Factors affecting car ownership and mode choice in rail transit-supported suburbs of a large Chinese city

As Chinese cities continue to grow rapidly and their newly developed suburbs continue to accommodate most of the enormous population increase, rail transit is seen as the key to counter automobile dependence. This paper examines the effects of rail transit-supported urban expansion using travel survey data collected from residents in four Shanghai suburban neighborhoods, including three located near metro stations. Estimated binary logit model of car ownership and nested logit model of commuting mode choice reveal that: (1) proximity to metro stations has a significant positive association with the choice of rail transit as primary commuting mode, but its association with car ownership is insignificant; (2) income, job status, and transportation subsidy are all positively associated with the probabilities of owning car and driving it to work; (3) higher population density in work location relates positively to the likelihood of commuting by the metro, but does not show a significant relationship with car ownership; (4) longer commuting distance is strongly associated with higher probabilities of riding the metro, rather than driving, to work; (5) considerations of money, time, comfort, and safety appear to exert measurable influences on car ownership and mode choice in the expected directions, and the intention to ride the metro for commuting is reflected in its actual use as primary mode for journey to work. These results strongly suggest that rail transit-supported urban expansion can produce important positive outcomes, and that this strategic approach can be effectively facilitated by transportation policies and land use plans, as well as complemented by timely provision of high quality rail transit service to suburban residents.     

Travel attitudes and mode use among Asian international students at an Australian university

International students and immigrants in general are fuelling the growth in Australia’s population and the pressure that is putting on its urban transport systems. Yet, we know very little about their travel habits and limited previous research has been previously undertaken to address this gap. To address this research need, this study draws on a survey that was designed and distributed online and on-campus to students at Australia’s largest university (Monash University). Using multivariate statistical tools including factor analysis and multinomial logistic regression, significant differences were found between native-born Australian and Asian international students with regards to their mode perceptions, present travel habits and socio-demographics. For Asian students, attitudes towards non-car mode decrease and car-dependency increases the longer they reside in Australia. The findings of this research further highlight the need to encourage newer immigrants to use more sustainable travel options and highlight the relevance for local government and policy planners to support further research in this area, given that these international students have the potential to be key agents for travel behaviour change.     

Built environment and mode choice relationship for commute travel in the city of Rajkot,India

Metropolitan areas around the world are looking for sustainable strategies to reduce use of private automobiles, energy consumption and emissions, often achieved by built environment interventions that encourage use of sustainable modes of transport. This study contributes by providing the empirical evidence on the relation between built environment and mode choice in context of Indian city of Rajkot. Using personal interview data and data available from Rajkot Municipal Corporation it is observed that there is a strong tendency among Rajkot residents to preselect their residential location to suit their modal preferences. This is especially true for non-motorized transport users. Among the built environment variables, access to destination and land use related indicators also have significant influence on mode choice. The study Infers that the land use policy should focus on accessibility and mixing of diverse uses, and transport supply will have to be location based to support non-motorized and public transport travel.     

Factors affecting temporal changes in mode choice model parameters

In travel demand forecasting models, parameters are often assumed to be stable over time. The stability of these parameters, however, has been questioned. This study investigates the factors affecting temporal changes in mode choice model parameters using a method proposed by the author that jointly utilises repeated cross-sectional data. In this method, the parameters are assumed to follow functional forms and the parameter changes are modelled endogenously. While the author’s previous studies assumed that all parameters are the same function of the same variable, this study assumes that different parameters are different functions of different variables, including time (year) and macro-economic variables. The paper describes a case study of a journey-to-work mode choice analysis for Nagoya, Japan, that examines 288 combinations of the functional forms and variables. The analysis found that the functions of time had serious over-fitting problems and that parameter changes are more closely related to economic factors.     

Household-level commuting mode choices,car allocation and car ownership level choices of two-worker households: the case of the city of Toronto

The paper presents a comprehensive investigation on household level commuting mode, car allocation and car ownership level choices of two-worker households in the City of Toronto. A joint econometric model and a household travel survey dataset are used for empirical investigations. Empirical models reveal that significant substitution patterns exist between auto driving and all other mode choices in two-worker households. It is revealed that, female commuters do not prefer auto driving, but in case of a one car (and two commuters with driving licenses) household, a female commuter gets more preference for auto driving option than the male commuter. Reverse commuting (commuting in opposite direction of home to central business district) plays a critical role on household level car allocation choices and in defining the stability of commuting behaviour of two-worker households. Two worker households in higher income zones and with longer commuting distances tend to have higher car ownership levels than others. However, higher transit accessibility to jobs reduces household car ownership levels. The study reveals that both increasing two worker households and reverse commuting would increase dependency on private car for commuting.     

