Driving by choice or necessity?

From just about all accounts, Americans are driving more than ever, not just to work but to shopping, to school, to soccer practice and band practice, to visit family and friends, and so on. Americans also seem to be complaining more than ever about how much they drive—or, more accurately, how much everyone else drives. However, the available evidence suggests that a notable share of their driving is by choice rather than necessity. Although the distinction between choice and necessity is not always so clear, it is important for policy makers. For necessary trips, planners can explore ways of reducing the need for or length of the trip or ways of enhancing alternatives to driving. For travel by choice, the policy implications are much trickier and touch on basic concepts of freedom of choice. This paper first develops a framework for exploring the boundary between choice and necessity based on a categorization of potential reasons for and sources of “excess driving”, and then uses in-depth one-on-one interviews guided by this framework to characterize patterns of excess driving. This research contributes to a deeper understanding of travel behavior and provides a basis for developing policy proposals directed at reducing the growth in driving.     

Investigating the subjective and objective factors influencing teenagers’ school travel mode choice – An integrated choice and latent variable model

In this paper, we apply Bhat and Dubey’s (2014) new probit-kernel based Integrated Choice and Latent Variable (ICLV) model formulation to analyze children’s travel mode choice to school. The new approach offered significant advantages, as it allowed us to incorporate three latent variables with a large data sample and with 10 ordinal indicators of the latent variables, and still estimate the model without any convergence problems. The data used in the empirical analysis originates from a survey undertaken in Cyprus in 2012. The results underscore the importance of incorporating subjective attitudinal variables in school mode choice modeling. The results also emphasize the need to improve bus and walking safety, and communicate such improvements to the public, especially to girls and women and high income households. The model application also provides important information regarding the value of investing in bicycling and walking infrastructure.     

The same mode again? An exploration of mode choice variability in Great Britain using the National Travel Survey

The main focus of travel behaviour research has been explaining differences in behaviour between individuals (interpersonal variability) with less emphasis given to the variability of behaviour within individuals (intrapersonal variability). The subject of this paper is the variability of transport modes used by individuals in their weekly travel. Our review shows that previous studies have not allowed the full use of different modes in weekly travel to be taken into account, have used categorical variables as simple indicators of modal variability and have only considered a limited set of explanatory indicators in seeking to explain modal variability. In our analysis we use National Travel Survey data for Great Britain. We analyse modal variability with continuous measures of modal variability (Herfindahl–Hirschman Index, the difference in mode share between the primary and secondary mode, the total number of modes used). Taking inspiration from Hägerstrand (1970), we conceive that modal variability is determined by different types of spatial mobility constraints and find that reduced modal variability is predicted for having mobility difficulties, being aged over 60, being non-white, working full-time, living in smaller settlement, lower household income, having regular access to a car, having no public transport pass/season ticket and not owning a bicycle. The findings can support a change in perspective in transport policy from encouraging people to replace the use of one mode with another to encouraging people to make a change to their relative use of different transport modes.     

Discretionary activity location choice: in-home or out-of-home?

This paper examines the location choice associated with discretionary activities (in-home vs. out-of-home). These substitution patterns are important in terms of travel demand as in-home activities do not necessitate travel while out-of-home activities incur travel. Mixed logit models are estimated using an activity dataset (2003 CHASE data) to analyze the factors associated with this choice at the individual activity-level. Results suggest that the attributes of an activity significantly contribute to understanding the likelihood of engaging in out-of-home activities. Activity type interaction terms reveal the varying influence that socio-demographics, activity attributes and travel have over four different activity types modeled. The results reveal that the location choice (in-home vs. out-of-home) is sensitive to travel characteristics. As the travel time and cost increases, an individual is less likely to engage in an activity out-of-home. Compared to passive and social activities, the location of active activities is more sensitive to changes in travel attributes.     

Does regional travel time unreliability influence mode choice?

Researchers and practitioners highlight the unreliability of travel as a potential weak link in the transportation system which may inhibit individuals’ accessibility and urban economic activity. With the trend towards increasing traffic congestion, the outlook suggests that travel conditions will become structurally less reliable over time, but that not all places will be equally affected. But is travel time unreliability a problem? This study uses global positioning systems travel survey data for Chicago to build a regional model of travel time unreliability. The results suggest that unreliability varies spatially during different time periods, but that the average overall network unreliability varies little across times in the day. Using the Chicago Metropolitan Agency for Planning (CMAP)’s 2007 Travel Tracker Survey, a household travel diary survey including both GPS and non-GPS components, we estimate a mode choice model for work trips to explore the influence of unreliability on travel behavior. The results suggest that unreliable auto travel conditions induce mode switching to transit and that the influence is strongest when service by train is already faster than by car. This further suggests that auto travel unreliability may have the strongest influence in metropolitan regions with highly-competitive transit systems. Nevertheless, the influence of travel unreliability is limited and is not the underlying driver of travel decision-making.     

