Free-floating carsharing is a rapidly growing urban mobility service. It has emerged at commercial scale more recently than traditional ‘round-trip’ carsharing, and at present its growth trajectory ...is steeper. The evidence base regarding its impacts on sustainable transport indicators is, however, less well-developed. This issue is topical for a variety of reasons, including the importance of public policy to the success of this form of carsharing.
The research objective of this study is to establish the early-stage impact of free-floating carsharing on private car ownership. We report findings from a point in time three months following the initiation of a free-floating carsharing service in London (UK). We investigate characteristics of FFCS users that are associated with having one's car ownership impacted, as well as the distinction between deterrence of increased car ownership and sale/disposal of a previously owned private car.
We find that 37% (n=347; 95% confidence interval:±5%) of users indicate that free-floating carsharing has impacted their ownership of private cars. Of this 37%, a large majority (83%) indicated that the mechanism of impact was that they decided not to buy a car that they otherwise would have purchased. 11% reported that they had disposed of a car in the past three months, and 6% stated that they will sell a private car within the next three months.
The average income and education level of users are both higher than for the general population. Within the population of service-users, multivariate analysis demonstrates that, net of confounding effects, heavier (more-frequent) service-users are more likely to indicate impacts on car ownership, and that being highly-educated and higher-income than other users were both (independently) associated with maintaining one's car ownership level. Additional findings are presented that relate car ownership impacts to further demographic characteristics as well as behavioural indicators.
Our findings should be interpreted to pertain to the ‘early adopter’ cohort of FFCS users, and as free-floating carsharing services mature and grow further research will be needed to ascertain how user characteristics, behaviour and impacts are evolving.
•Real booking data of a German free-floating carsharing system is analyzed.•Free-floating carsharing usage concentrates on few Hot Spots.•Weather changes can influence the usage of free-floating ...carsharing.•Cluster analysis of booking data shows imbalances between carsharing demand and supply of vehicles.
Carsharing has become an important addition to existing mobility services over the last years. Today, several different systems are operating in many big cities. For an efficient and economic operation of any carsharing system, the identification of customer demand is essential. This demand is investigated within the presented research by analyzing booking data of a German free-floating carsharing system.
The objectives of this paper are to describe carsharing usage and to identify factors that have an influence on the demand for carsharing. Therefore, the booking data are analyzed for temporal aspects, showing recurring patterns of varying lengths. The spatial distribution of bookings is investigated using a geographic information system and indicates a relationship between city structure and areas with high demand for carsharing. The temporal and spatial facets are then combined by applying a cluster analysis to identify groups of days with similar spatial booking patterns and show asymmetries in the spatiotemporal distribution of vehicle supply and demand.
Influences on demand can be either short-term or long-term. The paper shows that changes in the weather conditions are a short-term influence as users of free-floating carsharing react to those. Furthermore, the application of a linear regression analysis reveals that socio-demographic data are suitable for making long-term demand predictions since booking numbers show quite a strong correlation with socio-demography, even in a simple model.
•A detailed description of a new problem emerging in carsharing systems.•A novel mathematical model for the problem of charging and repositioning electric vehicles in a free-floating carsharing ...system.•A Hybrid Genetic Search with Adaptive Diversity Control algorithm (HGSADC) capable of solving instances of size compatible with real-life problems.•Results showing the effectiveness of the proposed algorithm and that combining charging and repositioning yields advantages.
Carsharing has received increased attention from the Operations Research community in recent years. Currently, many systems are adopting electric vehicles that require charging when battery levels fall below a given level. To do this, staff is often used to move cars to charging stations. Repositioning cars, rather than simply moving them to the closest charging station, might provide a better distribution of cars and in turn generate increased revenue and customer service while only marginally increase the operational costs. We present a mathematical model for the problem of charging and repositioning a fleet of shared electric cars. The model considers the assignment of cars to charging stations and the routing of staff and service vehicles. The complexity of the resulting mixed integer program makes it impossible to solve real world instances using a commercial solver. Therefore, we propose a new Hybrid Genetic Search with Adaptive Diversity Control algorithm. Tests based on data from a real life carsharing organization demonstrate that the proposed method can handle real size instances and that combining repositioning and charging operations can give significant benefits.