Understanding repetitive travel mode choices in a stable context: A panel study approach

It is argued that most travel mode choices are repetitive and made in a stable context. As an example, the everyday use of public transport is analyzed based on a panel survey with a random sample of about 1300 Danish residents interviewed up to three times in the period 1998–2000. The use of public transport is traced back to attitudes towards doing so, beliefs about whether or not public transportation can cover one’s transport needs, and car ownership. The influence of these variables is greatly attenuated when past behavior is accounted for, however. For subjects without a car, behavior changes are in the direction of greater consistency with current attitudes and perceptions. For car owners, current attitudes are inconsequential. The temporal stability of transport behavior is also higher for car-owners than for non-owners.     

Transition to a cyclable city: Latent variables affecting bicycle commuting

An understanding of the key factors influencing bicycle commuting is essential for developing effective policies towards a cyclable city. This paper contributes to this line of research by proposing a methodology for including cycling-related indicators in mobility surveys based on the Theory of Planned Behaviour (TPB), and applying an exploratory factor analysis (EFA) to evaluate the structure of latent variables associated with bicycle commuting. The EFA identified six cycling latent variables: Lifestyle, Safety and comfort, Awareness, Direct disadvantages, Subjective norm, and Individual capabilities. These were complemented with a latent variable related to habit: Non-commuting cycling habit. Statistical differences and regression analysis were applied with the cycling latent variables. The study also includes the relationship between objective factors and bicycle commuting, which reveals minor associations. This methodology was applied to the “starter cycling city” of Vitoria-Gasteiz (Spain). The results confirm that in this context – in transition to a cyclable city – safety and comfort issues are not the main barriers for all commuters, although more progress needs to be made to normalise cycling. A set of customised policy initiatives is recommended in the light of the research findings, including marketing campaigns to encourage non-commuting cycling trips, bicycle measures to target social groups as opposed to individuals, bicycle-specific programs such as “Bike-to-work Days”, and cycling courses.     

Skateboarding for transportation: exploring the factors behind an unconventional mode choice among university skateboard commuters

Transportation - Efforts to promote non-motorized, active transportation modes typically focus on walking and bicycling. However, other self-propelled devices such as skateboards, roller skates,...     

Short-term planning and policy interventions to promote cycling in urban centers: Findings from a commute mode choice analysis in Barcelona,Spain

BackgroundCycling for transportation has become an increasingly important component of strategies to address public health, climate change, and air quality concerns in urban centers. Within this context, planners and policy makers would benefit from an improved understanding of available interventions and their relative effectiveness for cycling promotion. We examined predictors of bicycle commuting that are relevant to planning and policy intervention, particularly those amenable to short- and medium-term action.MethodsWe estimated a travel mode choice model using data from a survey of 765 commuters who live and work within the municipality of Barcelona. We considered how the decision to commute by bicycle was associated with cycling infrastructure, bike share availability, travel demand incentives, and other environmental attributes (e.g., public transport availability). Self-reported and objective (GIS-based) measures were compared. Point elasticities and marginal effects were calculated to assess the relative explanatory power of the independent variables considered.ResultsWhile both self-reported and objective measures of access to cycling infrastructure were associated with bicycle commuting, self-reported measures had stronger associations. Bicycle commuting had positive associations with access to bike share stations but inverse associations with access to public transport stops. Point elasticities suggested that bicycle commuting has a mild negative correlation with public transport availability (−0.136), bike share availability is more important at the work location (0.077) than at home (0.034), and bicycle lane presence has a relatively small association with bicycle commuting (0.039). Marginal effects suggested that provision of an employer-based incentive not to commute by private vehicle would be associated with an 11.3% decrease in the probability of commuting by bicycle, likely reflecting the typical emphasis of such incentives on public transport.ConclusionsThe results provide evidence of modal competition between cycling and public transport, through the presence of public transport stops and the provision of public transport-oriented travel demand incentives. Education and awareness campaigns that influence perceptions of cycling infrastructure availability, travel demand incentives that encourage cycling, and policies that integrate public transport and cycling may be promising and cost-effective strategies to promote cycling in the short to medium term.     

Travel mode choices in small cities of China: A case study of Changting

The existing literature on urban transportation planning in China focuses primarily on large cities and neglects small cities. This paper aims to fill part of the knowledge gap by examining travel mode choice in Changting, a small city that has been experiencing fast spatial expansion and growing transportation problems. Using survey data collected from 1470 respondents on weekdays and weekends, the study investigates the relationship between mode choice and individuals’ socio-economic characteristics, trip characteristics, attitudes, and home and workplace built environments. While more than 35 percent of survey respondents are car owners, walk, bicycle, e-bike, and motorcycle still account for over 85 percent of trips made during peak hours. E-bike and motorcycle are the dominant means of travel on weekdays, but many people shift to walking and cycling on weekends, making non-motorized and semi-motorized travel especially important for non-commuting trips. Results of multinomial logistic regression show that: (1) job-housing balance might exert different effects on mode choice in different types of urban areas; (2) negative attitude towards e-bike and motorcycle is associated with more walking and cycling; and (3) land use diversity of workplace is related to commuting mode choice on weekdays, while land use diversities of both residential and activity places do not significantly affect mode choice on weekends. Our findings imply that planning and design for small cities needs to differentiate land use and transportation strategies in various types of areas, and to launch outreach programs to shift people’s mode choice from motorized travel to walking and cycling.     

