Urban spatial location advantage: The dual of the transportation problem and its implications for land-use and transport planning

Numerous recent studies have investigated the relationship between the location of jobs and housing in urban areas and how this relates to urban commuting patterns. Few have utilised the dual of the transportation problem of linear programming (TPLP) to provide insights into these relationships Accordingly, this analysis utilises the TPLP to determine dual variable values (shadow prices) for a study area in Dublin, Ireland. The approach determines the pattern of relative location advantage for the peak and off-peak travel periods and for public and private transport for 1991 and 2001. The results are set against the expected results for hypothetical urban structures. The results show that the pattern of relative location advantage has altered sharply over the study period for off-peak trip-making but has remained more or less the same for trip-making in the peak period. For the off-peak period, the pattern of relative location advantage has shifted from the central area to the periphery specifically for private transport trips; for public transport, the pattern has remained focused on the city centre. This indicates that private transport users can react more quickly to changes in the distribution of land-use activities than their public transport counterparts due to the relatively fixed nature of the latter mode. This implies that the public transport network needs to be reorganized to better reflect the revised pattern of trip-making specifically for the off-peak period. The results demonstrate the value of using the approach for providing information about the spatial organisation of land uses within cities and where future development may be targeted.     

Excess commuting and modal choice

This paper reports results from research conducted to analyse the extent of excess commuting in Dublin, Ireland. The research differs from similar studies on excess commuting in two ways. First, a disaggregate modal choice analysis of excess commuting is undertaken for two time periods – 1991 and 2001. Second, sensitivity analysis is undertaken to explore the impact of changes in the density of the transport network for users of public and private transport. The results suggest that excess commuting is considerably greater for users of private transport implying the greater inefficiency of commuting associated with that mode. By way of contrast, capacity utilisation measures suggest the opposite indicating the difficulty of using these measures for policy-making. The results suggest also that the greater inter-mixing of jobs–housing functions has facilitated reductions in actual commuting costs as well as increasing the range of available trip possibilities over the study period. In terms of the sensitivity analysis, the results suggest that public transport users could achieve dramatic savings on their commute if the density of that network was increased considerably.     

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.     

Metropolitan sprawl measurement and its impacts on commuting trips and road emissions

This study measures urban form as indicators of metropolitan sprawl and explores its impact on commuting trips and NO_x and CO₂ emissions from road traffic in all metropolitan statistical areas (MSAs) and four groups’ MSAs separated by population in the continental United States. Encompassing all MSAs, the study adds the accessibility factor to four existing factors: density, land use mix, centeredness, and street connectivity. The study establishes multivariate regression models between urban form, commuting trips, and emissions from road traffic while controlling for socioeconomic conditions. The study shows that urban form index and five urban form factors have a statistically significant association with commuting trips, NO_x and CO₂ emissions from road traffic. In four MSA groups as determined by MSA population size, higher values of urban form factors (i.e., lower sprawl) are statistically associated with more walking commuters. On the other hand, higher values of urban form factors are associated with fewer commuting vehicles per household in large MSAs with the moderate effect, a lower average commuting drive time in medium and small MSAs, and more commuters using public transportation in medium and large MSAs. This study provides an urban form index covering all metropolitan areas in the continental United States by adding another urban form factor, and the findings show that urban form factors have different effects on mode choices, drive time, and emission from road traffic depending on the MSA population size.     

Impacts of commuting efficiency on congestion and emissions: case of the Hamilton CMA, Canada

This study uses IMULATE (Integrated Model of Urban LAnd use, Transportation, energy and Emissions) to examine the impacts of commuting efficiency on congestion and automobile emissions—specifically, non-methane hydrocarbons, carbon monoxide and nitrogen oxides—in the Hamilton Census Metropolitan Area. Estimates of these externalities are compared for two commuting scenarios: a base scenario of estimated commuting flows for 1991 and an optimal scenario in which the mean commuting time for all workers is minimized. The findings indicate that significant reductions in congestion and automobile emissions are possible by advocating policies that encourage greater commuting efficiency in the locational choices of workers. The analysis of jobs–housing balance as one such means suggests that a considerable proportion of commuting cannot be explained by geographical imbalances in the distributions of jobs and housing, and that workers consider many factors besides commuting costs in their locational choices. It is concluded that policies promoting jobs–housing balance as the principal strategy for facilitating more efficient commuting may not meet the expectations of policy-makers.     

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.     

