Showing papers in "Transportation in 2011"
TL;DR: In a survey of 1,402 current and potential cyclists in Metro Vancouver, 73 motivators and deterrents of cycling were evaluated as discussed by the authors, and the top motivators were: routes away from traffic noise and pollution; routes with beautiful scenery; and paths separated from traffic.
Abstract: In a survey of 1,402 current and potential cyclists in Metro Vancouver, 73 motivators and deterrents of cycling were evaluated. The top motivators, consistent among regular, frequent, occasional and potential cyclists, were: routes away from traffic noise and pollution; routes with beautiful scenery; and paths separated from traffic. In factor analysis, the 73 survey items were grouped into 15 factors. The following factors had the most influence on likelihood of cycling: safety; ease of cycling; weather conditions; route conditions; and interactions with motor vehicles. These results indicate the importance of the location and design of bicycle routes to promote cycling.
495 citations
TL;DR: In this article, an integrated simultaneous multi-dimensional choice model of residential location, auto ownership, bicycle ownership, and commute tour mode choices using a mixed multidimensional choice modeling methodology is presented.
Abstract: The integrated modeling of land use and transportation choices involves analyzing a continuum of choices that characterize people’s lifestyles across temporal scales. This includes long-term choices such as residential and work location choices that affect land-use, medium-term choices such as vehicle ownership, and short-term choices such as travel mode choice that affect travel demand. Prior research in this area has been limited by the complexities associated with the development of integrated model systems that combine the long-, medium- and short-term choices into a unified analytical framework. This paper presents an integrated simultaneous multi-dimensional choice model of residential location, auto ownership, bicycle ownership, and commute tour mode choices using a mixed multidimensional choice modeling methodology. Model estimation results using the San Francisco Bay Area highlight a series of interdependencies among the multi-dimensional choice processes. The interdependencies include: (1) self-selection effects due to observed and unobserved factors, where households locate based on lifestyle and mobility preferences, (2) endogeneity effects, where any one choice dimension is not exogenous to another, but is endogenous to the system as a whole, (3) correlated error structures, where common unobserved factors significantly and simultaneously impact multiple choice dimensions, and (4) unobserved heterogeneity, where decision-makers show significant variation in sensitivity to explanatory variables due to unobserved factors. From a policy standpoint, to be able to forecast the “true” causal influence of activity-travel environment changes on residential location, auto/bicycle ownership, and commute mode choices, it is necessary to capture the above-identified interdependencies by jointly modeling the multiple choice dimensions in an integrated framework.
378 citations
TL;DR: In this article, the authors investigated whether satisfaction with daily travel has a positive impact on subjective well-being, either directly or indirectly through facilitating the performance of out-of-home activities.
Abstract: Previous research demonstrates an impact on subjective well-being (SWB) of affect associated with routine performance of out-of-home activities. A primary aim of the present study is to investigate whether satisfaction with daily travel has a positive impact on SWB, either directly or indirectly through facilitating the performance of out-of-home activities. A secondary aim is to determine whether emotional-symbolic or instrumental reasons for car use results in higher satisfaction with daily travel than other travel modes. A survey of a population-based sample of 1,330 Swedish citizens included measures of car access and use, satisfaction with daily travel, satisfaction with performance of out-of-home routine activities, and affective and cognitive SWB. The results confirmed that the effect on affective and cognitive SWB of satisfaction with daily travel is both direct and indirect via satisfaction with performance of activities. Percent weekly car use had a small effect on satisfaction with daily travel and on affective SWB, although fully mediating the effect of satisfaction with performance of the activities. This suggests that car use plays a minor role for satisfaction with daily travel and its effect on SWB. This role may be larger if investigated after a forced reduced car use.
261 citations
TL;DR: In this article, a multi-dimensions measurement of transport infrastructure and examines the linkage between transportation infrastructure and regional economic growth is presented. But, the results provide strong evidence that transport infrastructure plays an important role in economic growth, while airway transport infrastructure is weak.
Abstract: This article develops a multi-dimensions measurement of transport infrastructure and examines the linkage between transport infrastructure and regional economic growth. A panel data model is estimated using data from a sample of 31 Chinese provinces from 1998 to 2007. The results provide strong evidence that transport infrastructure plays an important role in economic growth. Both land transport and water transport infrastructure have strong and significant impacts, while the contribution of airway transport infrastructure is weak. Furthermore, land transport infrastructure contributes more to economic growth in locations with poor land transport infrastructure, while the investment in water transport infrastructure contribute positively to economic growth only after the investment scale exceeds a threshold level. These results are robust to a variety of alternative methods, the exclusion of possible outliers, and consideration of endogeneity. A retrospective analysis shows that uneven distribution of transport infrastructure is an important reason behind economic disparities across Chinese regions.