‘Informal Travel’: A New Conceptualization of Travel Patterns?

Abstract

In transportation, informal transport refers mainly to the use of paratransit services in the developing world. In this paper we argue that informal travel may include, in addition to mode and users, also other travel pattern elements, such as trip planning, structure, purpose, and destination. Each of these can be placed along an axis ranging from formal manifestations to informal ones, thus creating a ‘formality scale’. Moreover, these elements may be combined in numerous ways, creating a multitude of travel patterns that may be placed all along the formality scale. After providing a definition of formal, semi-formal, and informal travel and characterizing travel patterns according to the formality scale we identify population groups which exemplify semi-formal and informal travel patterns. Next, we analyze the 2009 US National Household Travel Survey, which suggests informal travel may be growing. This leads to a discussion on various factors that might affect travel formality. Most notably, the growing use of information and communication technologies may be shifting travel toward the informal end of the axis. In turn, this might affect trip symmetry, which may result in further effects on the transportation system.     

How does environmental concern influence mode choice habits? A mediation analysis

Starting from the intuition that people with high environmental concern have a better perception of public transport and therefore a better perception of the utility of public transport, we construct a theoretical model in which the effect of environmental concern on mode choice habits is mediated by the indirect utility of travel. Travel procures the direct utility of providing access to activities, but it also offers an indirect utility that is inherently personal and perceptual. We approach the indirect utility of public transport by measuring perceptions of time and feelings. The indirect utility of the car is approached by measuring affective and symbolic motives. Taking into account car use habits and habits of public transport use, the results show that people who have a high environmental concern perceive public transport use as easier, more useful and more pleasurable than people who do not have that environmental motivation. Such positive attitudes foster public transport use. Conversely, low environmental concern generates non-instrumental motives for car use, such as affective and symbolic motives. However, the relationship between affective and symbolic motives and car use habits is not robust. We can conclude that environmental concern influences mode choice habits and that the effect is partially mediated by perceptions and feelings towards public transport but not significantly by affective and symbolic motives for car use.     

What cognitive mechanisms predict travel mode choice? A systematic review with meta-analysis

Reduced private car use can limit greenhouse gas emissions and improve public health. It is unclear, however, how promotion of alternative transport choices can be optimised. A systematic review and meta-analysis was conducted to identify potentially modifiable cognitive mechanisms that have been related to car use and use of alternative transport modes. A qualitative synthesis of measures of potentially modifiable mechanisms based on 43 studies yielded 26 conceptually distinct mechanism categories. Meta-analyses of associations between these mechanisms and car use/non-use generated 205 effects sizes (Pearson’s r) from 35 studies. The strongest correlates of car use were intentions, perceived behavioural control, attitudes and habit. The strongest correlates of alternative transportation choices were intentions, perceived behavioural control and attitudes. Implications for researchers and policy implementation are discussed.     

Shared school transportation: determinants of carpooling as children’s school travel mode in California

Transportation - Carpooling has potential as an alternative mode of school transportation along with other viable options, especially at a time when technology continues to increase our reliance...     

Does the choice model method and/or the data matter?

The opportunity to have seven data sets associated with a stated choice experiment that are very similar in content and design is rare, and provides an opportunity to look in detail at the empirical evidence within and between each data set in the context of a range of discrete choice estimation methods, from multinomial logit to latent class to scale multinomial logit to mixed logit, and the most general model, generalized mixed multinomial logit that accounts for preference and scale heterogeneity. Given the problems associated with data from different countries and time periods, we estimate separate models for each data set, obtaining values of travel time savings that are then updated post estimation to a common dollar for comparative purposes. We also pooled all data sets for a scaled MNL model, treating each data set as a set of three separate utility expressions, but linked to the other data sets through scale heterogeneity. This is not behaviourally appropriate with MNL, latent class or mixed logit. The main question investigated is whether there exists greater synergy in the willingness to pay evidence within model form across data sets compared to across model forms within data sets. The evidence suggests that there is a relatively greater convergence of evidence across the choice models, with the exception of generalized mixed logit, after controlling for data set differences; and there is strong evidence to suggest that differences between data sets do matter.     

Correction to: Shared school transportation: determinants of carpooling as children’s school travel mode in California

Transportation - In the online published article, in figure 2 a value is missing in column 4. The correct figure is given in this correction. The original article has been corrected.     

Travel mode attitudes,urban context,and demographics: do they interact differently for bicycle commuting and cycling for other purposes?

