Future use of stage bus services

The reasons underlying the decline of stage bus services in the U.K. over the past 30 years seem to be well understood, and the probable future trends have been projected using a quantitative forecasting model. The model considers U.K. bus services at a very aggregate level, but it breaks the demand into specific user groups: work trips, children's travel, travel by the elderly, and all other travel, and separately for households with and without a private car. Forecasts depend very sensitively on the level of economic growth assumed, since this governs the two major factors which determine public transport use — car ownership and the cost of operating the services. If the economy could recover its historic growth rates, a further substantial decline in bus use seems inevitable under most realistic assumptions. However, with the present economic outlook, a lower growth rate seems likely to persist for some time, and in this case public transport use will become much more stable in the 1990's; a tendency which would be helped if there were large increases in fuel prices. Many of the Metropolitan Counties have adopted policies of strongly restraining future rises in fares, in some cases to the extent of freezing fares in monetary terms. The effects of such policies on both patronage and subsidies are considered here, and although much of the current political attention is focussed on controlling fares, the question of balance between fares and service levels is also discussed. Lastly, it must be admitted that these predictions are based on knowledge which is largely restricted to the short-term effects of transport policies. The nature of our uncertainty about longer-term effects, and the possible size of them, is considered in terms of sensitivity-testing of the prediction model.     

An investigation into the feasibility of increasing rail use as an alternative to the car

With rail travel largely seen to be a more sustainable method than road-based transport, this paper examines the market segments amongst existing motorists that would be most likely to travel by train in the UK. The analysis is based on a large survey in London and the south-east of England, the area surrounding the routes operated by the train company First Capital Connect. Findings show that train travellers tend to be middle-aged and of a higher social grade, typically taking commuting or business trips. Individuals living within four miles of a station are considerably more likely to travel by rail than those further away. Given the competition from road-based transport, it is of particular interest that the measure highlighted to increase rail use for those living further away from the rail network is to enhance car parking at train stations.     

A direct demand model for downtown work trips

This article documents the development of a direct travel demand model for bus and rail modes. In the model, the number of interzonal work trips is dependent on travel times and travel costs on each available mode, size and socioeconomic characteristics of the labor force, and the number of jobs. In estimating the models’ coefficients constraints are imposed to insure that the travel demand elasticities behave according to the economic theory of consumer behavior. The direct access time elasticities for both transit modes are estimated to be approximately minus two, and the direct linehaul time elasticities approximately minus one. The cross-elasticities with respect to the travel time components are estimated to be less than the corresponding direct elasticities. In general, the time cross-elasticities are such that rail trip characteristics but not car trip characteristics affect bus travel, and car trip characteristics but not bus trip characteristics affect rail travel. The cost elasticities lie between zero and one-half. Thus, the success of mass transit serving a strong downtown appears to depend on good access arrangements. This success can be confirmed with competitive linehaul speeds. The cost of travel appears to assume a minor role in choice of mode and tripmaking decisions. In the paper, a comparison is also made between the predictive performance of the models developed and that of a traditional transit model. The results indicate that the econometric models developed attain both lower percent error and lower variation of the error than the traditional model.     

Neighborhoods,cars, and commuting in New York City: A discrete choice approach

Cities around the world are trying out a multitude of transportation policy and investment alternatives with the aim of reducing car-induced externalities. However, without a solid understanding of how people make their transportation and residential location choices, it is hard to tell which of these policies and investments are really doing the job and which are wasting precious city resources. The focus of this paper is the determinants of car ownership and car use for commuting. Using survey data from 1997 to 1998 collected in New York City, this paper uses discrete choice econometrics to estimate a model of the choices of car ownership and commute mode while also modeling the related choice of residential location.The main story told by this analysis is that New Yorkers are more sensitive to changes in travel time than they are to changes in travel cost. The model predicts that the most effective ways to reduce both auto ownership and car commuting involve changing the relative travel times for cars and transit, making transit trips faster by increasing both the frequency and the speed of service and making auto trips slower – perhaps simply by allowing traffic congestion. Population density also appears to have a substantial effect on car ownership in New York.     