Autonomous vehicles are expected to disrupt mobility but face consumer reluctance. Diffused through carsharing services, the technology could become more accessible and overcome initial skepticism. ...Consequently, carsharing with shared autonomous vehicles (SAVs) can provide the combined benefits of autonomous driving technology and access-based consumption. Whereas first investigations into the topic provide projections in adoption preferences and first impacts, the literature lacks a holistic understanding of drivers, barriers, and future developments in carsharing with SAVs over the next ten years. We conducted a four-stage exploratory Delphi-study with 40 international experts to elicit these factors. Key findings include the strong perception of technological aspects, consumer acceptance considerations, and legislative concerns. Remarkably, the factors of sustainability and ethics were perceived as secondary. We conclude our paper with implications and recommendations for managers, policy makers, and future academic research.
•A four-stage Delphi study with 40 international experts involved in novel mobility services.•Examination of drivers, inhibitors and future developments of carsharing with shared autonomous vehicles•Technology, encompassing functionality and convenience, considered most important•Economic drivers, including demand and supply factors, received high ratings.•Sustainability and ethics were considered of minor importance.
•We compile a database of about 800 UAM, EV, and AV articles.•We use insights from the EV and AV literature to inform future UAM research directions.•UAM research has primarily focused on aircraft ...technologies and operations.•EV and AV research has a greater emphasis on technology adoption and integration with existing infrastructure.•To date, the majority of UAM research has been conducted by U.S. researchers.
Urban air mobility (UAM), if successful, will disrupt urban transportation. UAM is not the first disruptive technology in transportation, with recent examples including electric ground vehicles (EVs), autonomous ground vehicles (AVs), and sharing services. In this paper, we conduct a meta-analysis of about 800 articles in the UAM, EV, and AV areas that have been published from January 2015 to June 2020, and compare and contrast research thrusts in order to inform future UAM research. Alongside this effort, we conduct an in-depth review of articles related to demand modeling, operations, and integration with existing infrastructure. We use insights from the meta-analysis and comprehensive review to inform future UAM research directions. Some of the potential research directions we identify include: (1) developing more refined demand models that incorporate the timing of when individuals will adopt UAM; (2) developing high-fidelity simulation models for UAM operations that capture interactions among vertiport locations, vertiport topology, demand, pricing, dispatching, and airspace restrictions; (3) explicitly considering one-way demand and parking constraints in demand and operational models; and (4) developing more realistic time-of-day energy profiles for UAM vehicles in order to assess whether the current electrical grid can support UAM operations.
Carsharing services have been introduced as new mobility options in metropolitan areas worldwide. In order for the new mobility option to operate successfully and attract sufficient demand to sustain ...service, it is imperative to understand where carsharing stations should be located and what factors are important for bolstering demand. To provide insights for this understanding, this study attempts to identify factors that influence carsharing operators’ selection of carsharing station locations and demand based on one-month rental transaction data in Seoul, South Korea. Identification is conducted by relating location selection and demand to underlying characteristics of specific census blocks in which reported carsharing stations are located. Comparative analyses are also conducted by segmenting the transaction data into subsets: 1) workday and non-workday rentals and 2) rentals made by age groups of members in their 20s–30s and 40s and older. To correct the selection bias (carsharing rentals are observed only where carsharing stations are located), Heckman selection models are applied to jointly explain the selection of station locations and demand. The estimated models suggest that the supply level of public transit service is positively related to both location selection for carsharing stations and demand. Meanwhile, population density is negatively associated with both selection and demand. A rather weak association between carsharing station location and demand by members in their 40s and older are found, suggesting that carsharing operators mainly target young users when selecting carsharing service locations.
•We explore factors affecting carsharing demand and station location.•Census block level models are developed using carsharing transaction data.•Heckman selection models are applied to correct station location selection biases.•Carsharing demand varies depending on users’ age and day of week.•Public transit is the most important factor for both station location and demand.
•The choice between regular vehicles, PAVs and SAVs is modelled.•Five latent variables describe the individuals’ attitudes.•Large hesitations towards autonomous vehicle adoption currently ...exist.•Early AV adopters will likely be young, students, more educated, and spend more time in vehicles.