Hitting the sweet spot: Variability in commute lengths and vehicle emissions across a diverse state

In this paper we consider travel across Virginia and identify sustainability “sweet spots” where commute lengths and vehicle emissions per mile combine to maximize green travel in terms of total CO₂ emissions associated with commuting. The analysis is conducted across local voter precincts (N = 2373 in the state) because they are a useful proxy for neighborhoods and well-sized for implementing policy designed to encourage sustainable travel behavior. Virginia is especially appropriate for an examination of variability in sustainable travel behavior and technologies because the state’s transportation, demographic, and political patterns are particularly diverse and have been changing rapidly. We identify four Virginia precinct-based sustainability clusters: Sweet Spots, Emerging Sweet Spots, Neutral and Non-sustaining. A model of demographic differences among the clusters shows that sustainability outcomes, understood in terms of both local commute behavior and vehicle emissions, are significantly associated with the diverse demography and politics of the state. We also look at changes in transportation sustainability and socio-demographic trends within the clusters over the past half-decade, showing that differences in sustainability and demographic metrics are actually accelerating within the state over time. We conclude with a discussion of the implications of the differences among the clusters for developing and implementing effective transportation sustainability policies across the state.     

Factors influencing commuting choices in suburban labor markets: A case analysis of Pleasanton,California

Worsening suburban congestion in recent years has sparked considerable interest in the travel behavior of suburban workers. This paper examines workplace characteristics have influenced the modal and temporal travel choices of suburban employees, using Pleasanton, California, a fast-growing suburb of the San Francisco Bay Area, as a case setting. The incidence of ridesharing was found to be highest for large companies of single-tenant sites with predominantly white-collar workers. Employers who offer workers flex-time privileges tend to be smaller firms with professional staffs situated in multitenant complexes. Many opt for flex-time because they do not have a critical mass of workers to successfully launch and sustain ridesharing programs. Flex-time programs were found to hinder the formation of carpools and vanpools in suburban settings like Pleasanton. The preferred traffic management program, it is argued, would encourage the staggering of work schedules across, not within, companies in order to promote more ridesharing.     

Factors affecting the use of bus and rail services in a deregulated environment

In 1987, the NSW Government commenced deregulation of the long-distance bus industry in NSW. This immediately led to greater inter-modal competition and contestability within the context of changing passenger markets.This study utilises categorical data analysis methods to examine the emerging passenger markets of inter-modal competitors (bus and rail) and to assess the relative importance of socioeconomic and travel related variables which affect the use of bus and rail services along the high volume Sydney-Canberra and Sydney-North Coast corridors.Conclusions from the study indicate varied passenger markets within a relatively new contestable environment which are mode and corridor specific. Results are indicative of the need for competitors to develop marketing strategies conducive to the demands of the travelling public in order to enhance viability and commercial opportunities.     

Trip chaining propensity and tour mode choice of out-of-home workers: evidence from a mid-sized Canadian city

Suburban development patterns, flexible work hours, and increasing participation in out-of-home activities are making the travel patterns of individuals more complex, and complex trip chaining could be a major barrier to the shift from drive-alone to public transport. This study introduces a cohort-based approach to analyse trip tour behaviors, in order to better understand and model their relationships to socio-demographics, trip attributes, and land use patterns. Specifically, it employs worker population cohorts with homogenous activity patterns to explore differences and similarities in tour frequency, trip chaining, and tour mode choices, all of which are required for travel demand modeling. The paper shows how modeling of these important tour variables may be improved, for integration into an activity-based modeling framework. Using data from the Space–Time Activity Research (STAR) survey for Halifax, Canada, five clusters of workers were identified from their activity travel patterns. These were labeled as extended workers, 8 to 4 workers, shorter work-day workers, 7 to 3 workers, and 9 to 5 workers. The number of home-based tours per day for all clusters were modeled using a Poisson regression model. Trip chaining was then modeled using an Ordered Probit model, and tour mode choice was modeled using a Multinomial logit (MNL) model. Statistical analysis showed that socio-demographic characteristics and tour attributes are significant predictors of travel behavior, consistent with existing literature. Urban form characteristics also have a significant influence on non-workers’ travel behavior and tour complexity. The findings of this study will assist in the future evaluation of transportation projects, and in land-use policymaking.