170 citations
TL;DR: In this paper, a causal relationship model that considers the service quality-satisfaction-behavioral intentions paradigm, perceived value theory, and switching barrier theory was proposed to improve passengers' behavioral intention.
Abstract: This paper seeks to improve our understanding of passengers’ behavioral intention by proposing an integrated framework from the attitudinal perspective. According to the literature in marketing research, we establish a causal relationship model that considers “service quality-satisfaction-behavioral intentions” paradigm, perceived value theory, and switching barrier theory. Exploring passengers’ behavioral intention from satisfaction and perceived value help to understand how passengers are attracted by the company, while switching barriers assist in realizing how passengers are “locked” into a relationship with the current company. Furthermore, in order to capture the nature of service quality, we adopt a hierarchical factor structure which serves service quality as the higher-order factor. In this study, coach industry is selected as our research subject. The empirical results, as hypothesized, show that all causal relationships are statistically significant, and perceived value us the most important predictor of satisfaction and passengers’ behavioral intention. In conclusion, the managerial implications and suggestions for future research are discussed.
169 citations
TL;DR: In this paper, a multiple group structural equation model (SEM) was used to model the relationship between land use and commuting in Ghent (Belgium) and found that car use and commute times significantly differ between commuting trips within work-only tours and more complex tours.
Abstract: 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.
161 citations
TL;DR: In this article, the costs of carsharing and vehicle ownership are compared based on actual vehicle usage patterns from a large survey of San Francisco Bay Area residents, and the results of this analysis show that a significant minority of Bay Area households own a vehicle with a usage pattern that car-sharing could accommodate at a lower cost.
Abstract: Carsharing is a vehicle sharing service for those with occasional need of private transportation. Transportation planners are beginning to see great potential for carsharing in helping to create a more diversified and sustainable transport system. While it has grown quickly in the US in recent years, it is still far from the level where it can deliver significant aggregate benefits. A key element to the potential growth of carsharing is its ability to provide cost savings to those who adopt it in favor of vehicle ownership. This research seeks to quantify these potential cost savings. The costs of carsharing and vehicle ownership are compared based on actual vehicle usage patterns from a large survey of San Francisco Bay Area residents. The results of this analysis show that a significant minority of Bay Area households own a vehicle with a usage pattern that carsharing could accommodate at a lower cost. Further research is required to indentify how these cost savings translate to the adoption of carsharing.
90 citations
TL;DR: In this article, a sensitivity analysis-based approach is proposed to improve computational efficiency and allow for large-scale applications of road network vulnerability analysis, which significantly reduces computational burden and memory storage requirements compared with the traditional approach.
Abstract: Traditionally, an assessment of transport network vulnerability is a computationally intensive operation. This article proposes a sensitivity analysis-based approach to improve computational efficiency and allow for large-scale applications of road network vulnerability analysis. Various vulnerability measures can be used with the proposed method. For illustrative purposes, this article adopts the relative accessibility index (AI), which follows the Hansen integral index, as the network vulnerability measure for evaluating the socio-economic effects of link (or road segment) capacity degradation or closure. Critical links are ranked according to the differences in the AIs between normal and degraded networks. The proposed method only requires a single computation of the network equilibrium problem. The proposed technique significantly reduces computational burden and memory storage requirements compared with the traditional approach. The road networks of the Sioux Falls city and the Bangkok metropolitan area are used to demonstrate the applicability and efficiency of the proposed method. Network manager(s) or transport planner(s) can use this approach as a decision support tool for identifying critical links in road networks. By improving these critical links or constructing new bypass roads (or parallel paths) to increase capacity redundancy, the overall vulnerability of the networks can be reduced.
73 citations
TL;DR: In this article, the authors show that there is a nonlinearity in the relationship between accessibility and productivity with no positive effect to be discerned over broad ranges of the data.