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

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

Changes to commute mode: The role of life events,spatial context and environmental attitude

It has been suggested that commuting behaviours become habitual and that changes to commute mode are more likely at the time of major life events. However, evidence to support this has so far been limited to analyses of small-scale samples. To address this evidence gap, we use two waves of panel data from the UK Household Longitudinal Study (2009/10 and 2010/11) to identify and explain the prevalence of individual change in commute mode from year to year amongst a representative sample of the English working population (n = 15,200). One third of those that cycle or get the bus to work, and one quarter of those that walk to work, are shown to change commuting mode by the following year. Car commuting is more stable, with only one in ten car commuters changing mode by the following year. Commute mode changes are found to be primarily driven by alterations to the distance to work which occur in association with changing job or moving home. Switching to non-car commuting becomes much more likely (9.2 times) as the distance to work drops below three miles. High quality public transport links to employment centres are shown to encourage switches away from car commuting and mixed land uses are shown to encourage switches to active commuting (walking and cycling). Switches away from car commuting are found to be more likely (1.3 times) for those with a pro-environmental attitude. The attitude orientation is shown to precede the behaviour change, demonstrating evidence of ‘cause and effect’. Overall, the study shows that changes in commuting behaviour are strongly influenced by life events, spatial context and environmental attitude.     

Understanding job-housing relationship and commuting pattern in Chinese cities: Past,present and future

There are debates about whether job-housing balance and short commuting distances could be achieved through government intervention in Western countries. However, few studies have been carried out in developing context. The present study aims to fill in this knowledge vacuum by studying how China’s changing socio-spatial context, particularly the spatial ideas of danwei, influences job-housing relationships and commuting patterns from a historical perspective. The results clearly show that the dominant trend in commuting patterns in Chinese cities has changed from intra-danwei commuting before 1978 to reverse commuting from the city center to the inner suburbs in 1978–1998, to long-distance suburb-to-city commuting since 1998. The findings suggest that government intervention could be helpful in achieving shorter commute in China, and that urban planning and policy that promote mixed land-use and job-housing balance should be considered. Some limitations of government intervention are also discussed.     

Immigration, residential location, car ownership, and commuting behavior: a multivariate latent class analysis from California

Using latent class cluster analysis, this paper investigates the spatial, social, demographic, and economic determinants of immigrants’ joint distribution among travel time, mode choice, and departure time for work using the 2000 Census long form data. Through a latent tree structure analysis, age, residential location, immigration stage, gender, personal income, and race are found to be the primary determinants in the workplace commute decision-making process. By defining several relatively homogeneous population segments, the likelihood of falling into each segment is found to differ across age groups and geography, with different indicators affecting each group differentially. This analysis complements past studies that used regression models to investigate socio-demographic indicators and their impact on travel behavior in two distinct ways: (a) analysis is done by considering travel time, mode choice, and departure time for work simultaneously, and (b) heterogeneity in behavior is accounted for using methods that identify different groups of behavior and then their determinants. Conclusively the method here is richer than many other methods used to study the ethnically diverse population of California and shows the addition of geographic location and latent segment identification to greatly improve our understanding of specific behaviors. It also provides evidence that immigrants are as diverse as the non-immigrant population and transportation policies need to be defined accordingly.

The social context of informal commuting: Slugs, strangers and structuration

Despite considerable interest in the role of social interactions and social context on transportation, there have been very few attempts to explore specific cases of social interaction influencing transportation systems. This paper explores the social practice of slugging, an informal system of carpooling in the Washington, DC area. Slugging emerged in response to the establishment of Virginia’s High Occupancy Vehicle (HOV) lanes in the early 1970s, as single drivers picked up riders alongside the road (slugs) in order to meet the requirements for driving in the less congested HOV lanes. Drawing on the work of sociologist Anthony Giddens, as well as the sociological insights of Georg Simmel and Stanley Milgram, we suggest that the practice of slugging highlights the processes of institutionalization and structuration. This paper details how the region’s mass transportation policies and urban culture have combined to result in an institutionalized practice with particular norms and logics of behavior. We conclude that looking at specific cases where social context has affected transportation, like slugging, could provide useful insights on the impact of social context on transportation policies and systems.     

Car use,commuting and urban form in a rapidly growing city: evidence from Beijing

The links between urban form and travel behaviour have been widely studied in the field of travel demand management. However, the existing literature is dominated by case studies from the developed countries. A study of a city in a developing and industrialising country can add some fresh evidence to the debate on the impacts of urban form on travel patterns. Using household survey data from Beijing, this paper finds that aspects of urban form have significant effects on workers' car use and the duration of travel by car in journeys to work, while controlling for socio-economic factors and households’ preferences related to residential location. The sprawling patterns of land development play a negative role in reducing motorised commuting trips and shortening vehicle hours travelled in the current processes of rapid urban expansion and motorisation. Since urban sprawl is greatly influenced by growing market forces, the findings in this paper reveal the negative effects of regulation–liberation of land development management on travel behaviour modification.     

