Transportation (TRANSPORTATION )

Publisher: Springer Verlag

Description

Although the transportation needs of cities and nations around the world may differ in detail there is much that is common. The benefit to be derived by sharing research findings and practical experience is therefore vast. Transportation lends itself to that vital process of information exchange by publishing carefully selected papers which advance the international fund of knowledge. Transportation focuses on issues of direct relevance to those concerned with the formulation of policy the preparation and evaluation of plans and the day-to-day operational management of transport systems. It concerns itself with the policies and systems themselves as well as with their impacts on and relationships with other aspects of the social economic and physical environment. Transportation is relevant to all parts of the world: industrialized newly industrialized or developing. The journal has no model bias and is totally apolitical. Its mission is simply to help improve the transportation of people and goods by bringing an improved understanding of the subject to the theorists practitioners and policy makers who study it.

  • Impact factor
    1.66
    Hide impact factor history
     
    Impact factor
  • 5-year impact
    2.13
  • Cited half-life
    8.60
  • Immediacy index
    0.34
  • Eigenfactor
    0.00
  • Article influence
    0.85
  • Website
    Transportation website
  • Other titles
    Transportation
  • ISSN
    0049-4488
  • OCLC
    1624097
  • Material type
    Periodical
  • Document type
    Journal / Magazine / Newspaper

Publisher details

Springer Verlag

  • Pre-print
    • Author can archive a pre-print version
  • Post-print
    • Author can archive a post-print version
  • Conditions
    • Author's pre-print on pre-print servers such as arXiv.org
    • Author's post-print on author's personal website immediately
    • Author's post-print on any open access repository after 12 months after publication
    • Publisher's version/PDF cannot be used
    • Published source must be acknowledged
    • Must link to publisher version
    • Set phrase to accompany link to published version (see policy)
    • Articles in some journals can be made Open Access on payment of additional charge
  • Classification
    ​ green