This study gains insight into individual motivations for choosing to own and use autonomous vehicles and develops a model for autonomous vehicle long-term choice decisions. A stated preference questionnaire is distributed to 721 individuals living across Israel and North America. Based on the characteristics of their current commutes, individuals are presented with various scenarios and asked to choose the car they would use for their commute. A vehicle choice model which includes three options is estimated:(1)Continue to commute using a regular car that you have in your possession.(2)Buy and shift to commuting using a privately-owned autonomous vehicle (PAV).(3)Shift to using a shared-autonomous vehicle (SAV), from a fleet of on-demand cars for your commute.A factor analysis determined five relevant latent variables describing the individuals’ attitudes: technology interest, environmental concern, enjoy driving, public transit attitude, and pro-AV sentiments. The effects that the characteristics of the individual and the autonomous vehicle have on use and acceptance are quantified through random utility models including logit kernel model taking into account panel effects.
Currently, large overall hesitations towards autonomous vehicle adoption exist, with 44% of choice decisions remaining regular vehicles. Early AV adopters will likely be young, students, more educated, and spend more time in vehicles. Even if the SAV service were to be completely free, only 75% of individuals would currently be willing to use SAVs. The study also found various differences regarding the preferences of individuals in Israel and North America, namely that Israelis are overall more likely to shift to autonomous vehicles.
Methods to encourage SAV use include increasing the costs for regular cars as well as educating the public about the benefits of shared autonomous vehicles.
Carsharing programs-subscription-based car rentals-allow users to purchase only the automobility that they need. These programs may benefit low-income travelers by increasing access at lower prices ...than private auto ownership. Most carshare programs, however, disproportionately serve higher-income drivers. To assess carsharing's potential to address the accessibility needs of disadvantaged households, we interviewed members of BlueLA, an electric carsharing program in central Los Angeles (CA) that offers both subsidized and regular memberships. We found few differences in how travelers with different membership types used BlueLA. They both used the service to complement travel by other modes like public transit and ridehail. In addition, members cited the benefits of gaining car access without the financial burden of car ownership or the unpredictability of ridehail fares. Neighborhood context, including residential density and the availability of non-automobile transportation options, also increased BlueLA's appeal. However, due to limited and unreliable vehicle availability, most users did not rely on BlueLA for time-sensitive trips. BlueLA both eased and increased access to destinations outside of the commute and complemented public transit for subsidized and regular members.
Services like BlueLA cannot meet all transportation needs. However, subsidized electric carsharing-particularly targeted to central-city neighborhoods-may address some accessibility needs of low-income households without imposing the burdens of automobile ownership.
Abstract
This paper provides insights into differences in carsharing users' attitudes, motives for joining carsharing, and transport behaviour between users with and without another car at their ...disposal. It builds on revealed and stated data about members of the oldest carsharing company in the Czech Republic. Carsharing adopters without a car utilise shared cars more intensively than carsharing users with a car available in their household. On the other hand, unlike the second group, they drive fewer kilometres by car in total. The car availability in households also influences the shift in car use after joining carsharing. The sale of a car thanks to adopting carsharing is a factor leading to a decrease in overall car use. Those who have a car at their disposal within their household have a lower probability of decreasing kilometres driven after joining carsharing. Households without an additional car available seem to be less car-dependent on average than those utilising carsharing as a second or third car. They tend to be more environmentally conscious and more inclined towards policies supporting alternative modes and restricting private car use, although both groups share these beliefs. The findings open a debate over whether carsharing increases the legitimacy of restrictive transport measures against private car ownership and use.
The problems related to traffic emissions are becoming increasingly pressing and serious, especially in big cities where the private car plays the main role in the mobility of people, being ...excessively used, while walking, cycling and the use of public transport are often seen as secondary options and are hampered by a poorly urban environment. Therefore, solutions must be found to reduce the number of cars circulating in the city and to support the most sustainable modes of transport at the same time, in order to reduce emissions of greenhouse gases and harmful substances. A modal alternative which is of undoubted interest could be represented by carsharing, which is a mode complementary to public transport, often involves walking or cycling and causes a reduction in private cars and kilometers travelled. This paper aims to estimate, therefore, the environmental benefits related to carsharing, using the COPERT methodology, developed within the European project CORINAIR for the estimation of road-transport related pollutant emissions. As a case study, the carsharing service in the city of Palermo has been chosen, where pollution and congestion caused by the excessive use of car are fundamental problems that the administration has to solve. The research has shown that there are benefits deriving from the use of carsharing in terms of reducing emissions of pollutants: there is a reduction of 25% for PM10 and of 38% for CO2. However, these benefits are limited compared to the emissions of the registered fleet circulating in Palermo.
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