Evolution of latent modal captivity and mode choice patterns for commuting trips: A longitudinal analysis using repeated cross-sectional datasets

This paper presents an investigation of the temporal evolution of commuting mode choice preference structures. It contributes to two specific modelling issues: latent modal captivity and working with multiple repeated crossectional datasets. In this paper latent modal captivity refers to captive reliance on a specific mode rather than all feasible modes. Three household travel survey datasets collected in the Greater Toronto and Hamilton Area (GTHA) over a ten-year time period are used for empirical modelling. Datasets collected in different years are pooled and separate year-specific scale parameters and coefficients of key variables are estimated for different years. The empirical model clearly explains that there have been significant changes in latent modal captivity and the mode choice preference structures for commuting in the GTHA. Changes have occurred in the unexplained component of latent captivities, in transportation cost perceptions, and in the scales of commuting mode choice preferences. The empirical model also demonstrates that pooling multiple repeated cross-sectional datasets is an efficient way of capturing behavioural changes over time. Application of the proposed mode choice model for practical policy analysis and forecasting will ensure accurate forecasting and an enhanced understanding of policy impacts.     

Employment suburbanisation, reverse commuting and travel behaviour by residents of the central city in the Paris metropolitan area

This paper analyses the relationship between employment suburbanisation in the Paris metropolitan area, the growth of reverse commuting and changes in the weekday travel behaviour of working residents of the central city over a 20-year period. The results show that the number of reverse commuters has significantly increased because the municipality of Paris has lost many jobs but few working residents whilst employment has developed in the suburbs. Reverse commuters are mainly and increasingly high-income professionals whose workplace is located close to the central city in employment sub-centres that are well served by public transport. Consequently reverse commuters have lower than average car use although differences exist and are related to their professional status. The policy implications of these findings are discussed in the conclusion.     

Examining the effects of the built environment and residential self-selection on commuting trips and the related CO2 emissions: An empirical study in Guangzhou,China

Numerous studies have established the link between the built environment and travel behavior. However, fewer studies have focused on environmental costs of travel (such as CO₂ emissions) with respect to residential self-selection. Combined with the application of TIQS (Travel Intelligent Query System), this study develops a structural equations model (SEM) to examine the effects of the built environment and residential self-selection on commuting trips and their related CO₂ emissions using data from 2015 in Guangzhou, China. The results demonstrate that the effect of residential self-selection also exists in Chinese cities, influencing residents’ choice of living environments and ultimately affecting their commute trip CO₂ emissions. After controlling for the effect of residential self-selection, built environment variables still have significant effects on CO₂ emissions from commuting although some are indirect effects that work through mediating variables (car ownership and commuting trip distance). Specifically, CO₂ emissions are negatively affected by land-use mix, residential density, metro station density and road network density. Conversely, bus stop density, distance to city centers and parking availability near the workplace have positive effects on CO₂ emissions. To promote low carbon travel, intervention on the built environment would be effective and necessary.     

Water transit and excess travel: discrete choice modelling of bus and ferry trips in Brisbane,Australia

Recent investment in urban ferry transport has created interest in what value such systems provide in a public transport network. In some cases, ferry services are in direct competition with other land-based transport, and despite often longer travel times passengers still choose water transport. This paper seeks to identify a premium attached to urban water transit through an identification of excess travel patterns. A one-month sample of smart card transaction data for Brisbane, Australia, was used to compare bus and ferry origin–destination pairs between a selected suburban location and the central business district. Logistic regression of the data found that ferry travel tended towards longer travel times (OR?=?2.282), suggesting passengers do derive positive utility from ferry journeys. The research suggests the further need to incorporate non-traditional measures other than travel time for deciding the value of water transit systems.     

Use of a novel dataset to explore spatial and social variations in car type,size, usage and emissions

The ’MOT’ vehicle inspection test record dataset recently released by the UK Department for Transport (DfT) provides the ability to estimate annual mileage figures for every individual light duty vehicle greater than 3 years old within Great Britain. Vehicle age, engine size and fuel type are also provided in the dataset and these allow further estimates to be made of fuel consumption, energy use, and per vehicle emissions of both air pollutants and greenhouse gases. The use of this data permits the adoption of a new vehicle-centred approach to assessing emissions and energy use in comparison to previous road-flow and national fuel consumption based approaches. The dataset also allows a spatial attribution of each vehicle to a postcode area, through the reported location of relevant vehicle testing stations. Consequently, this new vehicle data can be linked with socio-demographic data in order to determine the potential characteristics of vehicle owners.This paper provides a broad overview of the types of analyses that are made possible by these data, with a particular focus on distance driven and pollutant emissions. The intention is to demonstrate the very broad potential for this data, and to highlight where more focused analysis could be useful. The findings from the work have important implications for understanding the distributional impacts of transport related policies and targeting messaging and interventions for the reduction of car use.     