The spatial distribution of journey-to-work trips in Greater London

Although a great deal is known about the distribution of homes and the distribution of workplaces in Greater London, the spatial relationship between them is less well understood. Using 1966 census data, the authors try to give a simple visual picture of this relationship, and to assess the relative travel intensities which would arise at different points in London from commuter trips, assuming straight line routing.The results show firstly that a large proportion of the population work quite close to their homes, with radial travel towards the city centre being only slightly more prominent than other directions of movement. The remainder tend to work near the city centre and to travel much longer distances. Secondly, relative to various annuli at 2 km increments centred on Charing Cross, the amounts of through traffic expressed as a proportion of the totals are roughly constant for radii between 4 and 14 km. Thirdly, people's choice of home in relation to their workplace is, on the whole, quite efficient, since it gives rise to a total amount of travel which is much closer to the theoretical minimum than it is to the amount corresponding to a random choice of homes from the available stock.     

Uncertain benefits: Application of Bayesian melding to the Alaskan Way Viaduct in Seattle

Uncertainty is inherent in major infrastructure projects, but public decision-making for such projects ignores it. We investigate the uncertainty about the future effects of tearing down the Alaskan Way Viaduct in downtown Seattle, using an integrated model of housing, jobs, land use and transportation, on outcomes including average commute times. Our methodology combines the urban simulation model UrbanSim with the regional transportation model. We assess uncertainty using Bayesian melding, yielding a full predictive distribution of average commute times on 22 different routes in 2020. Of these routes, 14 do not include the viaduct and eight do. For the 14 base routes that do not include the viaduct, the predictive distributions overlap substantially, and so there is no indication that removing the viaduct would increase commute times for these routes. For each of the eight routes that do include the viaduct, the 95% predictive interval for the difference in average travel times between the two scenarios includes zero, so there is not strong statistical support for the conclusion that removing the viaduct would lead to any increase in travel times. However, the median predicted increase is positive for each of these routes, with an average of 6 min, suggesting that there may be some measurable increase in travel time for drivers that use the viaduct as a core component of their commute.     

The cost of equity: Assessing transit accessibility and social disparity using total travel cost

Social equity is increasingly incorporated as a long-term objective into urban transportation plans. Researchers use accessibility measures to assess equity issues, such as determining the amount of jobs reachable by marginalized groups within a defined travel time threshold and compare these measures across socioeconomic categories. However, allocating public transit resources in an equitable manner is not only related to travel time, but also related to the out-of-pocket cost of transit, which can represent a major barrier to accessibility for many disadvantaged groups. Therefore, this research proposes a set of new accessibility measures that incorporates both travel time and transit fares. It then applies those measures to determine whether people residing in socially disadvantaged neighborhoods in Montreal, Canada experience the same levels of transit accessibility as those living in other neighborhoods. Results are presented in terms of regional accessibility and trends by social indicator decile. Travel time accessibility measures estimate a higher number of jobs that can be reached compared to combined travel time and cost measures. However, the degree and impact of these measures varies across the social deciles. Compared to other groups in the region, residents of socially disadvantaged areas have more equitable accessibility to jobs using transit; this is reflected in smaller decreases in accessibility when fare costs are included. Generating new measures of accessibility combining travel time and transit fares provides more accurate measures that can be easily communicated by transportation planners and engineers to policy makers and the public since it translates accessibility measures to a dollar value.     

When strike comes to town… anticipated and actual behavioural reactions to a one-day,pre-announced,complete rail strike in the Netherlands

We conducted secondary analysis on data collected among rail users, days before and after a national rail strike in the Netherlands. Our aim was to compare anticipated and actual behavioural reactions to the rail strike, investigate associations with traveller and trip characteristics, and perceived behavioural control and satisfaction with the chosen alternative. Forty-four percent of the people who had anticipated to travel by train on the day of the strike abandoned their trip, 24% switched to car as driver, 14% switched to another mode (as passenger), 18% stayed with the train and rescheduled the planned activity to another day. Almost half of people who had anticipated travelling by car expected to change behaviour as well. Multinomial logistic regression showed low preference for car among rail users. Considerable marginal effects were found for several variables, e.g.: young people and females were less likely to switch to car; short and middle distance trips were less likely abandoned or switched to another day; commute and business trips were more likely done by car, and business trips less likely cancelled. Despite high levels of perceived behavioural control and satisfaction with the chosen alternative, permanent modal shift as result of this strike is not expected.     

