Home-to-work commuting,urban form and potential energy savings: A local scale approach to regional statistics

The link between transport energy consumption and land use patterns has been the focus of a considerable amount of academic works over the past decades. While many empirical researches are backed up with solid statistical techniques, most of them do not fully consider the influence of scale underlying empirical quantitative investigations. Using fine-scale home-to-work commuting data for Wallonia (Belgium), this paper re-evaluates Breheny’s (1995) assertion that urban structure should hold the characteristics of major cities if substantial energy savings are to be achieved. A local scale approach highlights efficient settlements in terms of transport energy consumption not only within major towns, but also within remote rural areas. Furthermore, results suggest that influencing the urban form following local energy efficient examples rather than regional ones could also yield significant gains, without an extreme policy stance of re-urbanisation in major cities.     

Built environmental impacts on commuting mode choice and distance: Evidence from Shanghai

The impacts of the built environment characteristics in residential neighborhoods on commuting behavior are explored in the literature. Scant evidence, however, is provided to scrutinize the role of the built environment characteristics at job locations. Studies also overlooked the potential error correlations between commuting mode and commuting distance due to the unobserved factors that influence both variables. We examined the impacts of the built environment characteristics at both residential and job locations on commuting mode and distance, by applying a discrete-continuous copula-based model on 857 workers in Shanghai. In contrast with studies of Western countries, we showed residential built environment characteristics are more influential on commute behavior than the built environment characteristics at job locations. This suggests the importance of local specificity in policymaking process. We also found the proportion of four-way intersections, road density, and population density in residential areas are negatively associated with driving probability, with elasticity amounts of −1.00, −0.23, and −0.08, respectively. Hence, dense and pedestrian- and cyclist-oriented development help to reduce travel distance and encourage walking, biking, and transit modes of travel.     

Influences of built environment characteristics and individual factors on commuting distance: A multilevel mixture hazard modeling approach

Concerns over transportation energy consumption and green-household gas (GHG) emissions have prompted a growing body of research into the influence of built environment on travel behavior. Studies on the relationship between land use and travel behavior are often at a certain aggregated spatial unit such as traffic analysis zone (TAZ), spatial issues occur among individuals clustered within a zone because of the locational effects. However, recognition of the spatial issues in travel modeling was not sufficiently investigated yet. The object of this study is twofold. First, a multilevel hazard model was applied to accommodate the spatial context in which individuals generate commuting distance. Second, this research provides additional insights into examine the effects of socio-demographics and built environment on commuting distance. Using Washington metropolitan area as the case, the built environment measures were calculated for each TAZ. To estimate the model parameters, the robust maximum likelihood estimation method for a partial function was used, and the model results confirmed the important roles that played by the TAZ and individual level factors in influencing commuting distance. Meanwhile, a comparison among the general multilevel model, single level and multilevel hazard models was conducted. The results suggest that application of the multilevel hazard-based model obtains significant improvements over traditional model. The significant spatial heterogeneity parameter indicates that it is necessary to accommodate the spatial issues in the context of commuting distance. The results are expected to give urban planners a better understanding on how the TAZ and individual level factors influence the commuting distance, and consequently develop targeted countermeasures.     

The impact of land-use mix on residents' travel energy consumption: New evidence from Beijing

Policies that encourage mixed land use are widely believed to make transport more energy efficient. However, few studies have directly examined the impacts of land-use heterogeneity on travel energy consumption at the individual level. Moreover, the definition and measures of land-use heterogeneity are debated. This paper aims to fill these gaps using the large city of Beijing, China, as a case study. Three types of land use are examined in terms of their effects on individual residents’ travel energy consumption. The results suggest that high land-use diversity and a good jobs-housing balance significantly reduces commuting travel. Interestingly, highly heterogeneous retail and housing areas may have high travel energy use, as residents are more likely to go shopping. There are obvious spatial variations in these effects. Residents of suburban ‘newtowns’, where the jobs-housing balance is particularly good, consume less travel energy. The results suggest that decreased use of conventional planning patterns, such as the socialist danwei system, and increasing urban sprawl, bring new challenges to achieving transport efficiency. Mixed land-use policies can be an effective solution to these challenges.     

