Subjects -> TRANSPORTATION (Total: 214 journals)
    - AIR TRANSPORT (9 journals)
    - AUTOMOBILES (26 journals)
    - RAILROADS (10 journals)
    - ROADS AND TRAFFIC (9 journals)
    - SHIPS AND SHIPPING (43 journals)
    - TRANSPORTATION (117 journals)

TRANSPORTATION (117 journals)                     

Showing 1 - 53 of 53 Journals sorted alphabetically
Accident Analysis & Prevention     Hybrid Journal   (Followers: 128)
Analytic Methods in Accident Research     Hybrid Journal   (Followers: 8)
Applied Mobilities     Hybrid Journal   (Followers: 5)
Asian Transport Studies     Open Access   (Followers: 1)
Botswana Journal of Technology     Full-text available via subscription   (Followers: 1)
Case Studies on Transport Policy     Hybrid Journal   (Followers: 13)
Cities in the 21st Century     Open Access   (Followers: 17)
Communications in Transportation Research     Open Access  
Danish Journal of Transportation Research / Dansk Tidsskrift for Transportforskning     Open Access   (Followers: 1)
Decision Making : Applications in Management and Engineering     Open Access   (Followers: 1)
Economics of Transportation     Partially Free   (Followers: 16)
Emission Control Science and Technology     Hybrid Journal   (Followers: 1)
eTransportation     Open Access   (Followers: 1)
EURO Journal of Transportation and Logistics     Open Access   (Followers: 12)
European Journal of Transport and Infrastructure Research (EJTIR)     Open Access   (Followers: 1)
European Transport Research Review     Open Access   (Followers: 22)
Geosystem Engineering     Hybrid Journal  
IATSS Research     Open Access  
IEEE Open Journal of Intelligent Transportation Systems     Open Access   (Followers: 4)
IEEE Vehicular Technology Magazine     Full-text available via subscription   (Followers: 7)
IET Electrical Systems in Transportation     Open Access   (Followers: 13)
IET Intelligent Transport Systems     Open Access   (Followers: 11)
IET Smart Cities     Open Access  
IFAC-PapersOnLine     Open Access  
International Journal of Applied Logistics     Full-text available via subscription   (Followers: 5)
International Journal of Crashworthiness     Hybrid Journal   (Followers: 10)
International Journal of Electric and Hybrid Vehicles     Hybrid Journal   (Followers: 8)
International Journal of Heavy Vehicle Systems     Hybrid Journal   (Followers: 6)
International Journal of Intelligent Transportation Systems Research     Hybrid Journal   (Followers: 13)
International Journal of Mobile Communications     Hybrid Journal   (Followers: 8)
International Journal of Ocean Systems Management     Hybrid Journal   (Followers: 1)
International Journal of Physical Distribution & Logistics Management     Hybrid Journal   (Followers: 11)
International Journal of Services Technology and Management     Hybrid Journal   (Followers: 1)
International Journal of Sustainable Transportation     Hybrid Journal   (Followers: 18)
International Journal of Traffic and Transportation Engineering     Open Access   (Followers: 12)
International Journal of Transportation Engineering     Open Access   (Followers: 2)
International Journal of Transportation Science and Technology     Open Access   (Followers: 9)
International Journal of Vehicle Systems Modelling and Testing     Hybrid Journal   (Followers: 2)
Journal of Advanced Transportation     Hybrid Journal   (Followers: 12)
Journal of Big Data Analytics in Transportation     Hybrid Journal   (Followers: 2)
Journal of Intelligent and Connected Vehicles     Open Access   (Followers: 1)
Journal of Mechatronics, Electrical Power, and Vehicular Technology     Open Access   (Followers: 6)
Journal of Modern Transportation     Full-text available via subscription   (Followers: 7)
Journal of Navigation     Hybrid Journal   (Followers: 176)
Journal of Sport & Social Issues     Hybrid Journal   (Followers: 10)
Journal of Supply Chain Management Science (JSCMS)     Open Access   (Followers: 3)
Journal of Traffic and Transportation Engineering (English Edition)     Open Access   (Followers: 4)
Journal of Transport & Health     Hybrid Journal   (Followers: 12)
Journal of Transport and Land Use     Open Access   (Followers: 26)
Journal of Transport and Supply Chain Management     Open Access   (Followers: 10)
Journal of Transport Geography     Hybrid Journal   (Followers: 22)
Journal of Transport History     Hybrid Journal   (Followers: 12)
Journal of Transportation and Logistics     Open Access   (Followers: 3)