This study examined whether interactions between travel mode attitudes, urbanization level, and socio-demographics were different for bicycle commuting and cycling for other purposes. Data were obtained from the 2014 wave of the Netherlands mobility panel (MPN). In total, 2673 respondents (18?+?years) who had recorded at least one trip on the days covered by the survey were included in the sample. Four outcomes were constructed, two of which concerned commuting-related cycling: any commuting-related bicycle usage (yes vs. no) and average cycling duration (in hours per weekday). Likewise, two similar outcome variables concerning cycling for other proposes were constructed. These outcomes were analyzed by means of Tobit regression models (cycling duration) and binary logistic models (any bicycle usage). Attitudinal factors concerning different travel modes, namely bus, car, cycling, and train, were constructed by means of factor analysis. The results showed that a positive attitude toward cycling was positively related to bicycle commuting duration, but this association was less strong among those with a positive attitude toward bus use. Having a positive cycling attitude had a weaker association with both bicycle commuting usage and duration in those who do not always have a car available. Regarding cycling for other purposes, cycling attitude had a stronger positive association with cycling duration among residents of very highly urbanized area, compared to residents of less urbanized areas. The available evidence, though limited, suggests that targeting attitudes can have a measurable impact on bicycling, but not to the same extend among all people.

     

Experience as a conditioning effect on choice: Does it matter whether it is exogenous or endogenous?

Previous choice studies have proposed a way to condition the utility of each alternative in a choice set on experience with the alternatives accumulated over previous periods, defined either as a mode used or not in a most recent trip, or the mode chosen in their most recent trip and the number of similar one-way trips made during the last week. The paper found that the overall statistical performance of the mixed logit model improved significantly, suggesting that this conditioning idea has merit. Experience was treated as an exogenous influence linked to the scale of the random component, and to that extent it captures some amount of the heterogeneity in unobserved effects, purging them of potential endogeneity. The current paper continues to investigate the matter of endogeneity versus exogeneity. The proposed approach implements the control function method through the experience conditioning feature in a choice model. We develop two choice models, both using stated preference data. The paper extends the received contribution in that we allow for the endogenous variable to have an impact on the attributes through a two stage method, called the Multiple Indicator Solution, originally implemented in a different context and for a single (quality) attribute, in which stage two is the popular control function method. In the first stage, the entire utility expression associated with all observed attributes is conditioned on the prior experience with an alternative. Hence, we are capturing possible correlates associated with each and every attribute and not just one selected attribute. We find evidence of potential endogeneity. The purging exercise however, results in both statistical similarities and differences in time and cost choice elasticities and mean estimates of the value of travel time savings. We are able to identify a very practical method to correct for possible endogeneity under experience conditioning that will encourage researchers and practitioners to use such an approach in more advanced non-linear discrete choice models as a matter of routine.

     

The objective versus the perceived environment: what matters for bicycling?

This paper examines the relationship between the objectively measured and perceived built environment, and the relative strength of their association with bicycling behavior. By drawing on socio-cognitive theory, a conceptual model was proposed to explain the relationships between the objective environment, perceived environment, and bicycling behavior. Objective and perceived bike environments were measured using two latent constructs and structural equation modeling was employed to estimate the models based on data from three neighborhoods in Portland, Oregon. Results of this study showed that the perception of the environment had a direct and significant effect on bicycling behavior, while the direct effect of the objective environment on bicycling behavior became insignificant when controlling for perception. We therefore concluded that the objective environment may only indirectly affect bicycling behavior by influencing perceptions. An objectively good environment for bicycling was necessary but not sufficient for bicycling. Intervention programs to improve people’s perceptions of the environment may be necessary to reap the full potential of planning and design policies.     

Motorway crash duration and its determinants: do durations vary across motorways?

Traffic congestion has been a growing issue in many metropolitan areas during recent years, which necessitates the identification of its key contributors and development of sustainable strategies to help decrease its adverse impacts on traffic networks. Road incidents generally and crashes specifically have been acknowledged as the cause of a large proportion of travel delays in urban areas and account for 25% to 60% of traffic congestion on motorways. Identifying the critical determinants of travel delays has been of significant importance to the incident management systems, which constantly collect and store the incident duration data. This study investigates the individual and simultaneous differential effects of the relevant determinants on motorway crash duration probabilities. In particular, it applies parametric Accelerated Failure Time (AFT) hazard‐based models to develop in‐depth insights into how the crash‐specific characteristic and the associated temporal and infrastructural determinants impact the duration. AFT models with both fixed and random parameters have been calibrated on one year of traffic crash records from two major Australian motorways in South East Queensland, and the differential effects of determinants on crash survival functions have been studied on these two motorways individually. A comprehensive spectrum of commonly used parametric fixed parameter AFT models, including generalized gamma and generalized F families, has been compared with random parameter AFT structures in terms of goodness of fit to the duration data, and as a result, the random parameter Weibull AFT model has been selected as the most appropriate model. Significant determinants of motorway crash duration included traffic diversion requirement, crash injury type, number and type of vehicles involved in a crash, day of week and time of day, towing support requirement and damage to the infrastructure. A major finding of this research is that the motorways under study are significantly different in terms of crash durations; such that motorway 1 exhibits durations that are on average 19% shorter compared with the durations on motorway 2. The differential effects of explanatory variables on crash durations are also different on the two motorways. The detailed presented analysis confirms that looking at the motorway network as a whole, neglecting the individual differences between roads, can lead to erroneous interpretations of duration and inefficient strategies for mitigating travel delays along a particular motorway.     