Finding time‐robust fuel‐efficient paths for a call‐taxi in a stochastic city road network

Intra‐city commuting is being revolutionized by call‐taxi services in many developing countries such as India. A customer requests a taxi via phone, and it arrives at the right time and at the right location for the pick‐up. This mode of intra‐city travel has become one of the most reliable and convenient modes of transportation for customers traveling for business and non‐business purposes. The increased number of vehicles on city roads and raising fuel costs has prompted a new type of transportation logistics problem of finding a fuel‐efficient and quickest path for a call‐taxi through a city road network, where the travel times are stochastic. The stochastic travel time of the road network is induced by obstacles such as the traffic signals and intersections. The delay and additional fuel consumption at each of these obstacles are calculated that are later imputed to the total travel time and fuel consumption of a path. A Monte‐Carlo simulation‐based approach is proposed to identify unique fuel‐efficient paths between two locations in a city road network where each obstacle has a delay distribution. A multi‐criteria score is then assigned to each unique path based on the probability that the path is fuel efficient, the average travel time of the path and the coefficient of variation of the travel times of the path. Copyright © 2016 John Wiley & Sons, Ltd.     

The rational locator reexamined: Are travel times still stable?

The rational locator hypothesis posits that individuals can, if they choose, maintain approximately steady journey-to-work travel times by adjusting their home and workplace. This hypothesis was coupled with the observation of long-term stability in drive alone journey-to-work times in metropolitan Washington (those times were unchanged from 1957 through 1968 to 1988). Despite the increase of average commuting distance and congestion, trip duration remained constant or even declined when controlling for travel purpose and travel mode because of shifting a share of traffic from slow urban routes to faster suburban routes. This observation has significance, as it is important to know for travel demand analysis if there is an underlying budget, or even a regularity, as this helps us determine whether our forecasts are reasonable. To re-test the underlying rationale for the hypothesis that travel times are stable, intra-metropolitan comparisons of travel times are made using Washington DC data from 1968, 1988, and 1994, and Twin Cities data from 1990 and 2000. The results depend upon geography. For the larger Washington DC region, keeping the same geography shows little change in commute times, but using the larger 1994 area suggests an increase in commute times. However, the Twin Cities, starting from a much shorter commute time, shows a marked increase over the decade, using either the smaller or the larger geography. Despite the remarkable continuing observation of stability in drive alone commuting times in metropolitan Washington, we reject the theory of personal commuting budgets, as we find that not only are commuting times not generally stable over time at the intra-metropolitan area, but that commuting time clearly depends on metropolitan spatial structure.     

Using structural equations modeling to unravel the influence of land use patterns on travel behavior of workers in Montreal

This paper addresses the relations between travel behavior and land use patterns using a Structural Equations Modeling (SEM) framework. The proposed model structure draws on two earlier models developed for Lisbon and Seattle which show significant effects of land use patterns on travel behavior. The travel behavior variables included here are multifaceted including commuting distance, car ownership, the amount of mobility by mode (car, transit and non-motorized modes), both in terms of total kilometers travelled and number of trips. The model also includes a travel scheduling variable, which is the total time spent between the first and last trips to reflect daily constraints in time allocation and travel.The modeled land use variables measure the levels of urban concentration and density, diversity, both in terms of types of uses and the mix between jobs and inhabitants/residents, the transport supply levels, transit and road infrastructure, and accessibility indicators. The land use patterns are described both at the residence and employment zones of each individual included in the model by using a factor analysis technique as a data reduction and multicollinearity elimination technique. In order to explicitly account for self selection bias the land use variables are explicitly modeled as functions of socioeconomic attributes of individuals and their households.The results obtained show that people with different socioeconomic characteristics tend to work and live in places of substantially different urban environments. But besides these socioeconomic self-selection effects, land use variables significantly affect travel behavior. More precisely the effects of land use are in great part passed thru variables describing long term decisions like commuting distance, and car ownership. These results point to similar conclusions from the models developed for Lisbon and Seattle and thus give weight to the use of land use policies as tools for changing travel behavior.     