Abstract: The case for including agglomeration benefits within transport appraisal rests on an assumed causality between access to economic mass and productivity. Such causality is justified by the theory of agglomeration, but is difficult to establish empirically because estimates may be subject to sources of bias from endogeneity and confounding. The paper shows that conventional panel methods used to address these problems are unreliable due to the highly persistent nature of accessibility measures. Adopting an alternative approach, by applying semiparametric techniques to restricted sub-samples of the data, we find considerable nonlinearity in the relationship between accessibility and productivity with no positive effect to be discerned over broad ranges of the data. A key conclusion is that we are unable to distinguish the role of accessibility from other potential explanations for productivity increases. For transport appraisal, this implies that the use of conventional point elasticity estimates could be highly misleading.
70 citations
TL;DR: In this paper, a short turning model using demand information from station to station within a single bus line-single period setting, aimed at increasing the service frequency on the more loaded sections to deal with spatial concentration of demand considering both operators and users' costs.
Abstract: We develop a short turning model using demand information from station to station within a single bus line-single period setting, aimed at increasing the service frequency on the more loaded sections to deal with spatial concentration of demand considering both operators’ and users’ costs. We find analytical expressions for optimal values of the design variables, namely frequencies (inside and outside the short cycle), capacity of vehicles and the position of the short turn limit stations. These expressions are used to analyze the influence of different parameters in the final solution. The design variables and the corresponding cost components for operators and users (waiting and in-vehicle times) are compared against an optimized normal operation scheme (single frequency). Applications on actual transit corridors exhibiting different demand profiles are conducted, calculating the optimal values for the design variables and the resulting benefits for each case. Results show the typical demand configurations that are better served using a short turn strategy.
69 citations
TL;DR: In this paper, a factor analysis methodology was used to condense scores on 23 statements related to daily travel into six factors, and the factor scores on these six dimensions were used in conjunction with traveler socioeconomics, travel times, and costs to estimate a binary logistic regression of public transit choice.
Abstract: The commute mode choice decision is one of the most fundamental aspects of daily travel. Although initial research in this area was limited to explaining mode choice behavior as a function of traveler socioeconomics, travel times, and costs, subsequent studies have included the effect of traveler attitudes and perceptions. This paper extends the existing body of literature by examining public transit choice in the Chicago area. Data from a recent Attitudinal Survey conducted by the Regional Transportation Authority (RTA) in Northeastern Illinois were used to pursue three major steps. First, a factor analysis methodology was used to condense scores on 23 statements related to daily travel into six factors. Second, the factor scores on these six dimensions were used in conjunction with traveler socioeconomics, travel times, and costs to estimate a binary logistic regression of public transit choice. Third, elasticities of transit choice to the six factors were computed, and the factors were ranked in decreasing order of these elasticities. The analysis provided two major findings. First, from a statistical standpoint, the attitudinal factors improved the intuitiveness and goodness-of-fit of the model. Second, from a policy standpoint, the analysis indicated the importance of word-of-mouth publicity in attracting new riders, as well as the need for a marketing message that emphasizes the lower stress level and better commute time productivity due to transit use.
TL;DR: In this paper, the authors provide an overview of the various directions an equity analysis, carried out within the context of a social cost-benefit analysis, could take, and suggest that the equity analysis of transport projects should focus first and foremost on the mobility-enhancing benefits generated by such projects.
Abstract: While distributive aspects have been a topic of discussion in relation to cost–benefit analysis (CBA), little systematic thought has been given in the CBA literature to the focus of such an equity analysis in evaluating transport projects. The goal of the paper is to provide an overview of the various directions an equity analysis, carried out within the context of a social cost–benefit analysis, could take. The paper starts from the widely-shared definition of distributive justice: the morally proper distribution of goods and bads over members of society. Following this definition, carrying out an equity analysis requires that decisions are made about: (1) the benefits and costs that are distributed through a transport project; (2) the members of society between whom benefits and costs are distributed; and (3) the distributive principle that determines whether a particular distribution is fair. Much of the discussions about cost–benefit analysis and equity do not address these questions in any systematic way. The paper aims to provide a framework. Three sets of benefits and costs are identified as a possible focus of an equity analysis: (1) net benefits; (2) mobility-enhancing benefits; and (3) individual benefits and costs. For each set, a discussion follows regarding the way in which members of societies could be divided into meaningful groups, as well as the possible yardstick for judging whether a certain distribution is fair. While the paper acknowledges that the choice between the three sets is ultimately a political decision, it ends with a set of arguments that suggest that the equity analysis of transport projects should focus first and foremost on the mobility-enhancing benefits generated by such projects.
