Volatility of car ownership, commuting mode and time in the UK

This paper has two objectives: to examine the volatility of travel behaviour over time and consider the factors explaining this volatility; and to estimate the factors determining car ownership and commuting by car. The analysis is based on observations of individuals and households over a period of up to 11 years obtained from the British Household Panel Survey (BHPS). Changes in car ownership, commuting mode and commuting time over a period of years for the same individuals/households are examined to determine the extent to which these change from year-to-year. This volatility of individual behaviour is a measure of the ease of change or adaptation. If behaviour changes easily, policy measures are likely to have a stronger and more rapid effect than if there is more resistance to change. The changes are “explained” in terms of factors such as moving house, changing job and employment status. The factors determining car ownership and commuting by car are analysed using a dynamic panel-data models.     

The effect of prices and income on car travel in the UK

The objective of this paper is to analyse the factors determining household car travel, and specifically the effects of household income and the prices of cars and motor fuels, and to explore the intertemporal pattern of adjustment. The question of asymmetry in the response to rising and falling income is also addressed. Such asymmetry may be caused by habit or resistance to change or the tendency to acquire habits to consume more easily than to abandon them. The impact of prices, the speed of adjustment and the resistance to change will be important in determining the possibility of influencing travel behaviour and specifically car use. The study utilises repeated cross-section data from the annual UK Family Expenditure Surveys and employs a pseudo-panel methodology. The results are compared with those for car ownership estimated on the basis of similar models.     

The influence of individuals’ environmental attitudes and urban design features on their travel patterns in sustainable neighborhoods in the UK

This paper explores the influence of individuals’ environmental attitudes and urban design features on travel behavior, including mode choice. It uses data from residents of 13 new neighborhood UK developments designed to support sustainable travel. It is found that almost all respondents were concerned about environmental issues, but their views did not necessarily ‘match’ their travel behavior. Individuals’ environmental concerns only had a strong relationship with walking within and near their neighborhood, but not with cycling or public transport use. Residents’ car availability reduced public transport trips, walking and cycling. The influence of urban design features on travel behaviors was mixed, higher incidences of walking in denser, mixed and more permeable developments were not found and nor did residents own fewer cars than the population as a whole. Residents did, however, make more sustainable commuting trips than the population in general. Sustainable modes of travel were related to urban design features including secured bike storage, high connectivity of the neighborhoods to the nearby area, natural surveillance, high quality public realm and traffic calming. Likewise the provision of facilities within and nearby the development encouraged high levels of walking.     

Joint analysis of the spatial impacts of built environment on car ownership and travel mode choice

Concerns over transportation energy consumption and emissions have prompted more studies into the impacts of built environment on driving-related behavior, especially on car ownership and travel mode choice. This study contributes to examine the impacts of the built environment on commuter’s driving behavior at both spatial zone and individual levels. The aim of this study is threefold. First, a multilevel integrated multinomial logit (MNL) and structural equation model (SEM) approach was employed to jointly explore the impacts of the built environment on car ownership and travel mode choice. Second, the spatial context in which individuals make the travel decisions was accommodated, and spatial heterogeneities of car ownership and travel mode choice across traffic analysis zones (TAZs) were recognized. Third, the indirect effects of the built environment on travel mode choice through the mediating variable car ownership were calculated, in other words, the intermediary nature of car ownership was considered. Using the Washington metropolitan area as the study case, the built environment measures were calculated for each TAZ, and the commuting trips were drawn from the household travel survey in this area. To estimate the model parameters, the robust maximum likelihood (MLR) method was used. Meanwhile, a comparison among different model structures was conducted. The model results suggest that application of the multilevel integrated MNL and SEM approach obtains significant improvements over other models. This study give transportation planners a better understanding on how the built environment influences car ownership and commuting mode choice, and consequently develop effective and targeted countermeasures.     

An investigation into the feasibility of increasing rail use as an alternative to the car

With rail travel largely seen to be a more sustainable method than road-based transport, this paper examines the market segments amongst existing motorists that would be most likely to travel by train in the UK. The analysis is based on a large survey in London and the south-east of England, the area surrounding the routes operated by the train company First Capital Connect. Findings show that train travellers tend to be middle-aged and of a higher social grade, typically taking commuting or business trips. Individuals living within four miles of a station are considerably more likely to travel by rail than those further away. Given the competition from road-based transport, it is of particular interest that the measure highlighted to increase rail use for those living further away from the rail network is to enhance car parking at train stations.     