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

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

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.     

The determinants of long distance travel in Great Britain

This study analyses of the determinants of long distance travel in Great Britain using data from the 1995-2006 National Travel Surveys (NTSs). The main objective is to determine the effects of socio-economic, demographic and geographic factors on long distance travel. The estimated models express the distance travelled for long distance journeys as a function of income, gender, age, employment status, household characteristics, area of residence, size of municipality, type of residence and length of time living in the area. A time trend is also included to capture common changes in long distance travel over time not included in the explanatory variables. Separate models are estimated for total travel, travel by each of four modes (car, rail, coach and air), travel by five purposes (business, commuting, leisure, holiday and visiting friends and relatives (VFRs)) and two journey lengths (<150 miles and 150+ miles one way), as well as the 35 mode-purpose-distance combinations.The results show that long distance travel is strongly related to income: air is most income-elastic, followed by rail, car and finally coach. This is the case for most journey purposes and distance bands. Notable is the substantial difference in income elasticities for rail for business/commuting as opposed to holiday/leisure/VFR. In addition, the income elasticity for coach travel is very low, and zero for the majority of purpose-distance bands, suggesting coach travel to be an inferior mode in comparison to car, rail and air. Regarding journey distance, we find that longer distance journeys are more income elastic than shorter journeys.For total long distance travel, the study indicates that women travel less than men, the elderly less than younger people, the employed and students more than others, those in one adult households more than those in larger households and those in households with children less than those without. Long distance travel is also lowest for individuals living in London and greatest for those in the South West, and increases as the size of the municipality declines.     

The effect of attitudes toward cars and public transportation on behavioral intention in commuting mode choice—A comparison across six Asian countries

This study investigated the contribution of psychological factors in explaining the choice of transportation mode in six Asian countries. Data were collected from 1118 respondents in Japan, Thailand, China, Vietnam, Indonesia, and the Philippines. The dependent variable was the intention to use one of three modes for work travel after getting a job: car, public transit, or other modes. The explanatory variables were three attitude factors taken from a previous study, including: 1/symbolic affective, reflecting affective motives of travel mode use; 2/instrumental, referring to functional attributes of travel modes; and 3/social orderliness which represents for environmental friendliness, safety, altruism, quietness et cetera. Several logit model estimates were made using the samples from the six countries separately and together. We obtained three main findings. First, attitude variables about the car were all significant determinants for the entire sample from Asian countries. Second, the social orderliness aspect of public transit was a common concern of respondents from developing countries in selecting this mode for work trips. Third, in countries in which the intent to use a car was not very high, attitude factors about the car were found to be significant determinants of the behavioral intention to commute by car but were less significant in countries in which the desire to use a car was high.     

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

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

Is climate morality the answer? Preconditions affecting the motivation to decrease private car use

Persuasive messages are commonly used in campaigns promoting sustainable transport to motivate people to reduce private car use. This paper explores the preconditions affecting the motivation of people to reduce private car use when exposed to such messages. A sample of 1100 Swedish residents was analysed for the effect of variables related to accessibility, usual commute mode and attitudes. Significant variables were used to create a precondition index, which was cross-tabulated with demographic variables and stages drawn from the transtheoretical model. The results show that there are differences in the preconditions regarding motivation to reduce private car use between segments of the population. Results indicate that climate morality is the most critical factor affecting motivation, specifically the motivation of persistent drivers. Usual commute mode, car advocacy, health concern, attitudes towards cycling, car identity and travel time also influence motivation. Males, the middle-aged, people with low educational attainment, and rural residents have the least favourable preconditions concerning motivation to reduce private car use.     

The impact of transit station areas on the travel behaviors of workers in Denver,Colorado

