Transportation Planning and Technology (TRANSPORT PLAN TECHN)

Publisher: Taylor & Francis (Routledge)

Journal description

Section A: Transportation Planning and Technology presents papers covering transport demand models, land use forecasting models, economic evaluation and its relationship to policy in both developed and developing countries, conventional and possibly unconventional future systems technology, urban and interurban transport terminals and interchanges and environmental aspects associated with transport (particularly those relating to noise, pollution and the movement of hazardous materials) as well as more narrowly focused technical papers. Considerable emphasis is placed on work relating to the interface between transportation planning and technology, economics, land use planning, and policy. The journal contains in-depth state-of-the-art papers on transport topics. Section B: Specialized Transportation Planning and Practice is concerned with issues affecting the mobility of special groups in society for whom traditional transportation programs and services are now well designed or deemed suitable. These special groups, increasingly referred to as the transportation disadvantaged, include the elderly, the physically and emotionally impaired, and families with low incomes. The intent of this section is to contribute to improving the mobility of special groups. To that end, this section gathers and disseminates soundly based knowledge on the transportation disadvantaged, derived from research, service methods demonstrations, documented experiences from the field, advances in transport-related technology, and changes in public policy as a result of legislative action, administrative regulations or judicial decisions.

Current impact factor: 0.51

Impact Factor Rankings

2016 Impact Factor Available summer 2017
2014 / 2015 Impact Factor 0.512
2012 Impact Factor 0.427
2011 Impact Factor 0.203
2010 Impact Factor 0.411
2009 Impact Factor 0.516
2008 Impact Factor 0.286
2007 Impact Factor 0.106
2006 Impact Factor 0.156
2005 Impact Factor 0.182
2004 Impact Factor 0.139
2003 Impact Factor 0.269
2002 Impact Factor 0.12
2001 Impact Factor
2000 Impact Factor 0.032
1999 Impact Factor 0.176
1998 Impact Factor 0.147
1997 Impact Factor 0.231
1996 Impact Factor 0.148

Impact factor over time

Impact factor
Year

Additional details

5-year impact 0.63
Cited half-life 7.30
Immediacy index 0.11
Eigenfactor 0.00
Article influence 0.25
Website Transportation Planning and Technology website
Other titles Transportation planning and technology (Online)
ISSN 0308-1060
OCLC 50447092
Material type Document, Periodical, Internet resource
Document type Internet Resource, Computer File, Journal / Magazine / Newspaper

Publisher details

Taylor & Francis (Routledge)

  • Pre-print
    • Author can archive a pre-print version
  • Post-print
    • Author can archive a post-print version
  • Conditions
    • Some individual journals may have policies prohibiting pre-print archiving
    • On author's personal website or departmental website immediately
    • On institutional repository or subject-based repository after a 18 months embargo
    • Publisher's version/PDF cannot be used
    • On a non-profit server
    • Published source must be acknowledged
    • Must link to publisher version
    • Set statements to accompany deposits (see policy)
    • The publisher will deposit in on behalf of authors to a designated institutional repository including PubMed Central, where a deposit agreement exists with the repository
    • SSH: Social Science and Humanities
    • Publisher last contacted on 25/03/2014
    • This policy is an exception to the default policies of 'Taylor & Francis (Routledge)'
  • Classification
    green