Commute responses to employment decentralization: Anticipated versus actual mode choice behaviors of new town employees in Kunming,China

This study examines workers’ mode-choice responses to a typical job decentralization policy implemented in China’s urban development – government job relocation (GJR) to new towns in the urban periphery. Broadly, the literature suggests that job decentralization tends to increase car commuting; however, little is known about the effects of China’s GJR initiatives on individuals’ commuting mode choices. Using Kunming as a case study, this study examines how workers’ commuting mode choices have shifted in response to the GJR policy. Our study analyzes two travel survey datasets that span the job relocation process: (1) stated preference (SP) data on workers’ anticipated mode choices after a move of workplace to a planned new town; and (2) revealed preference (RP) data on workers’ actual choices of commuting mode after their jobs were moved. The findings suggest that after job relocation, workers’ actual commuting modes shift from more sustainable modes towards cars. The determinants of workers’ mode choices differ substantially between the hypothetical and actual setting of job relocation. The anticipated mode choices are largely determined by socio-demographic characteristics whereas the actual mode choices are strongly influenced by travel time and housing locations. The evidence from this study offers two important implications for future planning practice of job decentralization. First, planners and policy-makers should be skeptical about the transportation benefits of job decentralization. Second, while SP surveys can assist planners to predict individuals’ mode-choice responses, the robustness of SP results should be carefully assessed before translating into the evidence base for informing job decentralization policy-makings.     

Investigating micro-simulation error in activity-based travel demand forecasting: a case study of the FEATHERS framework

Activity-based models of travel demand have received considerable attention in transportation planning and forecasting in recent years. However, in most cases they use a micro-simulation approach, thereby inevitably including a stochastic error that is caused by the statistical distributions of random components. As a consequence, running a transport micro-simulation model several times with the same input will generate different outputs, which baffles practitioners in applying such a model and in interpreting the results. A common approach is therefore to run the model multiple times and to use the average value of the results. The question then becomes: what is the minimum number of model runs required to reach a stable result? In this paper, systematic experiments are carried out using Forecasting Evolutionary Activity-Travel of Households and their Environmental RepercussionS (FEATHERS), an activity-based micro-simulation modelling framework currently implemented for the Flanders region of Belgium. Six levels of geographic detail are taken into account. Three travel indices – average daily activities per person, average daily trips per person and average daily distance travelled per person, as well as their corresponding segmentations – are calculated by running the model 100 times. The results show that the more disaggregated the level, the larger the number of model runs is needed to ensure confidence. Furthermore, based on the time-dependent origin-destination table derived from the model output, traffic assignment is performed by loading it onto the Flemish road network, and the total vehicle kilometres travelled in the whole Flanders are subsequently computed. The stable results at the Flanders level provides model users with confidence that application of FEATHERS at an aggregated level requires only limited model runs.     

The call of the road: factors predicting students’ car travelling intentions and behaviour

The most common daily trip for employed persons and students is the commute to and from work and/or place of study. Though there are clear environmental, health and safety benefits from using public transport instead of private vehicles for these trips, a high proportion of commuters still choose private vehicles to get to work or study. This study reports an investigation of psychological factors influencing students’ travel choices from the perspective of the Theory of Planned Behaviour (TPB). Students from three different university campuses (n = 186) completed a cross-sectional survey on their car commuting behaviour. Particular focus was given to whether car commuting habits could add to understanding of commuting behaviour over and above behavioural intentions. Results indicated that, as expected, behavioural intention to travel by car was the strongest TPB predictor of car commuting behaviour. Further, general car commuting habits explained additional variance over and above TPB constructs, though the contribution was modest. No relationship between habit and intentions was found. Overall results suggest that, although student car commuting behaviour is habitual in nature, it is predominantly guided by reasoned action. Implications of these findings are that in order to alter the use of private vehicles, the factors influencing commuters’ intentions to travel by car must be addressed. Specifically, interventions should target the perceived high levels of both the acceptability of commuting by car and the perceived control over travel undertaken by private vehicle.     

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.     

The positive utility of the commute: modeling ideal commute time and relative desired commute amount

Two measures of commute time preferences – Ideal Commute Time and Relative Desired Commute amount (a variable indicating the desire to commute "much less" to "much more" than currently) – are modeled, using tobit and ordered probit, respectively. Ideal Commute Time was found to be positively related to Actual Commute Time and to a liking and utility for commuting, and negatively related to commute frequency and to a family/community-oriented lifestyle. Relative Desired Commute, on the other hand, was negatively related to amounts of actual commute and work-related travel, but positively related to travel liking and a measure of commute benefit. Overall, commute time is not unequivocally a source of disutility to be minimized, but rather offers some benefits (such as a transition between home and work). Most people have a non-zero optimum commute time, which can be violated in either direction – i.e. it is possible (although comparatively rare, occurring for only 7% of the sample) to commute too little. On the other hand, a large proportion of people (52% of the sample) are commuting longer than they would like, and hence would presumably be receptive to reducing (although usually not eliminating) that commute.     

