neighborhoods with the aid of reduced commute costs. Carrese et al (2019) estimated a logit model with a binary indicator of willingness to relocate based on 201 residents in Rome, Italy. After applying the model to predict residential relocation, they implemented traffic assignment with a modified origin-destination matrix and quantified the change in systemwide travel time due to relocation triggered by AVs.…”

Section: Modeling Of Residential Location Choice and Vehicle Ownershipmentioning

confidence: 99%

“…Some studies have started to explore changes in vehicle ownership or residential location (e.g. Carrese et al, 2019;Menon et al, 2019). These societal shifts may produce the greatest implications for future transportation planning/policy.…”

Section: Introductionmentioning

confidence: 99%

Will autonomous vehicles change residential location and vehicle ownership? Glimpses from Georgia

Kim

Circella

2020

Transportation Research Part D: Transport and Environment

View full text Add to dashboard Cite

Many studies have begun investigating possible transportation landscapes in the autonomous vehicle (AV) era, but empirical results on longer-term decisions are limited. We address this gap using data collected from a survey designed and implemented for Georgia residents in 2017-2018. Focusing on a hypothetical all-AV future, this section of the survey included questions regarding advantages/disadvantages of AVs, short-term mode choice impacts, mediumterm impacts on activity patterns, and long-term behavioral changes-specifically, whether/how AVs will influence individuals to change residential location and the number of cars in the household. We hypothesize that AVs could act in concert with attitudinal preferences to stimulate changes in these long-term decisions, and that some medium-term activity changes triggered by AVs could motivate people to relocate their residence or shed household vehicles. We applied exploratory factor analysis to measure the perceived likelihood that AVs would prompt various medium-term changes. We then included some of those measures, among other variables, in a cross-nested logit (CNL) model of the choice of the residential location/vehicle ownership bundle. Although more than half of respondents expected "no change" in their bundle, we found that younger, lower income, pro-suburban, and pro-non-car-mode individuals were more likely to anticipate changing their selections. In addition, some expected medium-term impacts of AVs influenced changes in these longer-term choices. We further applied the CNL model to two population segments (Atlanta and non-Atlanta-region residents). We found notable improvement in goodness of fit and different effects of factors across segments, signifying the existence of geography-related taste heterogeneity.

show abstract

“…Urban sprawl and the relocation of residents to cheaper neighbourhoods is a direct result of car-dependence, a behaviour that may witness further increases if AV private vehicles are readily available in the consumer market [65]. A preliminary study on the potential impact of AVs by Carrese et al [66] was conducted in the city of Rome. The authors found that more than 70% of survey respondents showed interest in relocation to suburban areas based upon the market penetration rate of private AVs.…”

Section: Urbanism and Urban Sprawlmentioning

confidence: 99%

A Review of the Transformation of Road Transport Systems: Are We Ready for the Next Step in Artificially Intelligent Sustainable Transport?

Hasan

Whyte

Jassmi

2019

ASI

View full text Add to dashboard Cite

Mobility is experiencing a revolution, as advanced communications, computers with big data capacities, efficient networks of sensors, and signals, are developing value-added applications such as intelligent spaces and autonomous vehicles. Another new technology that is both promising and might even be pervasive for faster, safer and more environmentally-friendly public transport (PT) is the development of autonomous vehicles (AVs). This study aims to understand the state of the current research on the artificially intelligent transportation system (ITS) and AVs through a critical evaluation of peer-reviewed literature. This study’s findings revealed that the majority of existing research (around 82% of studies) focused on AVs. Results show that AVs can potentially reduce more than 80% of pollutant emissions per mile if powered by alternate energy resources (e.g., natural gas, biofuel, electricity, hydrogen cells, etc.). Not only can private vehicle ownership be cut down by bringing in ridesharing but the average vehicle miles travelled (VMT) should also be reduced through improved PT. The main benefits of AV adoption were reported in the literature to be travel time, traffic congestion, cost and environmental factors. Findings revealed barriers such as technological uncertainties, lack of regulation, unawareness among stakeholders and privacy and security concerns, along with the fact that lack of simulation and empirical modelling data from pilot studies limit the application. AV–PT was also found to be the most sustainable strategy in dense urban areas to shift the heavy trip load from private vehicles.

show abstract

A preliminary study of the potential impact of autonomous vehicles on residential location in Rome

Cited by 41 publications

References 30 publications

Modeling the Impacts of Autonomous Vehicles on Land Use Using a LUTI Model

Modeling the Impacts of Autonomous Vehicles on Land Use Using a LUTI Model

Will autonomous vehicles change residential location and vehicle ownership? Glimpses from Georgia

A Review of the Transformation of Road Transport Systems: Are We Ready for the Next Step in Artificially Intelligent Sustainable Transport?

Contact Info

Product

Resources

About