Environmental impacts of transformative land use and transport developments in the Greater Beijing Region: Insights from a new dynamic spatial equilibrium model

This paper reports the insights into environmental impacts of the ongoing transformative land use and transport developments in Greater Beijing, from a new suite of dynamic land use, spatial equilibrium and strategic transport models that is calibrated for medium to long term land use and transport predictions. The model tests are focused on urban passenger travel demand and associated emissions within the municipality of Beijing, accounting for Beijing’s land use and transport interactions with Tianjin, Hebei and beyond. The findings suggests that background trends of urbanization, economic growth and income rises will continue to be very powerful drivers for urban passenger travel demand across all main modes of transport beyond 2030. In order to achieve the dual policy aims for a moderately affluent and equitable nation and reducing the absolute levels of urban transport emissions by 2030, road charging and careful micro-level coordination between land use, built form and public transport provision may need to be considered together for policy implementation in the near future.     

Social and spatial effects of transforming the private vehicle fleet in Brisbane,Australia

Transformation of the motor vehicle fleet has been an important feature of the world’s peak car phenomenon. Very few urban transport studies have explored such important changes in large urban cities. Using an innovative green vehicle datasets constructed for 2009 and 2014, this paper investigates the ongoing change in urban private vehicle fleet efficiency (VFE) in Brisbane. The spatial patterns of VFE change were examined with social-spatial characteristics of the urban area. The results showed that the social and spatial effect of VFE changes remain uneven over urban space. The inner urban areas have experienced higher level of VFE change, whilst people in the outer and oil vulnerable areas showed a low tendency in shifting to more efficient vehicles. The implication of VFE change for future household vehicle adoption was also evaluated based on a cost-benefit analysis of new vehicle technology costs and expected fuel savings for households that choose a fuel efficient vehicle. The results show that imposing a stronger national fuel economy target in the long term would accelerate evolution of vehicle fleets and oil vulnerability reduction in Brisbane.     

Urban single-lane roundabouts: A new analytical approach using multi-criteria and simultaneous multi-objective optimization of geometry design,efficiency and safety

Building safe and effective roundabouts requires optimizing traffic (operational) efficiency (TE) and traffic safety (TS) while taking into account geometric factors, traffic characteristics and local constraints. Most existing simulation-based optimization models do not simultaneously optimize all these factors. To capture the relationship among geometry, efficiency and safety, we put forward a model formulation in this paper. We present a new multi-criteria and simultaneous multi-objective optimization (MOO) model approach to optimize geometry, TE and TS of urban unsignalized single-lane roundabouts. To the best of our knowledge, this is the first model that uses the multi-criteria decision-making method known as analytic hierarchy process to evaluate and rank traffic parameters and geometric elements of urban single-lane roundabouts. The model was built based on comprehensive review of the research literature and existing roundabout simulation software, a field survey of 61 civil and traffic expert engineers in Croatia, and field studies of roundabouts in the Croatian capital city of Zagreb. We started from the basis of Kimber’s capacity model, HCM2010 serviceability model, and Maycock and Hall's accident prediction model, which we extended by adding sensitivity analysis and powerful MOO procedures of the bounded objective function method and interactive optimization. Preliminary validation of the model was achieved by identifying the optimal and most robust of three geometric alternatives (V.1-V.3) for an unsignalized single-lane roundabout in Zagreb, Croatia. The geometric parameters in variant V.1 had significantly higher values than in the existing design V.0, while approaches 1 and 3 in variant V.2 were enlarged as much as possible within allowed spatial limits and Croatian guidelines, reflecting their higher traffic demand. Sensitivity analysis indicated that variant V.2 showed the overall highest TE and TS across the entire range of traffic flow demand and pedestrian crossing flow demand at approaches. At the same time, the number of predicted traffic accidents was similar for all three variants, although it was lowest overall for V.2. The similarity in predicted accident frequency for the three variants suggests that V.2 provides the greatest safety within the predefined constraints and parameter ranges explored in our study. These preliminary results suggest that the proposed model can optimize geometry, TE and TS of urban single-lane roundabouts.