Journal of Transportation Safety & Security     Hybrid Journal   (Followers: 9)
Journal of Transportation Security     Hybrid Journal   (Followers: 3)
Journal of Transportation Technologies     Open Access   (Followers: 13)
Journal of Waterway Port Coastal and Ocean Engineering     Full-text available via subscription   (Followers: 7)
Journal on Vehicle Routing Algorithms     Hybrid Journal  
Les Dossiers du Grihl     Open Access   (Followers: 1)
LOGI ? Scientific Journal on Transport and Logistics     Open Access  
Logistics     Open Access   (Followers: 1)
Logistics & Sustainable Transport     Open Access   (Followers: 4)
Logistique & Management     Hybrid Journal  
Maritime Transport Research     Open Access  
Mobility in History     Full-text available via subscription   (Followers: 7)
Modern Transportation     Open Access   (Followers: 11)
Nonlinear Dynamics     Hybrid Journal   (Followers: 19)
Open Journal of Safety Science and Technology     Open Access   (Followers: 16)
Open Transportation Journal     Open Access   (Followers: 1)
Packaging, Transport, Storage & Security of Radioactive Material     Hybrid Journal   (Followers: 2)
Periodica Polytechnica Transportation Engineering     Open Access  
Pervasive and Mobile Computing     Hybrid Journal   (Followers: 8)
Proceedings of the Institution of Mechanical Engineers Part F: Journal of Rail and Rapid Transit     Hybrid Journal   (Followers: 11)
Promet : Traffic &Transportation     Open Access  
Public Transport     Hybrid Journal   (Followers: 18)
Recherche Transports Sécurité     Hybrid Journal   (Followers: 1)
Research in Transportation Business and Management     Partially Free   (Followers: 4)
Revista Transporte y Territorio     Open Access  
Romanian Journal of Transport Infrastructure     Open Access   (Followers: 1)
Sport, Education and Society     Hybrid Journal   (Followers: 12)
Sport, Ethics and Philosophy     Hybrid Journal   (Followers: 2)
Streetnotes     Open Access   (Followers: 2)
Synthesis Lectures on Mobile and Pervasive Computing     Full-text available via subscription   (Followers: 1)
Transactions on Transport Sciences     Open Access   (Followers: 4)
Transport     Open Access   (Followers: 16)
Transport and Telecommunication     Open Access   (Followers: 4)
Transport in Porous Media     Hybrid Journal  
Transport Problems     Open Access   (Followers: 4)
Transport Reviews: A Transnational Transdisciplinary Journal     Hybrid Journal   (Followers: 11)
Transportation     Hybrid Journal   (Followers: 32)
Transportation Engineering     Open Access   (Followers: 1)
Transportation Geotechnics     Full-text available via subscription   (Followers: 1)
Transportation in Developing Economies     Hybrid Journal  
Transportation Infrastructure Geotechnology     Hybrid Journal   (Followers: 8)
Transportation Journal     Full-text available via subscription   (Followers: 16)
Transportation Letters : The International Journal of Transportation Research     Hybrid Journal   (Followers: 4)
Transportation Research Interdisciplinary Perspectives     Open Access   (Followers: 2)
Transportation Research Part A: Policy and Practice     Hybrid Journal   (Followers: 38)
Transportation Research Part B: Methodological     Hybrid Journal   (Followers: 38)
Transportation Research Part C: Emerging Technologies     Hybrid Journal   (Followers: 29)
Transportation Research Procedia     Open Access   (Followers: 6)
Transportation Research Record : Journal of the Transportation Research Board     Full-text available via subscription   (Followers: 29)
Transportation Safety and Environment     Open Access   (Followers: 1)
Transportation Science     Full-text available via subscription   (Followers: 25)
Transportation Systems and Technology     Open Access  
TRANSPORTES     Open Access   (Followers: 3)
Transportmetrica A : Transport Science     Hybrid Journal   (Followers: 7)
Transportmetrica B : Transport Dynamics     Hybrid Journal   (Followers: 1)
Travel Behaviour and Society     Full-text available via subscription   (Followers: 9)
Travel Medicine and Infectious Disease     Hybrid Journal   (Followers: 2)
Urban, Planning and Transport Research     Open Access   (Followers: 33)
Vehicles     Open Access  
Vehicular Communications     Full-text available via subscription   (Followers: 4)
World Electric Vehicle Journal     Open Access   (Followers: 3)
World Review of Intermodal Transportation Research     Hybrid Journal   (Followers: 5)
Транспортні системи та технології перевезень     Open Access  

