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: 0.43

Impact Factor Rankings

2015 Impact Factor Available summer 2015
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

Additional details

5-year impact 0.65
Cited half-life 6.30
Immediacy index 0.09
Eigenfactor 0.00
Article influence 0.27
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)

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    • Author can archive a pre-print version
  • Post-print
    • Author can archive a post-print version
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    • 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: Activity-based travel demand modeling (ABTDM) has often been viewed as an advanced approach, due to its higher fidelity and better policy sensitivity. However, a review of the literature indicates that no study has been undertaken to investigate quantitatively the differences and accuracy between an ABTDM approach and a traditional four-step travel demand model. In this paper we provide a comparative analysis against each step - trip generation, trip distribution, mode split, and network assignment - between an ABTDM developed using travel diary data from the Tampa Bay Region in Florida and the Tampa Bay Regional Planning Model (TBRPM), an existing traditional four-step model for the same area. Results show salient differences between the TBRPM and the ABTDM, in terms of modeling performance and accuracy, in each of the four steps. For example, trip production rates calculated from the travel diary data are found to be either double or a quarter less than those used in the TBRPM. On the other hand, trip attraction rates computed from activity-based travel simulations are found to be either more than double or one tenth less than those used in the TBRPM. The trip distribution curves from the two models are similar, but both average and peak trip lengths of the two are significantly different. Mode split analyses show that the TBRPM may underestimate driving trips and fail to capture any usage of alternative modes, such as taxi and nonmotorized (e.g., walking and bicycling) modes. In addition, the ABTDMs are found to be less capable of reproducing observed traffic counts when compared to the TBRPM, most likely due to not considering external and through trips. The comparative results presented can help transportation engineers and planners better understand the strengths and weaknesses of the two types of model and this should assist decision-makers in choosing a better modeling tool for their planning initiatives.
    Transportation Planning and Technology 06/2015; DOI:10.1080/03081060.2015.1039232
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    ABSTRACT: Integrated land use/transportation forecasting models add significant policy and infrastructure alternatives analysis capabilities to the urban planning process. Historically, the financial, time, and staff requirements to develop one of these models has put them beyond the reach of most small- to medium-sized urban areas. The purpose of this paper is to present the large zone economic submodel of SE3M, an integrated model - founded upon economic base theory and bid-rent theory - that is reasonably accurate, yet simpler in form, function, and implementation than competing models. The US territory of Guam is used as the case study/proof of concept implementation for this model framework. The submodel presented here was validated against a horizon year with known data for zonal level population and employment totals together with control totals for the island as a whole. The model was able - across two base years and one validation, horizon year - to locate all jobs and a high percentage of the population on each zone on the island.
    Transportation Planning and Technology 06/2015; DOI:10.1080/03081060.2015.1039231
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    ABSTRACT: With rail travel largely seen to be a more sustainable method than road-based transport, this paper examines the market segments amongst existing motorists that would be most likely to travel by train in the UK. The analysis is based on a large survey in London and the south-east of England, the area surrounding the routes operated by the train company First Capital Connect. Findings show that train travellers tend to be middle-aged and of a higher social grade, typically taking commuting or business trips. Individuals living within four miles of a station are considerably more likely to travel by rail than those further away. Given the competition from road-based transport, it is of particular interest that the measure highlighted to increase rail use for those living further away from the rail network is to enhance car parking at train stations.
    Transportation Planning and Technology 05/2015; DOI:10.1080/03081060.2015.1039234
  • Transportation Planning and Technology 04/2015; 38(4):442-464. DOI:10.1080/03081060.2015.1026103
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    ABSTRACT: Activity-based models of travel demand have received considerable attention in transportation planning and forecasting in recent years. However, in most cases they use a micro-simulation approach, thereby inevitably including a stochastic error that is caused by the statistical distributions of random components. As a consequence, running a transport micro-simulation model several times with the same input will generate different outputs, which baffles practitioners in applying such a model and in interpreting the results. A common approach is therefore to run the model multiple times and to use the average value of the results. The question then becomes: what is the minimum number of model runs required to reach a stable result? In this paper, systematic experiments are carried out using Forecasting Evolutionary Activity-Travel of Households and their Environmental RepercussionS (FEATHERS), an activity-based micro-simulation modelling framework currently implemented for the Flanders region of Belgium. Six levels of geographic detail are taken into account. Three travel indices - average daily activities per person, average daily trips per person and average daily distance travelled per person, as well as their corresponding segmentations - are calculated by running the model 100 times. The results show that the more disaggregated the level, the larger the number of model runs is needed to ensure confidence. Furthermore, based on the time-dependent origin-destination table derived from the model output, traffic assignment is performed by loading it onto the Flemish road network, and the total vehicle kilometres travelled in the whole Flanders are subsequently computed. The stable results at the Flanders level provides model users with confidence that application of FEATHERS at an aggregated level requires only limited model runs.