TL;DR: In this paper, the authors established a link between an activity-based model for the Greater Toronto Area (GTA), dynamic traffic assignment, emission modelling, and air quality simulation, and provided agent-based output that allows vehicle emissions to be tracked back to individuals and households who are producing them.
Abstract: This paper establishes a link between an activity-based model for the Greater Toronto Area (GTA), dynamic traffic assignment, emission modelling, and air quality simulation. This provides agent-based output that allows vehicle emissions to be tracked back to individuals and households who are producing them. In addition, roadway emissions are dispersed and the resulting ambient air concentrations are linked with individual time-activity patterns in order to assess population exposure to air pollution. This framework is applied to evaluate the effects of a range of policy interventions and 2031 scenarios on the generation of vehicle emissions and greenhouse gases in the GTA. Results show that the predicted increase of approximately 2.6 million people and 1.3 million jobs in the region by 2031 compared to 2001 levels poses a major challenge in achieving meaningful reductions in GHGs and air pollution.
TL;DR: In this article, the authors explored the influence of factors on light rail ridership on 57 light rail routes in Australia, Europe and North America through an empirical examination of route level data.
Abstract: This paper explores the relative influence of factors affecting light rail ridership on 57 light rail routes in Australia, Europe and North America through an empirical examination of route level data. Previous research suggests a wide range of possible ridership drivers but is mixed in clarifying major influences. A multiple-regression analysis of route level ridership (boardings per route km) and catchment residential and employment density, car ownership, service level, speed, stop spacing, share of accessible stops, share of segregated right of away and integrated fares was undertaken. This established a statistically significant model (99% level, R2 = 0.76) with five significant variables including service level, routes being in Europe, speed, integrated ticketing and employment density. In general these findings support selected results from previous research. A secondary analysis of service effectiveness measures (boardings/vehicle km, i.e. the relative ridership performance for a given level of service), established a statistically significant model (99% level, R2 = 0.67) with 6 significant explanatory variables including being in Europe, speed, employment density, integrated ticketing, track segregation and service level. The latter implies that a higher frequency results in higher service effectiveness. Overall the research findings stress the importance of providing a high level of service as a major driver of light rail ridership. The ‘European Factor’ is also an important though intriguing influence but its cause remains unclear and requires further research to elaborate its nature.
TL;DR: In this article, the authors investigate microeconomic determinants of freight rates in the dry bulk shipping market, using a large sample of individual dry bulk charter contracts from January 2003 to July 2009.
Abstract: While the literature has established macroeconomic determinants of shipping freight (charter) rates, there has been no systematic investigation of the microeconomic determinants of shipping freight rates. Therefore, the purpose of this paper is to investigate microeconomic determinants of freight rates in the dry bulk shipping market, using a large sample of individual dry bulk charter contracts from January 2003 to July 2009. Differences in freight rates across major dry bulk shipping routes, the geographical distribution of shipping activities around the world, and the duration of the laycan period of shipping contracts are also investigated. Estimated results suggest that the laycan period and dry bulk freight rates are interrelated and determined simultaneously. Furthermore, vessel deadweight, age and voyage routes are important determinants of dry bulk shipping freight rates, while determinants of the laycan period of chartered vessels include vessel age, freight rate level, and freight rate volatility.
TL;DR: In this paper, the authors used a multiple equation approach to estimate the daily duration of shopping activities and trips while simultaneously controlling for daily durations of four broad categories of activities as well as their associated travel times.
Abstract: Increasing awareness and concern about the status of mobility-disadvantaged groups in society has given rise to a wide body of research that focuses on the social exclusion dimension of transportation. To date, much of the empirical work on this topic is mainly spatial in nature despite recent developments that call for the inclusion of time use analyses in social exclusion research. In this paper we attempt to fill this gap by estimating activity and trip durations to determine whether poverty, old age, or being a single parent results in time use patterns indicative of exclusion. Given the importance of shopping and using services for social inclusion objectives, these activities are the focus of this investigation. In terms of methods, use of a multiple equation approach allows for the estimation of the daily duration of shopping activities and trips while simultaneously controlling for daily durations of four broad categories of activities as well as their associated travel times. The results indicate: that being a senior citizen increases travel durations while decreasing shopping activity durations; that coming from a low income household decreases shopping activity durations; and single-parent status does not impact shopping activity durations when holding income and other activity durations constant. These results highlight the feasibility and challenges of time-use and activity analysis in social exclusion research.