           

Similar Journals
Journal Cover
Transportation
Journal Prestige (SJR): 1.911
Citation Impact (citeScore): 3
Number of Followers: 32  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1572-9435 - ISSN (Online) 0049-4488
Published by Springer-Verlag Homepage  [2469 journals]
  • Effects of high-speed rail on regional accessibility

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      Abstract: Abstract A high-speed rail (HSR) system, which can be developed either by building a new segregated line or upgrading an existing line according to a given set of operational standards, is considered as a competitive solution to improve the accessibility of main destinations. Scientific literature has reported limited contributions regarding the impacts of such infrastructures on the regional systematic mobility and their negative effects on locations excluded from the service. To fill this gap, this paper proposes a method for assessing the implications of regional accessibility on work and study trips, by comparing the two HSR options mentioned above (new segregated or upgraded existing lines). Instead of considering static indicators (e.g., population), the number of train commuters and the variation in travel times for each of the local employment systems crossed by the railway are used as input data. This method is then applied to analyse the territories located along the Venice–Trieste line (in the north-eastern part of Italy) that are characterised by several medium-sized municipalities and crossed by two TEN-T lines. An upgrade of the existing line rather than the construction of a segregated HSR is preferable for local commuters in terms of average travel times and social equity, also considering the expected construction costs. These results complement traditional medium- and long-distance market analyses and may be useful for policymakers to define the most appropriate territorial strategies for the development of specific TEN-T stretches.
      PubDate: 2022-05-15
       
  • Joint and sequential models for freight vehicle type and shipment size
           choice

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      Abstract: Abstract The choice of freight vehicle type and shipment size are among the most important logistics decisions made by firms. An important aspect is the nature of the choice process i.e., whether the two choices are sequential or joint in nature. In this study, we investigate the factors that influence the two choices and develop sequential and nested logit models with both possible sequence or nesting structures i.e., vehicle type first or at upper level and shipment size second or at lower level and vice-versa. A commercial travel survey for the Greater Toronto and Hamilton Area is used to estimate the models. Characteristics of firms including industry type and employment, and characteristics of shipments including commodity type, destination location, and density value are tested. Shipment size is categorized into four categories and four vehicle types are considered. The results show that both sequences and nesting structures are possible. The nested logit model results show a potential correlation among unobserved components of utility for vehicle types (80%) and shipment sizes (38%) which should be considered. Model performance is assessed using rho-squared and BIC value. The results show that the sequential logit model with shipment size first and vehicle type second sequence has the best model fit. However, based on the strong correlation indicated by the nested logit model for vehicle type nested within shipment size choice (second best model), a model reflecting the joint nature of the choice process might be suitable.
      PubDate: 2022-05-14
       
  • Stated benefits of teleworking in Mexico City: a discrete choice
           experiment on office workers

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      Abstract: Commuting is expensive in megacities of emerging economies. By decreasing work-related trips, teleworking may reduce congestion and commuting time. Taking Mexico City’s office workers’ as case study, this paper reports findings from a discrete choice experiment (DCE) exploring willingness to see a cut in monthly paycheck in exchange for teleworking two days a week from a shared office. This DCE explores preferences for bike parking spaces at shared office’s facilities, and walking commuting time to shared office. This design allows estimation of willingness to pay (WTP) for teleworking across commuting time scenarios. Monthly WTP for teleworking 2 days a week starts at (2019) USD 76.68—if commuting time is zero. As 1 h of commuting time is valued at USD 61.97 on a monthly basis, WTP for teleworking 30 min away from home is USD 45.69. Wealthier respondents report higher value for commuting time and WTP for teleworking. Monthly value of bike parking infrastructure is USD 14.70—reaching USD 30.98 for commuters that walk or (motor-)bike less than 50 min. We illustrate how these stated benefits can inform cost-benefit analysis of transportation, housing, and labor policies that enable teleworking and/or reduce commuting times in Mexico City.
      PubDate: 2022-05-08
       
  • Estimation of daily bicycle traffic using machine and deep learning
           techniques