Estimating the environmental benefits of ride-sharing: A case study of Dublin

Ride-sharing has often been cited as a successful method to reduce congestion and green house gas emissions. This paper examines the patterns of ride-sharing, in Dublin, and estimates the environmental benefits of ride-sharing both in terms of reductions in emissions and the vehicle kilometres travelled. Data from the 2006 Census of Ireland is used to examine the travel patterns of those that ride-share. The COPERT4 model is used in this paper to estimate the CO₂ emissions saved by ride-sharing.     

Understanding engagement and disengagement from pro-environmental behaviour: The role of neutralization and affirmation techniques in maintaining persistence in and desistance from car use

Despite mounting evidence that car use is a prime culprit of global warming, our love affair with the car persists. General awareness of the environmental consequences of car usage is high but fails to correspond to moderated car use. This paper contributes to an understanding of how university students’ environmental beliefs affect decisions to engage in continued car use (persistence) and/or to discontinue or reduce car use (desistance). The aim of the research presented here was to explore the range of neutralizations and counter-neutralizations (affirmations) employed by students and to examine the ways in which they are used to justify and maintain either persistence or desistance in car use. The research consisted of six focus group sessions with thirty-four UK-based Higher Education students. Analysis of the study’s data highlights the range of neutralizations and counter-neutralizations employed by students in social settings. The article discusses the usefulness of neutralization theory in accounting for actual and/or intended non-environmentally friendly behaviour such as car use. In addition, the study’s findings are discussed in relation to prior research and to potential implications for public policy interventions which favour moderating car usage.     

From e-bike to car: A study on factors influencing motorization of e-bike users across China

Household car ownership has risen dramatically in China over the past decade. At the same time a disruptive transportation technology emerged, the electric bike (e-bike). Most studies investigating motorization in China focus on macro-level economic indicators like GDP, with few focusing on household, city-level, environmental, or geographic indicators, and none in the context of high e-bike ownership. This study examines household vehicle purchase decisions across 59 cities in China with broad geographic, environmental, and socio-economic characteristics. We focus on a subset of households who own e-bikes and rely on a telephone survey from an industry customer database. From these responses, we estimate two three-level hierarchical choice models to assess attributes that contribute to (1) recent car purchases and (2) the intention to buy a car in the near future. The results show that the models are dominated by household characteristics including household income, household size, household vehicle ownership, number of licensed drivers and duration of car ownership. Some geographic, environmental and socio-economic factors have significant influences on car purchase decisions. Only two city-level transportation variable have an effect – higher taxi density and higher bus density reducing car purchase. Cold weather, population density gross domestic product per capita positively influence car purchase, while urbanization rate reduces car purchase. Because of supply heterogeneity in the data set, described by publicly available urban transportation data, this is the first study that can include geographic and urban infrastructure differences that influence purchase choice and suggests potential region-specific policy approaches to managing car purchase may be necessary.     

Gauging interventions for sustainable travel: A comparative study of travel attitudes in Berlin and London

So-called ‘soft’ policy instruments that respond to the psychological aspects of travel are regularly acknowledged as necessary complements to ‘hard’ infrastructure investments to effectively promote sustainable travel in cities. While studies investigating subjective orientations among travellers have proliferated, open questions remain including the role of recent technological advances, the expansion of alternative mobility services, locally specific mobility cultures and residential selection. This paper presents the methods, results and policy implications of a comparative study aiming to understand mobility attitudes and behaviours in the wider metropolitan regions of Berlin and London. We specifically considered information and communication technology (ICT), new types of mobility services such as car sharing, electric cars and residential preferences. In each region, we identified six comparable segments with distinct attitudinal profiles, socio-demographic properties and behavioural patterns. Geocoding of the home address of respondents further revealed varying contextual opportunities and constraints that are likely to influence travel attitudes. We find that there is significant potential for uptake of sustainable travel practices in both metropolitan regions, if policy interventions are designed and targeted in accordance with group-specific needs and preferences and respond to local conditions of mobility culture. We identify such interventions for each segment and region and conclude that comparative assessment of attitudinal, alongside geographical, characteristics of metropolitan travellers can provide better strategic input for realistic scenario-building and ex-ante assessment of sustainable transport policy.     