Transit development is one planning strategy that seeks to partially overcome limitations of low-density single use car oriented development styles. While many studies focus on how residential proximity to transit influences the travel behaviors of individuals, the effect of workplace proximity to transit is less understood. This paper asks, does working near a light rail transit station influence the travel behaviors of workers differently than workers living near a station? We begin by examining workers’ commute mode based on their residential and workplace proximity to transit station areas. Next, we analyze the ways in which personal travel behaviors differ between those who drive to work and those who do not. The data came from a 2009 travel behavior survey in the Denver, Colorado metropolitan area, which contains 8000 households, 16,000 individuals, and nearly 80,000 trips. We measure sustainable travel behaviors as reduced mileage, reduced number of trips, and increased use of non-car transportation. The results of this study indicate that living near a transit station area by itself does not increase the likelihood of using non-car modes for work commutes. But if the destination (work) is near a transit station area, persons are less likely to drive a car to work. People who both live and work in a transit station area are less likely to use a car and more likely to take non-car modes for both work and non-work (personal) trips. Especially for persons who work near a transit station area, the measures of personal trips and distances show a higher level of mobility for non-car commuters than car commuters – that is, more trips and more distant trips. The use of non-car modes for personal trips is most likely to occur by non-car commuters, regardless of their transit station area relationship.     

Commuting and wellbeing: a critical overview of the literature with implications for policy and future research

ABSTRACT

This review provides a critical overview of what has been learnt about commuting’s impact on subjective wellbeing (SWB). It is structured around a conceptual model which assumes commuting can affect SWB over three time horizons: (i) during the journey; (ii) immediately after the journey; and (iii) over the longer term. Our assessment of the evidence shows that mood is lower during the commute than other daily activities and stress can be induced by congestion, crowding and unpredictability. People who walk or cycle to work are generally more satisfied with their commute than those who travel by car and especially those who use public transport. Satisfaction decreases with duration of commute, regardless of mode used, and increases when travelling with company. After the journey, evidence shows that the commute experience “spills over” into how people feel and perform at work and home. However, a consistent link between commuting and life satisfaction overall has not been established. The evidence suggests that commuters are generally successful in trading off the drawbacks of longer and more arduous commute journeys against the benefits they bring in relation to overall life satisfaction, but further research is required to understand the decision making involved. The evidence review points to six areas that warrant policy action and research: (i) enhancing the commute experience; (ii) increasing commute satisfaction; (iii) reducing the impacts of long duration commutes; (iv) meeting commuter preferences; (v) recognising flexibility and constraints in commuting routines and (vi) accounting for SWB impacts of commuting in policy making and appraisal.     

Accounting for travel time variability in the optimal pricing of cars and buses

A number of studies have shown that in addition to travel time and cost as the common influences on mode, route and departure time choices, travel time variability plays an increasingly important role, especially in the presence of traffic congestion on roads and crowding on public transport. The dominant focus of modelling and implementation of optimal pricing that incorporates trip time variability has been in the context of road pricing for cars. The main objective of this paper is to introduce a non-trivial extension to the existing literature on optimal pricing in a multimodal setting, building in the role of travel time variability as a source of disutility for car and bus users. We estimate the effect of variability in travel time and bus headway on optimal prices (i.e., tolls for cars and fares for buses) and optimal bus capacity (i.e., frequencies and size) accounting for crowding on buses, under a social welfare maximisation framework. Travel time variability is included by adopting the well-known mean–variance model, using an empirical relationship between the mean and standard deviation of travel times. We illustrate our model with an application to a highly congested corridor with cars, buses and walking as travel alternatives in Sydney, Australia. There are three main findings that have immediate policy implications: (i) including travel time variability results in higher optimal car tolls and substantial increases in toll revenue, while optimal bus fares remain almost unchanged; (ii) when bus headways are variable, the inclusion of travel time variability as a source of disutility for users yields higher optimal bus frequencies; and (iii) including both travel time variability and crowding discomfort leads to higher optimal bus sizes.     

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.     

A practical approach to identifying the market potential for high speed rail: A case study in the Sydney-Canberra corridor

This paper presents the methodology and selective empirical results from a study of the demand for a high speed rail system serving the Sydney-Canberra corridor currently dominated by air travel for business trips and car travel for non-business trips. We outline the steps involved in the study from problem specification, data needs, development of base year trip tables, model specification and estimation to establish switching behaviour in the presence of a new mode and calculation of induced demand for current travellers. A stated choice heteroskedastic extreme value switching model is used to evaluate the choice of fare type for business and non-business travel given the current mode used in the corridor for each sampled traveller conventional train, charter coach, scheduled coach, plane or car. Starting with the current travel profile, patronage can be predicted under alternative fare regimes, taking into account diverted traffic, induced traffic and growth. Treating fare class as endogenous enhances the real choice context facing potential patrons.