Publications in this journal

  • [Show abstract] [Hide abstract]
    ABSTRACT: The focus of this paper is to investigate methods to cluster activity patterns of individuals such that the results of the clustering can be used for inference purposes in activity-based behavioral travel demand models. Such questions as how to classify activity patterns in the most informative manner, how well the clusters and their representative patterns can represent activity patterns at the population level, or how the patterns of out-of-sample individuals can be classified to the clusters for further analysis are addressed. We use a two-stage clustering technique of affinity propagation and K-means to classify activity patterns that are created by segmenting daily activities into ten-minute intervals, carrying information about activity types, duration, schedule, and travel distance. The measure used to estimate the distance between pairs of patterns is a weighted combination of agenda dissimilarity and edit-distance. Decision trees are employed to model dependencies between individuals’ socio-demographics and cluster allocation that then enable the methodology to be used as a model for pattern inference and practical applications.
    Transportation 01/2015; under review.
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    ABSTRACT: Stated choice experiments are designed optimally in a statistical sense but not necessarily in a behavioural choice making sense. Statistical designs, and consequently model estimation, assume that the set of alternatives offered in the experiment are processed by respondents with a specific processing strategy. Much has been studied about attribute processing using discrete choice methods in travel choice studies, but this paper focuses more broadly on processing of alternatives in the choice set offered in the experiment. This paper is motivated by the primary idea that the distribution of predicted choice probabilities associated with a set of alternatives defining a given choice set might provide strong evidence on the strategies that agents appear to use when choosing a preferred alternative. In an empirical setting of a choice set of size three, four model specifications are considered including a model for the selection of the best alternative in the full choice set and three variants of a best–worst regime. Using state choice data on road pricing reform, the empirical analysis examines which model specification delivers the most accurate prediction of the chosen alternative. The results suggest which alternatives really matter in choice making and hence the alternatives that might be included in a choice set for model specification.
    Transportation 12/2014;
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    ABSTRACT: This paper conducts an exploratory analysis of freight trip attraction and its relationship with key features of the urban environment. Using establishment level data, the authors explore the role of business attributes, as well as network and land use descriptors. The research uses data from 343 establishments from five different industry sectors in New York City. These establishments are geo-located, and spatial association indicators are estimated to assess the presence of spatial effects. Spatial econometric techniques are used to assess the role of spatial effects among establishments and the urban environment. The empirical evidence suggests that establishments’ location, such as land-value and front street width, play an important role on freight trip attraction (FTA), and that retail industries located in high employment zones tend to produce higher FTA per employee. Another key finding is that FTA is better modeled using non-linear models for all industry sectors. Specifically, the freight trip attraction of business establishments is concave with employment, flattening as employment increases. This is confirmed by the modeling results for which the range of coefficients estimated for employment reveals that, although larger establishments have higher FTA than small establishments, FTA increases at a diminishing marginal rate. These exploratory findings shed light on the use of locational variables, and nonlinear spatial effects specifications to enhance FTA models.
    Transportation 12/2014;
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    ABSTRACT: Recent years have witnessed a growing volume of papers describing the use of GPS technology and other tracking technologies for obtaining data on time–space activities. These methods have several advantages over traditional methods of time–space data collection in terms of accuracy, resolution and length of the possible data collection period. However, to date, no work has been done on the compliance rates among participants and the resulting validity of the collected data. This paper presents a method that combines the use of a GPS receiver with Radio Frequency Identification (RFID) technology that was implemented in research on time–space activities of elderly persons with cognitive impairment. The method presented in this paper enables monitoring the level of compliance of the participants during their participation in the study and presents a unique opportunity to examine the extent to which participants in a GPS based study are able to comply with study requirements. Healthy older adults and those with cognitive decline were found to be generally compliant with a complex study protocol. These results serve as another step into the acceptance of GPS based studies as a valid methodology for mobility data collection.
    Transportation 10/2014;
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    ABSTRACT: Private car ownership plays a vital role in the daily travel decisions of individuals and households. The topic is of great interest to policy makers given the growing focus on global climate change, public health, and sustainable development issues. Not surprisingly, it is one of the most researched transportation topics. The extant literature on car ownership models considers the influence of exogenous variables to remain the same across the entire population. However, it is possible that the influence of exogenous variable effects might vary across the population. To accommodate this potential population heterogeneity in the context of car ownership, the current paper proposes the application of latent class versions of ordered (ordered logit) and unordered response (multinomial logit) models. The models are estimated using the data from Quebec City, Canada. The latent class models offer superior data fit compared to their traditional counterparts while clearly highlighting the presence of segmentation in the population. The validation exercise using the model estimation results further illustrates the strength of these models for examining car ownership decisions. Moreover, the latent class unordered response models perform slightly better than the latent class ordered response models for the metropolitan region examined.
    Transportation 09/2014;