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      Abstract: Abstract Machine learning (ML) architecture has successfully characterized complex motorized volumes and travel patterns; however, non-motorized traffic has given less attention to ML techniques and relied on simple econometric models due to a lack of data for complex modeling. Recent advancements in smartphone-based location data that collect and process large amounts of daily bicycle activities makes the use of machine learning techniques for bicycle volume estimations possible and promising. This study develops eight modeling techniques ranging from advanced techniques, such as Convolution Neural Network (CNN), Deep Neural Network (DNN), Shallow Neural Network (SNN), Random Forest (RF), XGBoost, to conventional and simpler approaches, such as Decision Tree (DT), Negative Binomial (NB), and Multiple Linear Regression, to estimate Daily Bicycle Traffic (DBT). This study uses 6746 daily bicycle volumes collected from 178 permanent and short-term count locations from 2017 to 2019 in Portland, Oregon. A total of 45 independent variables capturing anonymous bicycle user activities (Strava count, bike share), built environments, motorized traffic, and sociodemographic characteristics create comprehensive variable sets for predictive modeling. Two variable dimension reduction techniques using principal component analysis and random forest variable importance analysis ensure that the models are not over-generalized or over-fitted with a large variable set. The comparative analysis between models shows that the SNN and DNN machine learning techniques produce higher accuracies in estimating daily bicycle volumes. The results show that the DNN models predict the DBT with a maximum mean absolute percentage error (MAPE) of 22% while the conventional model (linear regression) shows an APE of 45%.
      PubDate: 2022-04-30
       
  • Fundamental diagram of urban rail transit considering
           train–passenger interaction

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      Abstract: Abstract Urban rail transit often operates with high service frequencies to serve heavy passenger demand during rush hours. Such operations can be delayed by two types of congestion: train congestion and passenger congestion, both of which interact with each other. This delay is problematic for many transit systems, since it can be amplified due to the interaction. However, there are no tractable models describing them; and it makes difficult to analyze management strategies of congested transit systems in general and tractable ways. To fill this gap, this article proposes simple yet physical and dynamic model of urban rail transit. First, a fundamental diagram of transit system (i.e., theoretical relation among train-flow, train-density, and passenger-flow) is analytically derived considering the aforementioned physical interaction. Then, a macroscopic model of transit system for dynamic transit assignment is developed based on the fundamental diagram. Finally, accuracy of the macroscopic model is investigated by comparing to microscopic simulation. The proposed models would be useful for mathematical analysis on management strategies of urban rail transit systems, such as optimal dynamic pricing for travel demand management.
      PubDate: 2022-04-22
       
  • Joint modeling of mode choice and travel distance with intra-household
           interactions

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      Abstract: Abstract Travel mode and distance choices are not independent decisions, and individual choices are usually made in the knowledge of the preference and needs of other household members. To represent the dependency between mode choice and travel distance and the role of intra-household interactions in travel behavior, we develop a joint discrete–continuous model with intra-household interactions. In this model, we use joint household tour as the unit of analysis and characterize the dependency between mode choice and travel distance using flexible copula functions. Then, we apply the proposed model to analyze tour-based mode choice and travel distance in Beijing, China. The results indicate that unobserved factors contribute to positive dependency between mode choice and travel distance. The choice of walk is more dependent on travel distance than other travel modes, and the choice of travel modes except public transit shows a higher correlation with travel distance in complex individual tours than in simple individual and joint household tours. Further, a comparison between the proposed model, the independent model, and the model without intra-household interactions reveals that ignoring the dependency between mode choice and travel distance, or not considering intra-household interactions, could lead to over- or under-estimation of the effects of changes in exogenous variables.
      PubDate: 2022-04-19
       
  • What are the multimodal patterns of individual mobility at the day level
           in the Paris region' A two-stage data-driven approach based on the
           2018 Household Travel Survey