    Transportation Planning and Technology 04/2015; 38(4):425-441. DOI:10.1080/03081060.2015.1026102
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    ABSTRACT: This paper examines a case study of the SkyCabs system as a way to alleviate some of the traffic problems of Auckland, New Zealand. SkyCabs is an elevated two-way monobeam carrying light eight-seater cabs on tracks on each side of the beam, available on demand, providing fast, pollution-free, unimpeded travel above the footpath with panoramic views of the city. The aim of this study is to investigate the attractiveness of implementing the SkyCabs system to and from Auckland central business district (CBD) and Auckland international airport by examining four variables: different routes, different number of stops/stations, different passenger demand levels, and different number of cabs in the system. The analysis utilizes geographical information system and simulation tools for the various scenarios considered. The results show that it is possible to assess the cost–benefit of alternative routes in terms of those four variables and rate of return on investment.
    Transportation Planning and Technology 04/2015; 38(3). DOI:10.1080/03081060.2014.997453
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    ABSTRACT: The European Clean Vehicle Directive was introduced in 2009 to create an obligation on public authorities to take into account the impact of energy consumption, carbon dioxide (CO2) emissions and pollutant emissions into their purchasing decisions for road transport vehicles. This should stimulate the market for clean and energy-efficient vehicles and improve transport's impact on environment, climate change and energy use. Therefore the so-called ‘Operational Lifetime Cost’ of a vehicle is calculated, divided into the cost for energy consumption, CO2 and pollutant (nitrous oxide, particulate matter, non-methane hydrocarbons) emissions. In Belgium, a different methodology has been developed to calculate the environmental impact of a vehicle, called ‘Ecoscore’, based on a well-to-wheel approach. More pollutants are included compared to the Clean Vehicle methodology, but also indirect emissions are taken into account. In this paper, both methodologies are compared and used to analyze the environmental performance of passenger cars with different fuel types and from different vehicle segments. Similar rankings between both methodologies are obtained; however, the large impact of energy use (and CO2 emissions) in the Clean Vehicle methodology disadvantages compressed natural gas cars, as well as diesel cars equipped with particulate filters, compared to the Ecoscore methodology.
    Transportation Planning and Technology 02/2015; 38(3):335-346. DOI:10.1080/03081060.2015.1008797
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    ABSTRACT: A new approach for improving the performance of freight train timetabling for single-track railways is proposed. Using the idea of a fixed-block signaling system, we develop a matrix representation to express the occupation of inter- and intra-station tracks by trains illustrating the train blocking time diagram in its entirety. Train departure times, dwell times, and unnecessary stopping are adjusted to reduce average train travel time and single train travel time. Conflicts between successive stations and within stations are identified and solved. A fuzzy logic system is further used to adjust the range of train departure times and checks are made to determine whether dwell times and time intervals can be adjusted for passenger and freight trains at congested stations to minimize train waiting times. By combining manual scheduling expertise with the fuzzy inference method, timetable efficiency is significantly improved and becomes more flexible.
    Transportation Planning and Technology 02/2015; 38(2). DOI:10.1080/03081060.2014.959357
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    ABSTRACT: This paper explores the characteristics of process delays at airport passenger terminals and establishes a queuing model for both passengers and baggage served by different connecting type facilities. The impact of delay propagation on other processes and flights is investigated using an analytical approach. In addition, the extra costs incurred on passengers, process operators, and airlines are examined using the delay cost functions. To reduce the impact of process delays, various delay-controlled strategies are proposed, such as setting scheduled times for completion of a process, increasing the number of service counters, and priority service for emergent flights. Taoyuan International Airport in Taiwan is used as a case study when facing special events. Results showed that the model can effectively and efficiently estimate delay propagation and its costs. In addition, processes that are not consecutive allow more buffer time between different operations, which helps ease propagation of delays caused by previous services.
    Transportation Planning and Technology 02/2015; 38(2). DOI:10.1080/03081060.2014.959358