Children’s mode choice for the school trip: the role of distance and school location in walking to school

Rising levels of childhood obesity in the United States and a 75% decline in the proportion of children walking to school in the past 30 years have focused attention on school travel. This paper uses data from the US Department of Transportation’s 2001 National Household Travel Survey to analyze the factors affecting mode choice for elementary and middle school children. The analysis shows that walk travel time is the most policy-relevant factor affecting the decision to walk to school with an estimated direct elasticity of −0.75. If policymakers want to increase walking rates, these findings suggest that current policies, such as Safe Routes to School, which do not affect the spatial distribution of schools and residences will not be enough to change travel behavior. The final part of the paper uses the mode choice model to test how a land use strategy—community schools—might affect walking to school. The results show that community schools have the potential to increase walking rates but would require large changes from current land use, school, and transportation planning practices.

Emission control areas: More or fewer?

As the global sulphur limit implemented by the International Maritime Organization (IMO) and the further development of sulphur emission reduction technologies, the effects of Emission Control Areas (ECAs) on reducing the sulphur emissions from ships will be reduced gradually. To explore the necessity of ECAs in the near future, this paper introduces the fictitious sulphur emission permit allocated to shipping carriers for our considered region. We propose an ECA location problem, which determines the location of ECAs in order to minimize the impact of sulphur emissions on human health, while satisfying the constraint on the fictitious sulphur emission permit. A mixed-integer linear programming model is proposed for our investigated problem. Numerical experiments are carried out by using our proposed model applied to China and Africa, where the sulphur emissions at different sites are estimated via the fuel consumption calculated by collecting data from liner carriers. Results show that, for the case of China, the Bohai Rim, the Yangtze River Delta and the Pearl River Delta have a high probability for establishing ECAs. For the case of Africa, the Guinea Bay and South Africa have a high probability for establishing ECAs.     

Factors influencing travel mode choice among families with young children (aged 0–4): a review of the literature

Life events, such as the birth of a child, disrupt habitual travel behaviour and provide a valuable opportunity to influence the adoption of sustainable transport practices. However, in order for sustainable travel practices to be adopted, an understanding is required of the factors that influence travel mode choice among families with young children. Research in this field is particularly timely given many in the millennial generation, a comparably large cohort, are approaching this life stage. This comprehensive literature review develops a framework of factors influencing travel mode choice among families with young children. The findings reveal a multitude of factors influence decisions about mode choice, and, in particular, encourage travel by car, when travelling with young children. The paper concludes with an agenda for future research about travel among families with young children, a largely overlooked group of transport users.     

Understanding time use: Daily or weekly data?

The appropriate duration of time diaries as a source of time use data is analyzed in a structured way. Nine detailed European surveys based on seven-days diaries are used in order to study different dimensions of data quality, duration and variability of activities, and modeling capabilities. Pseudo diaries of 1, 2 (one week, one weekend) and 3 (one week, both weekend) days are constructed to further analyze these issues, selecting the seven-days diaries data as a benchmark. Comparative results show that two and three-days weighted surveys seem to be an adequate surrogate for the information obtained in weekly surveys that capture a basic work–leisure cycle.     

Eco-driving: An economic or ecologic driving style?

In this work the trade-off between economic, therefore fuel saving, and ecologic, pollutant emission reducing, driving is discussed. The term eco-driving is often used to refer to a vehicle operation that minimizes energy consumption. However, for eco-driving to be environmentally friendly not only fuel consumption but also pollutant emissions should be considered. In contrast to previous studies, this paper will discuss the advantages of eco-driving with respect to improvements in fuel consumption as well as pollutant gas emissions. Simulating a conventional passenger vehicle and applying numerical trajectory optimization methods best vehicle operation for a given trip is identified. With hardware-in-the-loop testing on an engine test bench the fuel and emissions are measured. An approach to integrate pollutant emission and dynamically choose the ecologically optimal gear is proposed.