Disentangling the behavioural side of the first and last mile problem: the role of modality style and the built environment

The first and last mile (FLM) problem, namely the poor connection between trip origins or destination and public transport stations, is a significant obstacle to sustainable transportation as it is likely to encourage the use of cars for FLM travel, if not for the entire trip. This study examines the role of modality style and built environment in FLM mode choice behaviour, in order to identify the key features that might invoke a travel mode shift from cars to more sustainable travel options for both mandatory and discretionary trips. More specifically, this study draws on disaggregate data from the South East Queensland household travel survey and presents a latent class choice model to unravel modality style groups. Results reveal two distinct individual-level modality style groups: (1) driving and walking oriented; (2) multimodal travellers. Individuals in the second modality style group were found to be relatively inelastic to FLM travel time for mandatory trips, while individuals in the first group were largely unaffected by built environment characteristics and highly habitual in their mode choice behaviour for both mandatory and discretionary trips. Home residence environments with high road intersection density and public transport accessibility, and home residence environments with diverse land use mix, respectively encourage individuals within the second modality style to walk for mandatory trips, and discretionary trips. To this end, when place-based policies seek to change certain built environment features, individuals in the second modality style are more likely to shift their preference from cars to more sustainable modes. Finally, our findings have practical planning implications in targeting mode shift through highlighting the importance of considering the intersection of individual modality style in a given locale and mode choice behaviour. More specifically, our findings advocate for place-based policies that seek to target particular locales with the certain modality style deemed to be more predisposed to adopting a mode shift.     

The path and time efficiency of residents' trips of different purposes with different travel modes: An empirical study in Guangzhou,China

Improving residents' travel efficiency and reducing carbon emissions from travel are the key issues for sustainable development of urban transportation. This study first employed a circuity index to measure the path efficiency of residents' trips based on 2015 survey data in Guangzhou and developed a generalized additive model (GAM) to investigate the relationship between the path efficiency and travel distance for different purposes of trip and different travel modes. On this basis, it further evaluated the time efficiency of different travel modes for each trip. The results showed that there is a complex and nonlinear relationship between the path efficiency and travel distance, which differs between different purposes of trips and different travel modes. In general, trips by non-motorized transport have a lower circuity index and higher path efficiency than those by cars or public transport. Moreover, non-motorized transport is the time-efficiency optimal mode for almost half of the trips, especially for daily shopping trips. However, people prefer to choose public transport on their trips even though public transport is not the time-efficiency optimal mode for these trips. Generally, only about half of the residents chose the time-efficiency optimal mode for their trips. Those who did not choose the time-efficiency optimal mode tended to choose the modes with higher carbon-intensity. The conclusions of this study indicate that for improving travel efficiency and reducing carbon emissions from transport, more efforts should be focused on the non-motorized travel environment and developing relevant policies to encourage more walking and cycling.     

Is telecommuting sustainable? An alternative approach to estimating the impact of home-based telecommuting on household travel

Telecommuting is regarded as a sustainable travel-demand management strategy. In investigating how much telecommuting reduces travel, studies typically adopt one method of the following three: (1) multiplying the telecommuting frequency by the round-trip commute distance, (2) measuring travel changes using quasi-experiments, and (3) determining the marginal effect of telecommuting on travel using econometric analyses. However, each approach has methodological limitations, and previous studies fail to take into consideration various aspects of household travel other than the telecommuter's commute. Against this backdrop, this study presents an alternative approach to estimating the impact of the household head's telecommuting on total household travel other than his or her commute travel using data from the 2006 Household Travel Survey in Korea. Our series of stratified tobit regression analyses show that when the household head does not commute, the usual compensatory travel mechanism induces person-kilometers traveled of 2 km. This rebound effect doubles when the household head telecommutes, although not on regular commuting days. The effect suggests that the benefits of telecommuting are significantly less than anticipated. Consequently, planners and policy makers should consider this counteracting effect when predicting the travel reduction effect of telecommuting or determining the level of telecommuting required to achieve environmental policy goals for urban sustainability.     