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    ABSTRACT: Immigrants to the United States walk, bicycle, and use transit and carpools more than U.S.-born residents do. These differences persist over time and across income groups. The differences appear strongest when immigrants reside in immigrant neighborhoods with high concentrations of other immigrants. This analysis uses a large, geocoded national dataset to analyze these differences and finds that living in an immigrant neighborhood has a strong influence on mode choice for immigrant residents and a much weaker effect on non-immigrant residents of immigrant neighborhoods. These effects are strongest for walking and bicycling, and particularly for shopping-related travel, and they persist after controlling for a number of variables. That these effects are considerably stronger for immigrants than for their U.S.-born neighbors suggests that social factors of the neighborhoods may play a role in structuring travel decisions.
    Transportation 08/2014;
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    ABSTRACT: This paper analyzes households’ decision to change their car ownership level in response to actions/decisions regarding mobility issues and other household events. Following recent literature on the importance of critical events for mobility decisions, it focuses on the relationship between specific events (e.g. childbirth and buying an extra car), rather than trying to explain the status of car ownership from a set of stationary explanatory variables. In particular, it is hypothesized that changes in household car ownership level take place in response to stressors, resulting from changed household needs or aspirations. The study includes a broad range of events. Apart from changes in work status, employer and residential location, it analyzes demographic events such as household formation and childbirth. Also, it scrutinizes the temporal sequence in which chains of related events are most likely to occur. To this end, data from a retrospective survey that records respondents’ car ownership status, as well as residential and household situation over the past 20 years are used. A panel analysis has been carried out to disentangle typical relationships. The results suggest that strong and simultaneous relationships exist between car ownership changes and household formation and dissolution processes. Childbirth and residential relocation invoke car ownership changes. Changes are also made in anticipation of future events such as employer change and childbirth. Childbirth is associated with increasing the number of cars, whereas the effect of employer change goes the opposite way. Job change increases the probability of car ownership change in the following year.
    Transportation 07/2014; 41(4):889-904.
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    ABSTRACT: The paper proposes a microscopic travel demand model that generates multi-week schedules by means of a continuous planning approach with an open planning horizon. This model introduces behavioral targets to describe people’s motivation to perform activities, and it uses a planning heuristic to make on-the-fly decisions about upcoming activities. The planning heuristic bases its decisions on three aspects: a dis- 13 comfort index derived from deviations from agents’ past performance with regard to their behavioral targets; the effectiveness of the immediate execution; and activity execution options available in the near future. The paper reports the results of a test scenario based on 16 an existing 6-week continuous travel diary and validates the model by comparing simulation results with observed behavioral patterns along several dimensions (weekday similarities, weekday execution probabilities of activities, transition probabilities between activities, duration distributions of activities, frequency distributions of activities, execution interval distributions of activities and weekly travel probability distributions). The results show that the model has the capability to reproduce observed behavior and the flexibility to introduces new behavioral patterns.
    Transportation 07/2014;
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    ABSTRACT: This study examines how the built environment and weather conditions influence the use of walking as a mode of transport. The Halifax Regional Municipality in Nova Scotia, Canada is the study area for this work. Data are derived from three sources: a socio-demographic questionnaire and a GPS-enhanced prompted recall time-use diary collected between April 2007 and May 2008 as part of the Halifax Space-Time Activity Research project, a daily meteorological summary from Environment Canada, and a comprehensive GIS dataset from the regional municipality. Two binary logit multilevel models are estimated to examine how the propensity to use walking is influenced by the built environment and weather while controlling for socio-demographic characteristics. The built environment is measured via five attributes in one model and a walkability index (derived from the five attributes) in the other. Weather conditions are shown to affect walking use in both models. Although the walkability index is significant, the results demonstrate that this significance is driven by specific attributes of the built environment—in the case of this study, population density and to a lesser extent, pedestrian infrastructure.
    Transportation 03/2014;
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    ABSTRACT: The modeling of service dynamics has been the focus of recent developments in the field of transit assignment modeling. The emerging focus on dynamic service modeling requires a corresponding shift in transit demand modeling to represent appropriately the dynamic behaviour of passengers and their responses to Intelligent Transportation Systems technologies. This paper presents the theoretical development of a departure time and transit path choice model based on the Markovian Decision Process. This model is the core of the MIcrosimulation Learning-based Approach to TRansit Assignment. Passengers, while traveling, move to different locations in the transit network at different points in time (e.g. at stop, on board), representing a stochastic process. This stochastic process is partly dependent on the transit service performance and partly controlled by the transit rider’s trip choices. This can be analyzed as a Markovian Decision Process, in which actions are rewarded and hence passengers’ optimal policies for maximizing the trip utility can be estimated. The proposed model is classified as a bounded rational model, with a constant utility term and a stochastic choice rule. The model is appropriate for modeling information provision since it distinguishes between individual’s experience with the service performance and information provided about system dynamics.
    Transportation 03/2014; 41(2).
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    ABSTRACT: A growing base of research adopts direct demand models to reveal associations between transit ridership and influence factors in recent years. This study is designed to investigate the factors affecting rail transit ridership at both station level and station-to-station level by adopting multiple regression model and multiplicative model respectively, specifically using an implemented Metro system in Nanjing, China, where Metro implementation is on the rise. Independent variables include factors measuring land-use mix, intermodal connection, station context, and travel impedance. Multiple regression model proves 11 variables are significantly associated with Metro ridership at station level: population, employment, business/office floor area, CBD dummy variable, number of major educational sites, entertainment venues and shopping centers, road length, feeder bus lines, bicycle park-and-ride (P&R) spaces, and transfer dummy variable. Results from multiplicative model indicate that factors influencing Metro station ridership may also influence Metro station-to-station ridership, varied by both trip ends (origin/destination) and time of day. In comparison with previous case studies, CBD dummy variable and bicycle P&R are statistically significant to explain Metro ridership in Nanjing. In addition, Metro travel impedance variables have significant influence on station-to-station ridership, representing the basic time-decay relationship in travel distribution. Potential implications of the model results include estimating Metro ridership at station level and station-to-station level by considering the significant variables, recognizing the necessity to establish a cooperative multi-modal transit system, and identifying opportunities for transit-oriented development.