TL;DR: In this article, a focus group discussion identified 14 attributes representing characteristics that describe the quality of roads for bicycling in Brazilian cities and an attitude survey was applied with individuals to assess their perception on the attributes, along with the importance given to each one of them.
Abstract: The promotion of bicycle transportation includes the provision of suitable infrastructure for cyclists. In order to determine if a road is suitable for bicycling or not, and what improvements need to be made to increase the level of service for bicycles on specific situations, it is important to know how cyclists perceive the characteristics that define the roadway environment. The present paper describes research developed to define which roadway and traffic characteristics are prioritized by users and potential users in the evaluation of quality of roads for bicycling in urban areas of Brazilian medium-sized cities. A focus group discussion identified 14 attributes representing characteristics that describe the quality of roads for bicycling in Brazilian cities. In addition, an attitude survey was applied with individuals to assess their perception on the attributes, along with the importance given to each one of them. The results were analyzed through the Method of Successive Intervals Analysis, which allows the transformation of categorical data into an interval scale. The analysis suggests that both the roadway and traffic characteristics related to segments and those related to intersections are important to the survey respondents. The five most important attributes, in their opinion, are: (1) lane width; (2) motor vehicle speed; (3) visibility at intersections; (4) presence of intersections; and (5) street trees (shading). Therefore, the research suggests that to promote bicycle use in Brazilian medium-sized cities, these attributes must be prioritized.
TL;DR: In this paper, the authors investigated the carpool mode choice option in the context of overall commuting mode choice preferences and used a hybrid discrete choice modeling technique to jointly model the consideration of carpooling in the choice set formation as well as commuting modes choice together with the response bias corrections through the accommodation of measurement equations.
Abstract: This article investigates the carpool mode choice option in the context of overall commuting mode choice preferences. The article uses a hybrid discrete choice modelling technique to jointly model the consideration of carpooling in the choice set formation as well as commuting mode choice together with the response bias corrections through the accommodation of measurement equations. A cross-nested error structure for the econometric formulation is used to capture correlations among various commuting modes and carpool consideration in the choice set. Empirical models are estimated using a data set collected through a week-long commuter survey in Edmonton, Alberta. The empirical model reveals many behavioural details of commuting mode choice and carpooling. Interestingly, it reveals that interactions between various Travel Demand Management (TDM) tools with the carpooling option can be different at different level of decision making (choice set formation level and final choice making level).
TL;DR: In this article, a vehicle transaction timing model which is conditional on household residential and job relocation timings is introduced. But the model was not considered to account for changes in household taste over time and the effects of land-use, economy and disaggregate travel activity attributes.
Abstract: This paper introduces a vehicle transaction timing model which is conditional on household residential and job relocation timings. Further, the household residential location and members’ job relocation timing decisions are jointly estimated. Some researchers have modeled the household vehicle ownership decision jointly with other household decisions like vehicle type choice or VMT; however, these models were basically static and changes in household taste over time has been ignored in nearly all of these models. The proposed model is a dynamic joint model in which the effects of land-use, economy and disaggregate travel activity attributes on the major household decisions; residential location and members’ job relocation timing decisions for wife and husband of the household, are estimated. Each of these models is estimated using both the Weibull and log-logistic baseline hazard functions to assess the usefulness of a non-monotonic rather than monotonic baseline hazard function. The last three waves of the Puget Sound Panel Survey data and land-use, transportation, and built environment variables from the Seattle Metropolitan Area are used in this study as these waves include useful explanatory variables like household tenure that were not included in the previous waves.
TL;DR: “Medical trips”, “Shopping” and “Personal Errands” were the least discretionary of all trip types, yet the most difficult for participants to find alternate arrangements, suggesting the need to explore different models of service delivery.