Estimating social travel demand of senior citizens in the Netherlands

Like many other countries, the Netherlands is experiencing a sharp rise in the ageing population. As age increases, people’s mobility may decrease. However, older people have more leisure time compared to their younger (working) counterparts, and potentially spend more time on social activities. Therefore, this group can possibly increase social travel demand. However, to date, the travel demand for social activities of senior citizens has received only little attention. This paper studies trip-making for social purposes, with a special focus on the demographic ageing factors. Using social activity diary data, models are estimated to predict the number of social trips, the travel distance and mode of transport for social trips. The results indicate that the elderly of today seem to be as mobile as their younger counterparts with respect to the number of social trips. High education and involvement in clubs on average result in more social trips and full time work is found to result in fewer social trips. With regard to trip distance the results show that the average travel distance does not decrease as people get older. Full time work is found to result in longer social trips. Shorter trips were found for people in urban as well as rural areas. Trips for the purpose of visiting or joint activities tend to be longer than average. With regard to transport mode choice the results indicate that older seniors (75+) are less likely to choose the bicycle, relative to driving. No other significant age effects were found. Significant effects were found for gender, household structure, education level, car ownership, having a disability, urban density, distance and the purpose of the social activity.     

Travel time use and its impact on high-speed-railway passengers' travel satisfaction in the e-society

The availability of wireless networks and the pervasive use of mobile ICT devices have allowed passengers to conduct various e-activities during journeys. These various e-activities, in turn, may change people's conventional perception of travel time from being “wasteful” and “unproductive,” to “desirable” and giving rise to satisfaction. Journeys on high-speed railway (HSR) is particularly relevant for transport researchers to probe into this question because of its characteristics of being medium to long-distance (typically taking half-an-hour or more), seat availability, and a smooth ride. Using a questionnaire survey on passengers along the Shanghai-Nanjing HSR route, this study aims to examine the nature of ICT device use and in-vehicle e-activities conducted by HSR passengers and the influence on their travel satisfaction with their on-board journey experience. Our results reveal a high percentage of ICT device use and a wide variety of e-activities such as e-working, e-communication, and e-reading for leisure on HSR trains. In addition, the higher use of ICT device was associated with an increase of passengers' travel satisfaction. Furthermore, we found a positive effect of work-related e-activities on travel satisfaction for business/work trips, while a positive effect of entertainment-related e-activities for non-business/work trips. Given that HSR is potentially a more sustainable transport mode, some possible policy implications are proposed to encourage people to use HSR, as opposed to driving or flying, for medium to long-distance intercity journeys.     

Predicting multi-faceted activity-travel adjustment strategies in response to possible congestion pricing scenarios using an Internet-based stated adaptation experiment

This paper reports the estimation of several discrete choice models describing reactions of individuals to congestion pricing scenarios. The models were estimated on data obtained in a stated adaptation experiment that was administered through the Internet and designed to examine how individuals adjust their activity-travel patterns. An activity-based approach is used meaning that all choice facets of activity patterns are taken into account as well as a complete set of activities. Estimates of price elasticities of travel demand are in line with other findings reported in the literature. Results of the stated adaptation experiment suggest that changing route or departure time is the most important way of adapting work trips, whereas public transport and working at home play a more limited role. For non-work activities changing route and switching to bike are the dominant responses.     

Conceptualising convenience: Transportation practices and perceptions of inner-urban high density residents in Brisbane,Australia

High-density living in inner-urban areas has been promoted to encourage the use of more sustainable modes of travel to reduce greenhouse gas emissions. However, previous research presents mixed results on the relationship between living in proximity to transport systems and reduced car-dependency. This research examines inner-city residents’ transportation practices and perceptions, via 24 qualitative interviews with residents from high-density dwellings in inner-city Brisbane, Australia. Whilst participants consider public transport accessible and convenient, car use continues to be relied on for many journeys. Transportation choices are justified through complex definitions of convenience containing both utilitarian and psycho-social elements, with three key themes identified: time-efficiency, single versus multi-modal trips, and distance to and purpose of journey, as well as attitudinal, affective and symbolic elements related to transport mode use. Understanding conceptions of transport convenience held by different segments of the transport users market, alongside other factors strongly implicated in travel mode choice, can ensure targeted improvements in sustainable transport service levels and infrastructure as well as information service provision and behavioural change campaigns.     

Residential location and daily travel distances: the influence of trip purpose

This paper investigates the extent to which residential location influences daily distance travelled if travel purposes are differentiated. Statistical multilevel models are applied to Swedish National Travel Survey data from 2005–2006. Travel purposes are categorized by considering time–spatial constraints and hypothesized factors of personal freedom of choice. Results indicate that the influence of residential location on daily distance travelled is highly conditional on trip purpose in a nationwide Swedish context. Although statistically significant proportions of the variation in daily distance travelled to work, on service errands, and on weekdays were dependent on residential location, daily travel distances for leisure activities and on weekends varied greatly among people living in the same neighbourhood. From a policy perspective, these results suggest that measures intended to alter the built environment to reduce the volume of travel will be most efficient as regards work trips, while trips taken during free time are unlikely to be much affected. In addition, the multilevel models applied reveal several important interactions between the variation in travel distances across residential locations and individual characteristics of which researchers should be aware, especially when examining service trips.     