     

Examination of factors affecting freeway incident clearance times: a comparison of the generalized F model and several alternative nested models

Traffic incidents are a principal cause of congestion on urban freeways, reducing capacity and creating risks for both involved motorists and incident response personnel. As incident durations increase, the risk of secondary incidents or crashes also becomes problematic. In response to these issues, many road agencies in metropolitan areas have initiated incident management programs aimed at detecting, responding to, and clearing incidents to restore freeways to full capacity as quickly and safely as possible. This study examined those factors that impact the time required by the Michigan Department of Transportation Freeway Courtesy Patrol to clear incidents that occurred on the southeastern Michigan freeway network. These models were developed using traffic flow data, roadway geometry information, and an extensive incident inventory database. A series of parametric hazard duration models were developed, each assuming a different underlying probability distribution for the hazard function. Although each modeling framework provided results that were similar in terms of the direction of factor effects, there was significant variability in terms of the estimated magnitude of these impacts. The generalized F distribution was shown to provide the best fit to the incident clearance time data, and the use of poorer fitting distributions was shown to result in severe over‐estimation or under‐estimation of factor effects. Those factors that were found to impact incident clearance times included the time of day and month when the incident occurred, the geometric and traffic characteristics of the freeway segment, and the characteristics of each incident. Copyright © 2012 John Wiley & Sons, Ltd.     

Accounting for inertia in modal choices: some new evidence using a RP/SP dataset

Inertia is related with effect that experiences in previous periods may have on the current choice. In particular, it has to do with the tendency to stick with the past choice even when another alternative becomes more appealing. As new situations force individuals to rethink about their choices new preferences may be formed. Thus a learning process begins that relaxes the effect of inertia in the current choice. In this paper we use a mixed dataset of revealed preference (RP)-stated preference (SP) to study the effect of inertia between RP and SP observations and to study if the inertia effect is stable along the SP experiments. Inertia has been studied more extensively with panel datasets, but few investigations have used RP/SP datasets. In this paper we extend previous work in several ways. We test and compare several ways of measuring inertia, including measures that have been proposed for both short and long RP panel datasets. We also explore new measures of inertia to test for the effect of “learning” (in the sense of acquiring experience or getting more familiar with) along the SP experiment and we disentangle this effect from the pure inertia effect. A mixed logit model is used that allows us to account for both systematic and random taste variations in the inertia effect and for correlations among RP and SP observations. Finally we explore the relation between the utility specification (especially in the SP dataset) and the role of inertia in explaining current choices.     

X vs. Y: an analysis of intergenerational differences in transport mode use among young adults

Transportation - Recent research has contrasted the travel patterns of young adults of Generation Y (or, synonymously, the Millennial Generation) with the travel patterns of earlier generations of...     

Measuring quality of service in dial-a-ride operations: the case of a Canadian city

In many countries, dial-a-ride services are provided by public authorities to elderly and handicapped people who cannot use regular transit. Cost minimization is key to running these services, but one can observe a growing interest in quality measurement and improvement. A first step in improving quality is to define a quality measurement scale specific to dial-a-ride services. A second step is to incorporate quality measurements in mathematical models that serve as a basis for optimization algorithms. To this end, an extensive survey of dial-a-ride users was conducted in Longueuil, the largest suburb of Montreal, Canada. This paper describes the steps of the survey and presents its main conclusions: (1) 56 attributes were identified based on interviews, (2) the questionnaire developed has proved to be reliable and valid, (3) an exploratory factor analysis allowed us to determine 13 dimensions of quality in dial-a-ride services, (4) the most important criteria for users were identified, and (5) population segmenting variables by which subgroups of users can be categorized were also determined. Managerial implications of our results are also discussed.     

Bicycle mode share in China: a city-level analysis of long term trends

In the past 15 years, cities in China have experienced big changes in socioeconomic and traffic conditions, resulting in a long term change in bicycle use. This study aims to quantify the changes in bicycle mode share in Chinese cities and explore the potential causes. Based on data from 51 cities, it is found that bicycle mode share at the city level decreased gradually in the past. Conventional bicycle mode share decreased with a rate of 3 % per year, but electric bicycle mode share increased with a rate of 2 % per year. The correlations between city features such as demographics and built environments and bicycle mode share at different city sizes are compared. The generalized linear models are estimated to relate the changes in the share of different trip modes to various city-level factors. The results show that the bicycle mode share in a city is impacted by factors including city area size, population density, number of cars, percentage of local road mileage among all roads, and trip purpose. Possible reasons for the changes in bicycle uses in Chinese cities are explored and policy implications are discussed.     

Double parking in New York city: a comparison between commercial vehicles and passenger vehicles

Transportation - Commercial vehicles are more likely to park close to their destinations than passenger vehicles even though sometimes parking violations are inevitable for their freight or service...