Abstract: Rural seniors are highly dependent on their automobile to meet their trip making needs, yet the effects of aging can make access to the vehicle difficult or impossible over time. The anticipated growth in the older person population, in concert with limited travel data available to support rural transportation planning in Canada suggests a disconnect between what rural older people may require for transportation and the availability of formal alternatives. Many will seek informal alternatives to driving, such as depending on friends and family, to meet their travel needs, but the degree is not well understood in the context of their actual vehicle usage and stated ability to adapt. This paper draws from a Global Positioning System (GPS)-based multi-day travel diary survey of a convenience sample of 60 rural older drivers (29 men, 31 women, average age of 69.6 years) from New Brunswick, Canada. Participants would rely on “friends and family” for 52% of all trips they undertook as driver in the survey, “walk or bike” for 14% of trips, and “not take the trip” in 34% of trips if they did not have access to a vehicle. The formal option of “Transit” was not selected as a viable alternative by any participant for any trip. “Medical trips”, “Shopping” and “Personal Errands” were the least discretionary of all trip types, yet the most difficult for participants to find alternate arrangements. This suggests the need to explore different models of service delivery, such as a community-supported, member-based rural shuttle service with volunteer and paid drivers that build on informal social networks and can provide service when friends and family are unavailable.
Journal Article•
TL;DR: In this paper, a survey of 60 rural older drivers from New Brunswick, Canada found that participants would rely on friends and family for 52% of all trips they undertook as driver in the survey, walk or bike for 14% of trips, and not take the trip in 34% of the trips if they did not have access to a vehicle.
Abstract: Rural seniors are highly dependent on their automobile to meet their trip making needs, yet the effects of aging can make access to the vehicle difficult or impossible over time. The anticipated growth in the older person population, in concert with limited travel data available to support rural transportation planning in Canada suggests a disconnect between what rural older people may require for transportation and the availability of formal alternatives. Many will seek informal alternatives to driving, such as depending on friends and family, to meet their travel needs, but the degree is not well understood in the context of their actual vehicle usage and stated ability to adapt. This paper draws from a Global Positioning System (GPS)-based multi-day travel diary survey of a convenience sample of 60 rural older drivers (29 men, 31 women, average age of 69.6 years) from New Brunswick, Canada. Participants would rely on “friends and family” for 52% of all trips they undertook as driver in the survey, “walk or bike” for 14% of trips, and “not take the trip” in 34% of trips if they did not have access to a vehicle. The formal option of “Transit” was not selected as a viable alternative by any participant for any trip. “Medical trips”, “Shopping” and “Personal Errands” were the least discretionary of all trip types, yet the most difficult for participants to find alternate arrangements. This suggests the need to explore different models of service delivery, such as a community-supported, member-based rural shuttle service with volunteer and paid drivers that build on informal social networks and can provide service when friends and family are unavailable.
TL;DR: In this paper, the authors present the results of a study exploring travellers' preferences for middle-distance travel using Q-methodology and rank-ordered 42 opinion statements regarding travel choice and motivations for travel in general.
Abstract: This article presents the results of a study exploring travellers’ preferences for middle-distance travel using Q-methodology. Respondents rank-ordered 42 opinion statements regarding travel choice and motivations for travel in general and for car and public transport as alternative travel modes. By-person factor analysis revealed four distinct preference segments for middle-distance travel: (1) choice travellers with a preference for public transport, (2) deliberate-choice travellers, (3) choice travellers with car as dominant alternative, and (4) car-dependent travellers. These preference segments differ in terms of the levels of involvement and cognitive effort in travel decision making, the travel consideration-set and underlying motivations. The study showed that for most people there is more to travel than getting from point A to point B, and that there is considerable heterogeneity in middle-distance travel preferences. Policy implications for reducing the need for travel and promoting a modal shift from car to other travel modes are discussed.
TL;DR: The principal findings were that the representation of awareness of transit services is significantly different than the underlying assumption of mode choice and forecasting models that there is perfect awareness and consideration of all modes.
Abstract: This research seeks to improve the understanding of the full range of determinants for mode choice behavior and to offer practical solutions to practitioners on representing and distinguishing these characteristics in travel demand forecasting models. The principal findings were that the representation of awareness of transit services is significantly different than the underlying assumption of mode choice and forecasting models that there is perfect awareness and consideration of all modes. Furthermore, inclusion of non-traditional transit attributes and attitudes can improve mode choice models and reduce bias constants. Additional methods and analyses are necessary to bring these results into practice. The work is being conducted in two phases. This paper documents the results of Phase I, which included data collection for one case study city (Salt Lake City), research and analysis of non-traditional transit attributes in mode choice models, awareness of transit services, and recommendations for bringing these analyses into practice. Phase II will include data collection for two additional case study cities (Chicago and Charlotte) with minor modifications based on limitations identified in Phase I, additional analyses where Phase I results indicated a need, and a demonstration of the research in practice for at least one case study city.