Is traffic congestion overrated? Examining the highly variable effects of congestion on travel and accessibility

Congestion is universally unpopular, but is it always a problem? Are some places more “congestion-adapted” than others? Using data for Los Angeles, we examine whether the geographies of congestion and accessibility are distinct by mapping and describing them across neighborhoods. We then estimate a series of regression models of trip-making to test the net effects of traffic delays on behavior. We find that there are places where people make many trips and engage in many activities despite lots of congestion, which tend to be more central, built-up areas that host many short trips; in other places, high congestion and low activity coincide. Why the variance? While congestion can constrain mobility and reduce accessibility, traffic is also associated with agglomerations of activity and is thus a byproduct of proximity-based accessibility. Whether agglomeration and congestion have net positive or negative impacts on activity participation thus varies substantially over space. Controlling for factors such as income and working at home, we find that the effects of congestion on access depend on whether congestion-adaptive travel choices (such as walking and making shorter trips to nearby destinations) are viable. Because “congestion-adapted” places tend to host more trip-making, planners may be justified in creating more such places in order to increase accessibility, even if doing so makes absolute levels of congestion worse in the process.     

Household decision-making for everyday travel: a case study of walking and cycling in Lancaster (UK)

Increased walking and cycling for short journeys in urban areas has many obvious advantages yet so far gains from the promotion of more sustainable travel of this type are mostly small. This paper reports on a large research project which uses a mixed method approach to explore attitudes to and perceptions of walking and cycling, and which examines the process of household decision-making for everyday travel and the constraints that this imposes. Using survey, interview and ethnographic data it is argued that many people hold ambiguous and sometimes contradictory views of walking and cycling as effective means of everyday travel, that what they do rarely matches precisely what they believe, and that the complexity and contingency associated with everyday travel for many households is a major barrier to the use of more sustainable travel modes. It is suggested that better understanding of these processes could help to inform both future transport policy and the promotion of walking and cycling for short trips in urban areas.     

Joint estimation of mode and time of day choice accounting for arrival time flexibility,travel time reliability and crowding on public transport

This study develops joint choice models of mode and departure time for implementation in MetroScan, a new version of TRESIS (Hensher and Ton, 2002). Separate models are estimated for work and non-work purposes, testing all practical alternatives of model structure with a rich set of explanatory variables. The contributions of the current work to the existing TRESIS are twofold. First, travel demand for non-work purposes such as shopping, social and recreation are explicitly modelled in MetroScan as opposed to TRESIS that scales the demand for work purposes to obtain non-work travel demand. Second, choices of travel mode and departure time become more sensitive to situational factors such as the flexibility of arrival time, the reliability of travel time and crowding. Willingness to pay for various improvements to the level of service is derived. We describe and demonstrate how the proposed models are applied in the general modelling framework of MetroScan.     

Measuring cycling accessibility in metropolitan areas

Different measures of cycling accessibility have been widely introduced in transportation planning. However, those measurements are mainly restricted by the availability of travel behavior data. In addition, there has been limited comprehensive research on the importance of cycling accessibility to destinations based on the travel time or distance. In this paper, a new index for measuring bikeability in metropolitan areas is introduced. A Cycling Accessibility Index (CAI) is developed for quantifying cycling accessibility within local areas in metropolitan Melbourne, Australia. CAI is defined according to gravity-based measures of accessibility. This index measures cycling accessibility levels in terms of diversity of different land uses, number of activities in statistical areas, and the travel impedance between origins and destinations. The Victorian Integrated Survey of Travel and Activity (VISTA) dataset was used to evaluate the index and investigate the association between the cycling accessibility levels and the number of bicycle trips in local areas. The index is assessed by investigating the association between levels of cycling accessibility and the number of bicycle trips in statistical areas. Key findings indicate that there is a significant positive association between bike trips and the CAI.     