All minutes are not equal: travel time and the effects of congestion on commute satisfaction in Canadian cities

Despite decades of research, it is unclear under which circumstances travel is most onerous. While studies have found that some individuals derive positive utility from aspects of commuting, others have shown that traffic congestion can entail important time, monetary, and mental stress costs. Moreover, responses to traffic congestion-related stressors differs by individual characteristics. In response, this research captures how exposure to traffic congestion events, the duration of this exposure, and individual trait susceptibility to congestion affect the utility of commuting. Working through the lens of individual satisfaction with the duration of their commute, we show that not every minute of travel is valued the same by car commuters in Canadian cities. Results suggest a complex relationship between travel time, congestion, and individual predisposition to congestion-related stress. While improvements in travel time matter for increasing commute satisfaction, it is reductions in travel in congested conditions that matter most, particularly among those susceptible to congestion-related stressors.     

Cycle commuting in Belgium: Spatial determinants and ‘re-cycling’ strategies

This paper attempts to explain the spatial variation of the use of a bicycle for commuting to work at the level of the 589 municipalities in Belgium. Regression techniques were used and special attention was paid to autocorrelation, heterogeneity and multicollinearity. Spatial lag models were used to correct for the presence of spatial dependence and a disaggregated modelling strategy was adopted for the northern and southern parts of the country. The results show that much of the inter-municipality variation in bicycle use is related to environmental aspects such as the relief, traffic volumes and cycling accidents. Town size, distance travelled and demographic aspects also have some effect. In addition, there are regional differences in the effects of the structural covariates on bicycle use: the impact of variables such as traffic volume and cycling accidents differs substantially between the north and the south of the country. This paper also suggests that high rates of bicycle use in one municipality stimulate cycling in neighbouring municipalities, and hence that a mass effect can be initiated, i.e. more cycle commuting encourages even more commuters in the area to cycle. These findings provide some recommendations for decision-makers wishing to promote a shift from car to bicycle use.     

An investigation of commuting trip timing and mode choice in the Greater Toronto Area: Application of a joint discrete-continuous model

The trip timing and mode choice are two critical decisions of individual commuters mostly define peak period traffic congestion in urban areas. Due to the increasing evidence in many North American cities that the duration of the congested peak travelling periods is expanding (peak spreading), it becomes necessary and natural to investigate these two commuting decisions jointly. In addition to being considered jointly with mode choice decisions, trip timing must also be modelled as a continuous variable in order to precisely capture peak spreading trends in a policy sensitive transportation demand model. However, in the literature to date, these two fundamental decisions have largely been treated separately or in some cases as integrated discrete decisions for joint investigation. In this paper, a discrete-continuous econometric model is used to investigate the joint decisions of trip timing and mode choice for commuting trips in the Greater Toronto Area (GTA). The joint model, with a multinomial logit model for mode choice and a continuous time hazard model for trip timing, allows for unrestricted correlation between the unobserved factors influencing these two decisions. Models are estimated by occupation groups using 2001 travel survey data for the GTA. Across all occupation groups, strong correlations between unobserved factors influencing mode choice and trip timing are found. Furthermore, the estimated model proves that it sufficiently captures the peak spreading phenomenon and is capable of being applied within the activity-based travel demand model framework.     

Comparing air pollution from ferry and landside commuting

Recent and anticipated growth in passenger ferry service has been complicated by concerns about air pollution from marine engines that are only starting to be regulated. While marine engines are known to be a significant and growing source category in some locations, sparse data and analytical difficulties have prevented rigorous comparisons of marine and on-land passenger travel. Using data gathered in the San Francisco Bay Area, we model emissions from three passenger ferries and the matching on-land travel that would be used by commuters if ferry service were not available. The results are analyzed parametrically for levels of ridership and induced travel demand, and for new technologies, including selective catalytic reduction and natural gas fuel. Results indicate that under some conditions, passenger ferries reduce some emissions (including particulate matter emissions) relative to the matching on-land service but increase others. Emissions of NO_X are particularly problematic––all the technologies examined lead to increased NO_X emissions due to ferry commuting. Some of the emissions comparisons are sensitive to mode split, ridership, or induced travel demand. However, NO_X emissions are not––ferry commuting always raises NO_X emissions, even with the most advanced technologies. Implications for local air quality regulators and for technology development are discussed.     