Dynamic ride sharing using traditional taxis and shared autonomous taxis: A case study of NYC

This study analyzes the potential benefits and drawbacks of taxi sharing using agent-based modeling. New York City (NYC) taxis are examined as a case study to evaluate the advantages and disadvantages of ride sharing using both traditional taxis (with shifts) and shared autonomous taxis. Compared to existing studies analyzing ride sharing using NYC taxi data, our contributions are that (1) we proposed a model that incorporates individual heterogeneous preferences; (2) we compared traditional taxis to autonomous taxis; and (3) we examined the spatial change of service coverage due to ride sharing. Our results show that switching from traditional taxis to shared autonomous taxis can potentially reduce the fleet size by 59% while maintaining the service level and without significant increase in wait time for the riders. The benefit of ride sharing is significant with increased occupancy rate (from 1.2 to 3), decreased total travel distance (up to 55%), and reduced carbon emissions (up to 866 metric tonnes per day). Dynamic ride sharing, wich allows shared trips to be formed among many groups of riders, up to the taxi capacity, increases system flexibility. Constraining the sharing to be only between two groups limits the sharing participation to be at the 50–75% level. However, the reduced fleet from ride sharing and autonomous driving may cause taxis to focus on areas of higher demands and lower the service levels in the suburban regions of the city.     

Car sharing in Norwegian urban areas: Examining interest,intention and the decision to enrol

This article’s objective is to investigate the effects of sociodemographic and residential built environments, directly and indirectly through personality traits, attitudes and car ownership, on willingness to use car sharing in the case of Norway. This is done by examining multiple dimensions of the adoption process: the stated general interest and intention to participate in car sharing among non-members, as well as the decision to enrol as a car sharing user by comparing members to non-members. In this study, we analyse web survey data from 2414 residents from urban areas in Norway, using three structural equation models. Our findings indicate that the adoption of car sharing is complexly related to car ownership, with a noteworthy discrepancy indicating greater car sharing interest, but lower car sharing membership rates among car owners. We also find that environmental concerns exert a clear positive effect on all three dimensions of the adoption process. Being careful with money is linked negatively to interest and intention to participate, while being sociable and agreeable exerts no effect. Car sharers’ sociodemographic profiles are typically that of early adopters, but many of the effects, especially on interest, are mediated by car ownership, environmental consciousness and/or being careful with money, rather than directly on the sociodemographic profiles. Finally, we find car sharing to be more prominent in denser areas, but we did not discover a clear connection with access to public transport.     

Uncertain benefits: Application of Bayesian melding to the Alaskan Way Viaduct in Seattle

Uncertainty is inherent in major infrastructure projects, but public decision-making for such projects ignores it. We investigate the uncertainty about the future effects of tearing down the Alaskan Way Viaduct in downtown Seattle, using an integrated model of housing, jobs, land use and transportation, on outcomes including average commute times. Our methodology combines the urban simulation model UrbanSim with the regional transportation model. We assess uncertainty using Bayesian melding, yielding a full predictive distribution of average commute times on 22 different routes in 2020. Of these routes, 14 do not include the viaduct and eight do. For the 14 base routes that do not include the viaduct, the predictive distributions overlap substantially, and so there is no indication that removing the viaduct would increase commute times for these routes. For each of the eight routes that do include the viaduct, the 95% predictive interval for the difference in average travel times between the two scenarios includes zero, so there is not strong statistical support for the conclusion that removing the viaduct would lead to any increase in travel times. However, the median predicted increase is positive for each of these routes, with an average of 6 min, suggesting that there may be some measurable increase in travel time for drivers that use the viaduct as a core component of their commute.     

Vehicle sharing system with fleet sizing and multi-transportation modes under allowable shortages: a hybrid metaheuristic approach

In this paper, a vehicle sharing system with multi-transportation modes and allowable shortage is presented. This model aims to minimize the system's total cost by using optimum locations and number of stations, routes, transportation modes, station capacities for different modes and time between stations balancing. Because of the model's complexity, currently available proprietary software is not able to solve the model in a reasonable computational time, so a hybrid algorithm based on a genetic algorithm (GA) and particle swarm optimization is presented. The results confirm its efficiency compared with the classic GA and exact solution methods. Moreover, a sensitivity analysis shows the applicability of the proposed algorithm.     

The determinants of car ownership in England and Wales from anonymous 2001 census data

Within the transportation research literature, the attempt to understand and predict the level of car ownership is probably one of the most popular areas of study. The primary reason for this is understandable, having access to a vehicle increases an individual’s (or their household’s) travel options, leading to greater mobility. Secondary reasons for this scrutiny include the need to predict future transport investment in road infrastructure and the commercial demand for new vehicles. This paper attempts to predict the level of household car ownership as a function of the characteristics of the household and the individuals that make up the household. The primary data source for this study comes from the 2001 United Kingdom Census and the analysis methods used are from the discipline of data mining. The results of this study are in line with those from previous research but show a potential to predict the higher levels of household car ownership with greater accuracy than other similar studies.     