Publications in this journal

  • [Show abstract] [Hide abstract]
    ABSTRACT: In transportation projects, uncertainty related to the difference between forecast and actual demand is of major interest for the decision-maker, as it can have a substantial influence on the viability of a project. This paper identifies and quantifies discrete choice model uncertainty, which is present in the model parameters and attributes, and determines its impact on risk taking for decision-making applied to a case study of the High-Speed Rail project in Portugal. The methodology includes bootstrapping for the parameter variation, a postulated triangular distribution for the mode-specific input and a probabilistic graphical model for the socio-economic input variation. In comparison to point estimates, the findings for mode shift results in a wider swing in the system, which constitutes valuable information for decision-makers. The methodology, findings and conclusions presented in this study can be generalized to projects involving similar models.
    No preview · Article · Jan 2016 · Transportation Planning and Technology
  • [Show abstract] [Hide abstract]
    ABSTRACT: When designing transit services, the Level-of-Service concept has been widely used by transport planners and service providers to assess the service quality of an existing transit system. In addition to the service quality assessment, service providers also need to estimate the service levels that will satisfy a maximum number of users and potential users, across all socio-economic groups, so as to maximize patronage. This paper demonstrates a method using the concept of ‘user satisfaction levels’ and their ‘zone of tolerance’, along with total utility and marginal utility for service providers, to provide a range of service delivery levels for individual transit service attributes in the city of Kolkata. This range of service levels provides a guideline for service providers within which they can consider making an improvement in service level. However, the final decision on service improvement is an outcome of both financial and infrastructural feasibility.
    No preview · Article · Jan 2016 · Transportation Planning and Technology
  • [Show abstract] [Hide abstract]
    ABSTRACT: Despite high costs, many cities build public transit to address regional equity, environmental and economic goals. Although public transit accounts for a minority of trips (∼5%), the impact is widely felt when service is suspended during a strike through excess road demand and slower journeys. In 2013, Bay Area Rapid Transit (BART) workers participated in two brief strikes, and the resulting traffic conditions illustrate the value of transit to drivers in the San Francisco Bay Area region. This paper tests the impact of rail transit service interruption on freeway traffic conditions using volumes and travel times. During the strike, regional freeway conditions showed negligible change. However, on facilities that parallel BART service, the impacts are as bad as the worst day of a typical week. Conditions on the San Francisco–Oakland Bay Bridge showed significant impacts with travel times and volumes nearly doubling the baseline median values on the worst day.
    No preview · Article · Jan 2016 · Transportation Planning and Technology
  • [Show abstract] [Hide abstract]
    ABSTRACT: Global Positioning System (GPS) technologies have been increasingly considered as an alternative to traditional travel survey methods to collect activity-travel data. Algorithms applied to extract activity-travel patterns vary from informal ad-hoc decision rules to advanced machine learning methods and have different accuracy. This paper systematically compares the relative performance of different algorithms for the detection of transportation modes and activity episodes. In particular, naive Bayesian, Bayesian network, logistic regression, multilayer perceptron, support vector machine, decision table, and C4.5 algorithms are selected and compared for the same data according to their overall error rates and hit ratios. Results show that the Bayesian network has a better performance than the other algorithms in terms of the percentage correctly identified instances and Kappa values for both the training data and test data, in the sense that the Bayesian network is relatively efficient and generalizable in the context of GPS data imputation.
    No preview · Article · Jan 2016 · Transportation Planning and Technology
  • [Show abstract] [Hide abstract]
    ABSTRACT: The rapid development and deployment of Intelligent Transportation Systems (ITS) that utilize data on the movement of vehicles can greatly benefit transportation network operations and safety, but may test the limits of personal privacy. In this paper we survey the current state of legal and industry-led privacy protections related to ITS and find that the lack of existing standards, rules, and laws governing the collection, storage, and use of such information could both raise troubling privacy questions and potentially hinder implementation of useful ITS technologies. We then offer practical recommendations for addressing ITS-related privacy concerns though both privacy-by-design solutions (that build privacy protections into data collection systems), and privacy-by-policy solutions (that provide guidelines for data collection and treatment) including limiting the scope of data collection and use, assuring confidentially of data storage, and other ways to build trust and foster consumer consent.
    No preview · Article · Jan 2016 · Transportation Planning and Technology