Can freeway traffic volume information facilitate urban accessibility assessment?: Case study of the city of St. Louis

In urban contexts, accessibility measures are often utilized to represent the interactions among land use, transport and people’s trips to services and other facilities. Accessibility is generally evaluated using conventional traffic measures such as travel time and distance, but traffic volume, which is a product of the travel trips induced by people’s needs, may also be positively related to accessibility. This study tests the hypothesis “can freeway traffic volume information facilitate urban accessibility assessment?” Traffic volume based accessibility models are proposed to investigate this relationship and test the hypothesis. The results indicate that the answer to this question is a qualified “yes”, as there is a statistically significant relationship between traffic volume differences and accessibility. The coefficients of the models can potentially be used as a reference to guide the urban planning process. The limitations of the proposed models can be addressed by deploying Intelligent Transportation Systems (ITS) traffic sensors on ramps and arterial roadways.     

Traffic exposure near the Los Angeles–Long Beach port complex: using GPS-enhanced tracking to assess the implications of unreported travel and locations

Traffic exposure assessments could misclassify the extent and locations of exposure if traditional recall surveys and self-reported travel diaries do not record all participant activities. The Harbor Communities Time Location Study (HCTLS) examines the nature, extent and implications of underreported locations/trips in a case study which used portable Global Positioning Systems (GPS) devices to track the diurnal patterns and traffic exposure of 47 residents of communities near the Los Angeles–Long Beach port complex. Participants were similar to adults nationwide in time spent indoors, in-vehicle, and outdoors, but spent more time indoors at home (78% vs. 66%). Overall, participants did not report nearly half (49%) of the locations and trips identified in GPS-enhanced data on their activity diaries, resulting in about 3 h/day in unreported locations and 0.6 h/day in unreported trips. The probability of a location/trip being underreported was systematically correlated with participant and location/trip characteristics. Self-reported data missed about 50 min of heightened air pollution exposures during the 5 h/day on average participants spent in high-traffic areas and about 30 min during the 4 h/day near truck routes. GPS-enhanced methods provide opportunities to more precisely characterize exposure periods and tools to identify facility, roadway, and land use types of the greatest concern for mitigation efforts.     

An approach to imputing destination activities for inclusion in measures of bicycle accessibility

This paper proposes a new method to estimate bicycle accessibility for various trip purposes based on a massive dockless bike-sharing dataset in Shanghai, China. Specifically, a Dirichlet multinomial regression topic model (DMR model) is applied to identify bicycle trajectories' trip purposes, simultaneously considering arrival time and drop-off location. Based on obtained trip purposes, we estimate impedance functions using a negative exponential function. Finally, based on estimated impedance functions, two cases of bicycle accessibility for two different purposes - restaurant and hospital - are presented in Shanghais central area. The results show that almost 90% of bicycle trips are less than 30 min or 5 km. Although the difference between the impedance functions between various trip purposes is not significant, we find that trip purposes of “Work and School” have the highest travel impedance for bicyclists. Cyclists in Shanghai accept longer bicycle travel times for leisure (e.g., shopping) than for commuting (e.g., work or school).     

Factors associated with disability paratransit's travel time reliability

This paper identifies some of the characteristics of trips and pick-up and drop-off locations that are associated with paratransit's travel time reliability. Following convention, reliability has been defined as the inverse of variability. Four measures of travel time variability have been used to examine reliability: Standard Deviation, Percent Variation, Misery Index, and Buffer Index. Regression models have been used to estimate these four variables with trip data from Access Link, the paratransit service provided by NJ TRANSIT pursuant to the Americans with Disabilities Act (ADA). A number of characteristics of the pick-up and drop-off locations as well as selected characteristics of the trips were used as independent variables of the models. The statistical significance of the independent variables varied depending on which measure of reliability was estimated, but a few variables were consistently associated with reliability in all four models. These variables were trip distance, booking type, winter season, density of motor vehicle crashes in pick-up and drop-off locations, and whether pick-ups occurred in suburban bus corridors or urban core areas. Because of the significance of the variables on motor vehicle crash density in pick-up and drop-off locations, an additional regression model was used to examine the effect of crash incidents on trip duration by considering drop-offs that occurred in locations immediately after a crash. The model showed that trips take 4 to 5% longer when crashes occur in locations prior to a drop off. Planning implications of the findings are discussed.     