    Transportation 01/2014;
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    ABSTRACT: This paper investigates the effects of the provision of traffic information on toll road usage based on a stated preference survey conducted in central Texas. Although many researchers have studied congestion pricing and traffic information dissemination extensively, most of them focused on the effects that these instruments individually produce on transportation system performance. Few studies have been conducted to elaborate on the impacts of traffic information dissemination on toll road utilization. In this study, 716 individuals completed a survey to measure representative public opinions and preferences for toll road usage in support of various traffic information dissemination classified by different modes, contents, and timeliness categories. A nested logit model was developed and estimated to identify the significant attributes of traffic information dissemination, traveler commuting patterns, routing behavior, and demographic characteristics, and analyze their impacts on toll road utilization. The results revealed that the travelers using dynamic message sign systems as their primary mode of receiving traffic information are more likely to choose toll roads. The potential toll road users also indicated their desire to obtain traffic information via internet. Information regarding accident locations, road hazard warnings, and congested roads is frequently sought by travelers. Furthermore, high-quality congested road information dissemination can significantly enhance travelers’ preferences of toll road usage. Specifically the study found that travelers anticipated an average travel time saving of about 11.3 min from better information; this is about 30 % of travelers’ average one-way commuting time. The mean value of the time savings was found to be about $11.82 per hour, close to ½ of the average Austin wage rate. The model specifications and result analyses provide in-depth insights in interpreting travelers’ behavioral tendencies of toll road utilization in support of traffic information. The results are also helpful to shape and develop future transportation toll system and transportation policy.
    Transportation 01/2014;
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    ABSTRACT: Although researchers have long argued in favor of off-peak transit service, studies that have empirically estimated its benefits regarding revenue generation, trip diversions, and greenhouse gas (GHG) emission are rare. This study provides important evidence about the benefits of off-peak commuter rail service by focusing on the Pascack Valley line in New Jersey, where off-peak service was introduced in October 2007. The research involved two focus groups and an onboard survey of passengers. Benefits were estimated regarding additional revenue generation and reduction in vehicle miles traveled (VMT) and GHG emission. The research shows that the new off-peak service potentially reduced VMT by more than 12 million annually due to diversions from other modes. Although diversions from other modes resulted in a substantial reduction in GHG emissions, due to the additional diesel fuel used by the new trains, the net GHG savings were in the range of 28–49 %. The research further shows that both peak period and off-peak riders benefited from the new off-peak service. Evidence is found about an increase in new transit riders and a modest increase peak period usage because of the off-peak service.
    Transportation 01/2014;
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    ABSTRACT: Young people appear to be using public transit more than their predecessors, reversing twentieth century trends, but the importance of such findings depends on whether high transit use persists as these riders age. This paper examines whether transit mode share for commuting trips is increasing; socio-economic and geographic trends are also explored to attempt to determine whether these trends are likely to continue. The study uses repeated cross-sectional origin–destination surveys of Greater Montreal (1998, 2003 and 2008). Over 45,000 home-to-work and home-to-school trips are studied for each survey year. A general lifecycle pattern of decreasing transit share with age is apparent within cohorts until individuals reach their early 30s, followed by decades of stability. This pattern appears to hold in recent years, but with higher youth use rates, and it is argued that the higher use will continue as current younger cohorts mature. Suburbanization by those in their early 30s is evident and, along with household composition changes, appears to explain much of the final within-cohort mode share declines before equilibrium. Transit providers might see lasting ridership gains, as those currently in their early 30s and younger replace lower-use cohorts in the workforce, provided service provision keeps pace. Addressing the needs of young people, whose mode choices are comparatively unsettled, should be a priority for transit agencies to ensure higher transit usage in the future.
    Transportation 01/2014;
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    ABSTRACT: Using a single line model, it has been shown recently that the presence of a stringent financial constraint induces a less than optimal bus frequency and larger than optimal bus size. This occurs because the constraint induces a reduction of the importance of users’ costs (their time); in the extreme, users’ costs disappear from the design problem. In this paper we show that such a constraint also has an impact on the spatial structure of transit lines. This is done departing from the single line model using an illustrative urban network that could be served either with direct services (no transfers) or with corridors (transfers are needed). First, the optimal structure of lines is investigated along with frequencies and vehicle sizes when the full costs for users and operators are minimized (unconstrained case); the optimal lines structure is shown to depend upon the patronage level, the values of time and the cost of providing bus capacity. Then the same problem is solved for the extreme case of a stringent financial constraint, in which case users’ costs have relatively little or no effect in determining the solution; in this case the preferred outcome would be direct services under all circumstances, with lower frequencies and larger bus sizes. The impact of the financial constraint on the spatial structure of transit lines is shown to be caused by the reduction in cycle time under direct services; the introduction of users’ costs in the objective function makes waiting times reverse this result under some circumstances.
    Transportation 01/2014;