Employer travel plans,cycling and gender: will travel plan measures improve the outlook for cycling to work in the UK?

Cycling is a ‘green’ alternative to commuting by car yet it makes up only a small percentage of journeys in the UK. Here we examine the commuter habits of three companies in Hertfordshire, UK. These provide contrasting case studies allowing examination of travel behaviour in relation to gender and employer travel plans. Women are known to commute shorter distances, yet are less likely to cycle. A variety of cultural and trip characteristics can account for this yet more detailed analysis reveals that some generalisations do not apply. Organisational initiatives to increase cycle commuting were perceived more positively by men than women and this suggests provision of cycling facilities in travel plans will not be effective for organisations employing a large proportion of women. However, this hides a subgroup of women who have access to a cycle and live near enough to cycle who are more positive about cycle facilities. A variety of cultural and societal constraints on cycle use are considered. Measures to encourage cycling in employer travel plans must reflect the gender balance in the organisation as well as recognised geographical and organisational factors.     

Commuting trips within tours: how is commuting related to land use?

Studies that model the effects of land use on commuting generally use a trip-based approach or a more aggregated individual-based approach: i.e. commuting is conceptualized in terms of modal choice, distance and time per single trip, or in terms of daily commuting distance or time. However, people try to schedule activities in a daily pattern and, thus, consider tours instead of trips. Data from the 2000 to 2001 Travel Behaviour Survey in Ghent (Belgium) illustrate that car use and commuting times significantly differ between commuting trips within work-only tours and more complex tours. Therefore, this paper considers trip-related decisions simultaneously with tour-related decisions. A multiple group structural equation model (SEM) confirmed that the relationship between land use and commuting differs between work-only tours and more complex tours. Trips should be considered within tours in order to correctly understand the effect of land use scenarios such as densifying on commuting. Moreover, the use of multiple group SEM enabled us to address the issue of the complex nature of commuting. Due to interactions between various explanatory variables, land use patterns do not always have the presumed effect on commuting. Land use policy can successfully influence commuting, but only if it simultaneously accounts for the effects on car availability, car use, commuting distance and commuting time.     

The missing link: bicycle infrastructure networks and ridership in 74 US cities

Cities promote strong bicycle networks to support and encourage bicycle commuting. However, the application of network science to bicycle facilities is not very well studied. Previous work has found relationships between the amount of bicycle infrastructure in a city and aggregate bicycle ridership, and between microscopic network structure and individual tripmaking patterns. This study fills the missing link between these two bodies of literature by developing a standard methodology for measuring bicycle facility network quality at the macroscopic level and testing its association with bicycle commuting. Bicycle infrastructure maps were collected for 74 Unites States cities and systematically analyzed to evaluate their network structure. Linear regression models revealed that connectivity and directness are important factors in predicting bicycle commuting after controlling for demographic variables and the size of the city. These findings provide a framework for transportation planners and policymakers to evaluate their local bicycle facility networks and set regional priorities that support nonmotorized travel behavior, and for continued research on the structure and quality of bicycle infrastructure and behavior.     

Bottleneck model revisited: An activity-based perspective

The timing of commuting trips made during morning and evening peaks has typically been investigated using Vickrey’s bottleneck model. However, in the conventional trip-based approach, the decisions that commuters make during the day about their activity schedules and time use are not explicitly considered. This study extends the bottleneck model to address the scheduling problem of commuters’ morning home-to-work and evening work-to-home journeys by using an activity-based approach. A day-long activity-travel scheduling model is proposed for the simultaneous determination of departure times for morning and evening commutes, together with allocations of time during the day among travel and activities undertaken at home or at the workplace. The proposed model maximizes the total net utility of the home-based tour, which is the difference between the benefits derived from participating in activities and the disutility incurred by travel between activity locations. The properties of the model solution are analytically explored and compared with the conventional bottleneck model for a special case with constant marginal-activity utility. For the case with linear marginal-activity utility, we develop a heuristic procedure to seek the equilibrium scheduling solution. We also explore the effects of marginal-work utility (or the employees’ average wage level) and of flexible work-hour schemes on the scheduling problem in relation to the morning and evening commuting tours.