Carer-employees’ travel behaviour: Assisted-transport in time and space

Assisted-transport demand is a daily caregiving task that affects carer-employee’s activity-travel behaviour; however, little is known about such behaviour and the types of constraints that impact carer-employee health. Combining the principles of Hägerstrand’s time geography and Mckie et al.’s caringscape terrain, this research develops a mixed-methods framework to classify the travel behaviour of carer-employees based on their travel experience and the space-time fixity of their weekly schedules. The mixed-methods framework consists of sentiment analysis and k-means clustering, both which are used to analyze 25 randomly selected participants within the Greater Toronto-Hamilton Area (GTAH). Participants were asked to reflect on their recorded one-week trips in a trip summary questionnaire. Sentiment analysis was used to thematically describe carer-employees’ travel behavior, whereas, k-means clustering generated travel behaviour profiles. “Time”, “pressure”, “parents”, “run”, and “long” were several thematic keywords describing the carer-employees’ travel behaviour. K-means clustering identified three relative types of carer-employees’ travel behaviours: 1) flexible, 2) between flexible and fixed, and; 3) fixed. These results provide critical information for the establishment of custom transport programs, such as maximum monthly telecommuting allotment; such programs are useful for employers to use in order to alleviate assisted-transport demand on their employees.     

Analysing bicycle-sharing system user destination choice preferences: Chicago’s Divvy system

In recent years, there has been increasing attention on bicycle-sharing systems (BSS) as a viable and sustainable mode of transportation for short trips. However, due to the relatively recent adoption of BSS, there is very little research exploring how people consider these systems within existing transportation options. Given recent BSS growth around the world, there is substantial interest in identifying contributing factors that encourage individuals to use these systems. The current study contributes to this growing literature by examining BSS behavior at the trip level to analyze bicyclists’ destination preferences. Specifically, we study the decision process involved in identifying destination locations after picking up a bicycle at a BSS station, using a random utility maximization approach in the form of a multinomial logit model (MNL). The quantitative frameworks developed have been estimated using 2013 data from the Chicago’s Divvy system. In our modeling effort, we distinguish between BSS users with annual membership and short-term customers with daily passes. The developed model should allow bicycle-sharing system operators to plan services more effectively by examining the impact of travel distance, land use, built environment, and access to public transportation infrastructure on users’ destination preferences. Using the estimated model, we generated utility profiles as a function of distance and various other attributes, allowing us to represent visually the trade-offs that individuals make in the decision process. To illustrate further the applicability of the proposed framework for planning purposes, destination station-choice probability prediction is undertaken.     

Non-linear associations between built environment and active travel for working and shopping: An extreme gradient boosting approach

Active travel has environmental, social, and public health-related benefits. Researchers from diverse domains have extensively studied built-environment associations with active travel. However, limited attention has been paid to distinguishing the associations between built environment characteristics at both the origins and destinations and active travel for working and shopping. Scholars have started to examine non-linear associations of built environment with travel behaviour, but active travel has seldom been a focus. Therefore, this study, selecting Xiamen, China, as the case, utilises a state-of-the-art machine learning method (i.e., extreme gradient boosting) to explore the non-linear associations between built environment and active travel for working and shopping. Our findings are as follows. (1) For both purposes, trip characteristics contribute the greatest, and the built environment is also quite important and has larger collective contributions for active travel than does socioeconomics. (2) The relative importance of built environment on active travel for shopping is evidently larger than that for working. (3) All built-environment variables have non-linear associations with active travel, and associations with active travel for working are generally in inverted U or V shapes, while those with shopping trips have much more complex patterns. (4) Differences in the threshold value and gradient exist between built-environment associations with active travel for working and shopping and between variables at origins and destinations. Decision makers are recommended to meticulously disentangle the complex influences of built environment on active travel and distinguish between diverse purposes to make informed and targeted interventions.     

The indirect effect of the built environment on travel mode choice: A focus on recent movers

Many studies have demonstrated that the built environment has a strong impact on people's travel mode choice. However, the built environment also influences elements such as travel distance and car ownership, which might be the true predictors of which travel modes are chosen. In this study, we analyse the effects of changes in residential neighbourhood on changes in travel mode (for commute trips and leisure trips), both directly and indirectly through changes in car ownership, travel distances and travel attitudes. This study applies a structural equation modelling approach using quasi-longitudinal data from 1650 recently relocated residents in the city of Ghent, Belgium. Results indicate that the built environment has strong direct effects on active leisure trips and car use. However, distance (for car use) and attitudes (for active travel) were found to be important mediating variables. In sum, the effect of the built environment on travel mode choice might be more complex than commonly assumed as it partly seems mediated by travel distance and travel attitudes.