  • No preview · Article · Jan 2016 · Transportation Planning and Technology
  • [Show abstract] [Hide abstract]
    ABSTRACT: The analysis of driving behaviour is a challenging task in the transport field that has numerous applications, ranging from highway design to micro-simulation and the development of advanced driver assistance systems. There has been evidence suggesting changes in the driving behaviour in response to changes in traffic conditions, and this is known as adaptive driving behaviour. Identifying these changes and the conditions under which they happen, and describing them in a systematic way, contributes greatly to the accuracy of micro-simulation, and more importantly to the understanding of the traffic flow, and therefore paves the way for introducing further improvements with respect to the efficiency of the transport network. In this paper adaptive driving behaviour is linked to changes in the parameters of a given car-following model. These changes are tracked using a dynamic system identification method, called particle filtering. Subsequently, the dynamic parameter estimates are further processed to identify critical points where significant changes in the system take place.
    No preview · Article · Dec 2015 · Transportation Planning and Technology
  • [Show abstract] [Hide abstract]
    ABSTRACT: Bus priority at traffic signals has been implemented in many cities around the world. At signalised junctions, priority can be given by altering signal timings in favour of approaching buses. In usual practice, this is achieved by either extending the green period for an approaching bus or recalling the green stage, if the signal is currently red for the bus. These bus priority methods reduce junction delays for buses and thus improve bus speed and reliability. At isolated junctions in the UK, the parameters used to implement these priority methods are only based on the requirements for green extensions. These parameters may not always be effective for recalls. This study was undertaken to explore whether bus priority benefits can be improved by considering new priority parameters effective for both methods. This research has involved the application of the VISSIM microscopic simulation software to evaluate existing and new strategies for bus priority at isolated signal controlled junctions operating under D-system vehicle actuation (VA). During evaluation, bus travel time savings and impacts on general traffic have been considered. The performance of these methods on various junction types has been evaluated. New advanced bus priority methods based on new priority parameters have been developed and their performance has been compared with the existing methods.
    No preview · Article · Nov 2015 · Transportation Planning and Technology
  • [Show abstract] [Hide abstract]
    ABSTRACT: This paper investigates the relative influence of urban form, attitude and preferences and socio-economic and demographic factors on travel patterns in terms of vehicular miles travelled in Northern Ireland. Two specific issues unique to the research context, where car reliance is an inherent part of daily lifestyle, are of concern when determining the pattern of these inter-relationships: firstly ‘where we live’ and secondly its impact on ‘how we travel’ or vice versa. Using partial least squares structural equation modelling the empirical findings show that while there is no significant direct influence of the neighbourhood scale urban form variables on the vehicular miles travelled (VMT), regional-scale urban form factors exert a strong effect on VMT. Car-oriented preference and socio-economic characteristics were found to be key determinants of VMT, although the strongest influence is exerted by residential preferences namely ‘where we live’ which in turn influences ‘how we travel’.
    No preview · Article · Nov 2015 · Transportation Planning and Technology
  • [Show abstract] [Hide abstract]
    ABSTRACT: Mobile real-time passenger information (RTPI) systems are becoming ubiquitous in public transport and a plethora of studies have explored the effects they have on passengers. However, these studies mostly focus on urban areas and largely ignore rural dwellers. In this paper, we present results of a study that looks into the effects that mobile RTPI has on passengers in rural areas. The results indicate that the participants primarily used the mobile RTPI system to gain situation and geospatial awareness and to adapt their travel behaviour in disrupted circumstances. Further, we have identified that mobile RTPI significantly affects the everyday public transport travel of individuals. The outcomes of this study provide an initial understanding of the effects of a mobile RTPI system on rural users.
    No preview · Article · Nov 2015 · Transportation Planning and Technology
  • [Show abstract] [Hide abstract]
    ABSTRACT: This paper applies multi-criteria decision-making (MCDM) methods to the evaluation of solutions and alternatives for matching airport system airside (runway) capacity to demand. For such a purpose, ‘building a new runway’ is considered as the solution and candidate airports of the system as alternatives for implementing the solution. The alternative airports are characterized by their physical/spatial, operational, economic, environmental, and social performance represented by corresponding indicator systems which, after being defined and estimated under given operating scenarios, are used as evaluation attributes/criteria by the selected MCDM methods. Two MCDM methods – Simple Additive Weighting and Technique for Order of Preference by Similarity to Ideal Solution – are applied to the case of the London airport system to rank and select the preferred alternative from three candidate airports – Heathrow, Gatwick, and Stansted – for where a new runway could be built.
    No preview · Article · Oct 2015 · Transportation Planning and Technology
  • [Show abstract] [Hide abstract]
    ABSTRACT: This study proposes a three-stage decision-making model for the selection of electric vehicle battery technology. Data used for analysis include surveys completed by 45 technology experts from industry, academia, and research throughout Taiwan. A three-stage model that includes developing multiple-criteria during the first stage, integrating the importance of criteria assessment using the fuzzy analytical hierarchy process in the second stage, and using patent analysis tools to further identify the patent portfolio of the technology selected by experts in the third stage are employed. The empirical results indicate that power source management technology and battery module technology are the key technologies for development by the electric vehicle industry. Battery energy storage management and cooling technology are found to be the key for building patent portfolios. When faced with substantial technical and market uncertainty, multiple-criteria for research and development (R&D) selection and stage-wise integration of decision tool must be employed by battery firms to effectively allocate the resources for R&D decisions.
    No preview · Article · Oct 2015 · Transportation Planning and Technology
  • [Show abstract] [Hide abstract]
    ABSTRACT: As road congestion is exacerbated in most metropolitan areas, many transportation policies and planning strategies try to nudge travelers to switch to other more sustainable modes of transportation. In order to better analyze these strategies, there is a need to accurately model travelers’ mode-switching behavior. In this paper, a popular artificial intelligence approach, the decision tree (DT), is used to explore the underlying rules of travelers’ switching decisions between two modes under a proposed framework of dynamic mode searching and switching. An effective and practical method for a mode-switching DT induction is proposed. A loss matrix is introduced to handle class imbalance issues. Important factors and their relative importance are analyzed through information gains and feature selections. Household Travel Survey data are used to implement and validate the proposed DT induction method. Through comparison with logit models, the improved prediction ability of the DT models is demonstrated.
    No preview · Article · Sep 2015 · Transportation Planning and Technology