Use of ecological footprinting to explore alternative transport policy scenarios in an Irish city-region

The objective of this paper is to compare the ecological footprint for travel-commuting patterns for the residents of an Irish city-region, that is Limerick city-region, in 1996 and 2002. Scenario building, based on ecological footprint analysis, is used to estimate the impact of different policy choices for 2010. The optimal policy mix for sustainable travel is proposed and consists of a mix of reduced demand through travel demand measures, better spatial planning and technological improvements in fuel economy.     

A choice experiment on alternative fuel vehicle preferences of private car owners in the Netherlands

This paper presents results of an online stated choice experiment on preferences of Dutch private car owners for alternative fuel vehicles (AFVs) and their characteristics. Results show that negative preferences for alternative fuel vehicles are large, especially for the electric and fuel cell car, mostly as a result of their limited driving range and considerable refueling times. Preference for AFVs increases considerably with improvements on driving range, refueling time and fuel availability. Negative AFV preferences remain, however, also with substantial improvements in AFV characteristics; the remaining willingness to accept is on average € 10,000–€ 20,000 per AFV. Results from a mixed logit model show that consumer preferences for AFVs and AFV characteristics are heterogeneous to a large extent, in particular for the electric car, additional detour time and fuel time for the electric and fuel cell car. An interaction model reveals that annual mileage is by far the most important factor that determines heterogeneity in preferences for the electric and fuel cell car. When annual mileage increases, the preference for electric and fuel cell cars decreases substantially, whilst the willingness to pay for driving range increases substantially. Other variables such as using the car for holidays abroad and the daily commute also appear to be relevant for car choice.     

Influence of the residential and work environment on car use in dual-earner households

This paper analyses whether the decision to commute by car is influenced by built environment characteristics of residential neighbourhoods and, more especially, of work locations, taking into account interdependencies between household partners. It shows that the residential environment only affects car use among single-earners. Conversely, for all commuters, but in particular for dual-earners, characteristics of the work location affect whether they commute by car. Even in dual-earner households with two cars, work environment plays a role. We found that in cases of dual-earners with only one car, the partners with the longest commuting distances and the lowest density work locations are most likely to commute by car. Moreover, in households with young children, men are more inclined to leave the car at home. Other features relating to work also affect car commuting, including work flexibility and, especially, possession of a company car. We conclude that future policies aimed at reducing car use should place greater focus on work factors.     

The role of urban form and transit in city car dependence: Analysis of 26 global cities from 1960 to 2000

Car dependence is in decline in most developed cities, but its cause is still unclear as cities struggle with priorities in urban form and transport infrastructure. This paper draws conclusions from analysis of data in 26 cities over the last 40 years of the 20th century. Statistical modelling techniques are applied to urban transport and urban form data, while examining the influence of region, city archetype and individual fixed effects. Structural equation modelling is employed to address causation and understand the direct and indirect effects of selected parameters on per capita vehicle kilometres travelled (VKT). Findings suggest that, while location effects are important, transit service levels and urban density play a significant part in determining urban car use per capita, and causality does flow from these factors towards a city’s levels of private vehicle travel as well as the level of the provision of road capacity.     

The relationship between instrumental, symbolic and affective factors as predictors of car use: A structural equation modeling approach

Traditionally, urban mobility has been studied from the utilitarian or practical viewpoint, focusing on instrumental motivations and ignoring symbolic and affective aspects that may play a relevant role. The purpose of this work is to analyze from a psychosocial perspective the influence of symbolic, affective, and instrumental motivations on the frequency of car use, taking into account diverse reasons for traveling. From a sample of the Spanish population, participants were 284 people (50.3% female), with a driver’s license, car owners and residents in cities of various sizes, who completed an anonymous questionnaire. The effect of each type of variable was estimated by a structural equation model. Results indicate that people’s affective link with their private vehicle explains 12% of frequency of car use, as a latent variable of different kinds of trips: visiting friends or relatives, going to work or to a study center, going shopping, or to leisure areas. The instrumental advantages associated with cars and thinking that it expresses one’s status predict the affective link with the car. These findings corroborate the relevance of the non-instrumental aspects involved in the selection of the means of transportation.