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    ABSTRACT: Although cluster analysis is recommended by the US Traffic Monitoring Guide (TMG) to supplement the development of seasonal adjustment factor groupings (SAFGs), the relationships among SAFGs' characteristics remain undiscovered, while the determination of the optimal number of clusters is an ambiguous task exposed to great subjectivity. Statistical indicators provide a mathematical solution by removing engineering judgment without taking into consideration any guidelines or other criteria, necessary for transportation planners to generate ‘practical and sensible’ groupings. The method examined in this study aims to overcome the above weaknesses incorporating into the methodology a series of statistics, recommendations, and previous research findings. The investigation of the relationships among (1) the within-group variation, (2) the total number of sites, (3) the minimum number of stations within a cluster, (4) the optimal number of clusters, and (5) the geographical size of the groups constitutes the main objectives of this research. According to the results, the cluster variability declines as the available number of stations increases. When the minimum number of stations within a cluster increases, the weighted coefficient of variation inflates as well, with the rate of increase depending on sample size. The average number of automatic traffic recorders per cluster is analogous to the sample size, while the optimal number of clusters varies conversely with the minimum number of stations within a cluster. The application developed for the conduct of the analysis minimizes the computational time needed, while it can be easily implemented by engineers to automate the process recommended by the TMG, enhancing the current state of practice.
    Transportation Planning and Technology 02/2015; 38(2). DOI:10.1080/03081060.2014.997448
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    ABSTRACT: Disruptions in carrying out planned bus schedules occur daily in many public transit companies. Disturbances are often so large that it is necessary to perform re-planning of planned bus and crew activities. Dispatchers in charge of traffic operations must frequently find an answer to the following question in a very short period of time: How should available buses be distributed among bus routes in order to minimize total passengers' waiting time on the network? We propose a model for assigning buses to scheduled routes when there is a shortage of buses. The proposed model is based on the bee colony optimization (BCO) technique. It is a biologically inspired method that explores collective intelligence applied by honey bees during the nectar collecting process. It has been shown that this developed BCO approach can generate high-quality solutions within negligible processing times.
    Transportation Planning and Technology 01/2015; 38(2):1-19. DOI:10.1080/03081060.2014.997447
  • [Show abstract] [Hide abstract]
    ABSTRACT: This paper reviews the literature on multicriteria decision analysis in transportation and provides a case study of high-speed rail (HSR) corridor/route selection using multicriteria methods in the context of HSR corridor prioritization in Malaysia. Using the screening method proposed by Hagler and Todorovich and the ELECTRE I multicriteria method, it is found that the southbound corridor from Kuala Lumpur to Singapore has the highest priority, followed by the eastbound corridor to Kuantan, and northbound to Georgetown. HSR trains could potentially reduce the trip times to Singapore, Kuantan, and Georgetown from Kuala Lumpur, as compared to driving, by 65–73%. The results of this study can be used to assist in the planning of HSR and/or integrated transportation systems in Malaysia. The same methods can be used to evaluate potential HSR corridors/routes in other countries or regions.
    Transportation Planning and Technology 01/2015; 38(2):1-14. DOI:10.1080/03081060.2014.997446
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    ABSTRACT: Fuel-speed curves (FSC) are used to account for the aggregate effects of congestion on fuel consumption in transportation scenario analysis. This paper presents plausible FSC for conventional internal combustion engine (ICE) vehicles and for advanced vehicles such as hybrid electric vehicles, fully electric vehicles (EVs), and fuel cell vehicles (FCVs) using a fuel consumption model with transient driving schedules and a set of 145 hypothetical vehicles. The FSC shapes show that advanced power train vehicles are expected to maintain fuel economy (FE) in congestion better than ICE vehicles, and FE can even improve for EV and FCV in freeway congestion. In order to implement these FSC for long-range scenario modeling, a bounded approach is presented which uses a single congestion sensitivity parameter. The results in this paper will assist analysis of the roles that vehicle technology and congestion mitigation can play in reducing fuel consumption and greenhouse gas emissions from motor vehicles.
    Transportation Planning and Technology 01/2015; 38(2):1-13. DOI:10.1080/03081060.2014.997449
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    ABSTRACT: A key factor in determining the performance of a railway system is the speed profile of the trains within the network. There can be significant variation in this speed profile for identical trains on identical routes, depending on how the train is driven. A better understanding and control of speed profiles can therefore offer significant potential for improvements in the performance of railway systems. This paper develops a model to allow the variability of real-life driving profiles of railway vehicles to be quantitatively described and predicted, in order to better account for the effects on the speed profile of the train and hence the performance of the railway network as a whole. The model is validated against data from the Tyne and Wear Metro, and replicates the measured data to a good degree of accuracy.
    Transportation Planning and Technology 01/2015; 38(1). DOI:10.1080/03081060.2014.976984