TL;DR: A modeling framework for dynamic activity scheduling that considers random utility maximization (RUM) assumption for its components in order to capture the joint activity type, location and continuous time expenditure choice tradeoffs over the course of the day reveals that on the weekend the utility of scheduling recreational activities for later in the day and over a longer duration of time is high.
Abstract: The paper presents a modeling framework for dynamic activity scheduling. The modeling framework considers random utility maximization (RUM) assumption for its components in order to capture the joint activity type, location and continuous time expenditure choice tradeoffs over the course of the day. The dynamics of activity scheduling process are modeled by considering the history of activity participation as well as changes in time budget availability over the day. For empirical application, the model is estimated for weekend activity scheduling using a dataset (CHASE) collected in Toronto in 2002–2003. The data set classifies activities into nine general categories. For the empirical model of a 24-h weekend activity scheduling, only activity type and time expenditure choices are considered. The estimated empirical model captures many behavioral details and gives a high degree of fit to the observed weekend scheduling patterns. Some examples of such behavioral details are the effects of time of the day on activity type choice for scheduling and on the corresponding time expenditure; the effects of travel time requirements on activity type choice for scheduling and on the corresponding time expenditure, etc. Among many other findings, the empirical model reveals that on the weekend the utility of scheduling Recreational activities for later in the day and over a longer duration of time is high. It also reveals that on the weekend, Social activity scheduling is not affected by travel time requirements, but longer travel time requirements typically lead to longer-duration social activities.
TL;DR: In this paper, the authors used a mixed dataset of revealed preference (RP)-stated preference (SP) to study the effect of inertia between RP and SP observations and to study if the inertia effect is stable along the SP experiments.
Abstract: Inertia is related with effect that experiences in previous periods may have on the current choice. In particular, it has to do with the tendency to stick with the past choice even when another alternative becomes more appealing. As new situations force individuals to rethink about their choices new preferences may be formed. Thus a learning process begins that relaxes the effect of inertia in the current choice. In this paper we use a mixed dataset of revealed preference (RP)-stated preference (SP) to study the effect of inertia between RP and SP observations and to study if the inertia effect is stable along the SP experiments. Inertia has been studied more extensively with panel datasets, but few investigations have used RP/SP datasets. In this paper we extend previous work in several ways. We test and compare several ways of measuring inertia, including measures that have been proposed for both short and long RP panel datasets. We also explore new measures of inertia to test for the effect of “learning” (in the sense of acquiring experience or getting more familiar with) along the SP experiment and we disentangle this effect from the pure inertia effect. A mixed logit model is used that allows us to account for both systematic and random taste variations in the inertia effect and for correlations among RP and SP observations. Finally we explore the relation between the utility specification (especially in the SP dataset) and the role of inertia in explaining current choices.
TL;DR: The results suggest that unreliable auto travel conditions induce mode switching to transit and that the influence is strongest when service by train is already faster than by car, which suggests that auto travel unreliability may have the strongest influence in metropolitan regions with highly-competitive transit systems.
Abstract: Researchers and practitioners highlight the unreliability of travel as a potential weak link in the transportation system which may inhibit individuals’ accessibility and urban economic activity. With the trend towards increasing traffic congestion, the outlook suggests that travel conditions will become structurally less reliable over time, but that not all places will be equally affected. But is travel time unreliability a problem? This study uses global positioning systems travel survey data for Chicago to build a regional model of travel time unreliability. The results suggest that unreliability varies spatially during different time periods, but that the average overall network unreliability varies little across times in the day. Using the Chicago Metropolitan Agency for Planning (CMAP)’s 2007 Travel Tracker Survey, a household travel diary survey including both GPS and non-GPS components, we estimate a mode choice model for work trips to explore the influence of unreliability on travel behavior. The results suggest that unreliable auto travel conditions induce mode switching to transit and that the influence is strongest when service by train is already faster than by car. This further suggests that auto travel unreliability may have the strongest influence in metropolitan regions with highly-competitive transit systems. Nevertheless, the influence of travel unreliability is limited and is not the underlying driver of travel decision-making.
TL;DR: The paper demonstrates the feasibility of developing panel data models that can be applied to forecasting the effect of interventions in the travel environment with the most realistic predictions arising from a model which takes into account lagged responses to change in LOS and unobserved heterogeneity.
Abstract: Panel data offers the potential to represent the influence on travel choices of changing circumstances, past history and persistent individual differences (unobserved heterogeneity). A four-wave panel survey collected data on the travel choices of residents before and after the introduction of a new bus rapid transit service. The data shows gradual changes to bus use over the four waves, implying time was required for residents to become aware of the new service and to adapt to it. Ordered response models are estimated for bus use over the survey period. The results show that the influence of level of service (LOS) is underestimated if unobserved heterogeneity is not taken into account. The delayed response to the new service is able to be well represented by including LOS as a lagged variable. Current bus use is found to be conditioned on past bus use, but with additional influence of lagged LOS and unobserved heterogeneity. It is shown how different model specifications generate different evolution patterns with the most realistic predictions arising from a model which takes into account lagged responses to change in LOS and unobserved heterogeneity. The paper demonstrates the feasibility of developing panel data models that can be applied to forecasting the effect of interventions in the travel environment. Longer panels—encompassing periods of both stability and change—are required to support future efforts at modelling travel choice dynamics.
TL;DR: In this article, individual reactions to a negative change in the reference alternative values, identifying the behavioural implications in terms of loss aversion and diminishing sensitivity, were identified. But, to date, the specification of a reference alternative in transport studies has been fixed, whereas it is common to observe individuals adjusting their preferences according to a change in their reference point.
Abstract: It is widely recognized that individual decision-making is subject to the evaluation of gains and losses around a reference point. The estimation of discrete choice models increasingly use data from stated choice experiments which are pivoted around a reference alternative. However, to date, the specification of a reference alternative in transport studies has been fixed, whereas it is common to observe individuals adjusting their preferences according to a change in their reference point. This paper focuses on individual reactions, in a freight choice context, to a negative change in the reference alternative values, identifying the behavioural implications in terms of loss aversion and diminishing sensitivity. The results show a significant adjustment in the valuation of gains and losses around a shifted reference alternative. In particular, we find an average increase in loss aversion for cost and time attributes, and a substantial decrease for punctuality. These findings are translated to significant differences in the willingness to pay and willingness to accept measures, providing supporting evidence of respondents’ behavioural reaction.
TL;DR: In this article, individual income-contingent utility functions are estimated based on survey data in order to describe human mobility behavior, and the implementation is tested in a test scenario.
Abstract: Standard economic policy evaluation allows the realization of projects if the aggregated economic benefit outweighs their costs. The use of one single aggregated welfare measure for evaluating and ranking projects has often been criticized for many reasons. A major issue is that differentiated effects on individuals or subgroups of the population are not taken into consideration. This leads to the need for transport planning tools that provide additional information for politicians and decision makers. The microscopic multi-agent simulation approach presented in this paper is capable of helping to design better solutions in such situations. In particular, it is shown that the inclusion of individual income in utility calculations allows a better understanding of problems linked to public acceptance. First, individual income-contingent utility functions are estimated based on survey data in order to describe human mobility behavior. Subsequently, using the MATSim framework, the implementation is tested in a test scenario. Furthermore, and going beyond Franklin (2006), it is shown that the approach works in a large-scale real world example. Based on a hypothetical speed increase of public transit, effects on the welfare distribution of the population are discussed. It is shown that the identification of winners and losers seems to be quite robust. However, results indicate that a conversion or aggregation of individual utility changes for welfare analysis is highly dependent on the functional form of the utility functions as well as on the choice of the aggregation procedure.
TL;DR: In this paper, the authors investigated the availability of an engineering-oriented trial-and-error method for the effective toll pattern of cordon-based congestion pricing scheme, under side-constrained probit-based stochastic user equilibrium (SUE) conditions.
Abstract: A toll pattern that can restrict link flows on the tolled links to some predetermined thresholds is named as effective toll solution, which can be theoretically obtained by solving a side-constraint traffic assignment problem. Considering the practical implementation, this paper investigates availability of an engineering-oriented trial-and-error method for the effective toll pattern of cordon-based congestion pricing scheme, under side-constrained probit-based stochastic user equilibrium (SUE) conditions. The trial-and-error method merely requires the observed traffic counts on each entry of the cordon. A minimization model for the side-constrained probit-based SUE problem with elastic demand is first proposed and it is shown that the effective toll solution equals to the product of value of time and optimal Lagrangian multipliers with respect to the side constraints. Then, employing the Lagrangian dual formulation of the minimization method, this paper has built a convergent trial-and-error method. The trial-and-error method is finally tested by a numerical example developed from the cordon-based congestion pricing scheme in Singapore.