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      Abstract: Abstract Human mobility patterns and their socio-demographic association have been widely studied on travel behavior analysis. To better suit the services of multimodal transport systems, people’s travel behavior needs to be examined at different levels, concerning the complexity of their multimodal trips or trip-chains. This article aims to reveal multimodal patterns of individual mobility and their relationships with socio-demographic characteristics and with travel complexities based on the 2018 Household Travel Survey in the Paris region. To identify the multimodal patterns, a two-stage statistical analysis is conducted. At the first stage (at the trip level), fifteen trip types are identified depending on the categories of travel modes and the degrees of modal trip lengths, duration, and departure time. At the second stage (at the day level), the individuals are characterized by their mobility profiles that are interpreted with the respective frequencies of the fifteen trip types on the day. Based on the profiles, six clusters, i.e., six daily mobility patterns, are obtained. Among the patterns, the daily travel distances vary widely (from 1 to 7 times), as do the daily travel time budgets (from 1 to 3 times). From the relationship analysis, we find that the obtained mobility patterns come along with specific features of car ownership and transit subscription. Socio-demographic associations to the clusters are also distinct. The daily mobility patterns demonstrate an adverse correlation between the trip complexity and the trip chain complexity. The findings in this study could help policy makers to implement concrete strategies for targeted people at multimodality circumstances.
      PubDate: 2022-04-15
       
  • Who should pay' Public acceptance of different means for funding
           transport infrastructure

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      Abstract: Abstract This paper examines acceptance of different ways to fund transport infrastructure. Our methodological approach, stemming from social psychology (attitudes), is based on latent variables. We differentiate between three types of explanatory variables: socioeconomic, (material) self-interest, and personal values. This approach has previously been used to study acceptance of congestion charges, but not (to our knowledge) acceptance of funding alternatives. We conclude that the funding alternatives that are less economically efficient (more deadweight loss per revenue) are unfortunately often the most attractive according to the public. User charges on new infrastructure are popular but might lead to sub-optimal use (since it leads to under usage of the new infrastructure). If charges are also applied to parallel infrastructure, the problem with suppressed demand is reduced, but so is acceptance. VAT (low deadweight loss) is unpopular, whereas income tax (higher deadweight loss) is more accepted. Therefore, politicians will need to handle tradeoffs between acceptance and efficiency. Possible solutions might be found in acceptance theory or by bundling measures. We also find that both context-specific self-interest and broader personal values explain individuals’ preferences towards different funding forms. In many cases the two types of independent variables are highly correlated since variables indicating self-interest against a specific funding form contribute to the formation of general personal values, too. Our results seem to indicate, however, that the explanatory power of more general personal values is larger than that of context-specific self-interest.
      PubDate: 2022-04-13
       
  • Residential self-selection or socio-ecological interaction' the
           effects of sociodemographic and attitudinal characteristics on the built
           environment–travel behavior relationship

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      Abstract: Abstract According to the residential self-selection hypothesis in transportation planning, individual characteristics centering on sociodemographics and attitudes have been conceptualized as antecedent confounders in the built environment–travel behavior relationship (and subsequently, the built environment as a mediator). In medical science, socio-ecological models have been used to designate the individual characteristics and built environment to mutually function as moderators. However, whether individual characteristics (built environment) assume the role of the antecedent (mediator), moderator, or control, has received scant scholarly attention. Using a structural equation model based on the total travel time data of Seoul, this study finds that, by mode of travel, sociodemographics work as moderators for automobile travel and attitudes as antecedents for nonmotorized travel. The sociodemographics/attitudes and built environment are likely to be significant only if their counterpart is also significant. Demographically, the compact built environment tends to reduce automobile travel only for older residents and those who live in larger households. Moreover, travelers with positive attitudes toward daily facilities may self-select into compact neighborhoods and subsequently increase nonmotorized travel.
      PubDate: 2022-04-08
       
  • Understanding California wildfire evacuee behavior and joint choice making

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      Abstract: Abstract For evacuations, people must make the critical decision to evacuate or stay followed by a multi-dimensional choice composed of concurrent decisions of their departure time, transportation mode, route, destination, and shelter type. These choices have important impacts on transportation response and evacuation outcomes. While extensive research has been conducted on hurricane evacuation behavior, little is known about wildfire evacuation behavior. To address this critical research gap, particularly related to joint choice-making in wildfires, we surveyed individuals impacted by the 2017 December Southern California Wildfires (n = 226) and the 2018 Carr Wildfire (n = 284). Using these data, we contribute to the literature in two key ways. First, we develop two latent class choice models (LCCMs) to evaluate the factors that influence the decision to evacuate or stay/defend. We find an evacuation keen class and an evacuation reluctant class that are influenced differently by mandatory evacuation orders. This nuance is further supported by different membership of people to the classes based on demographics and risk perceptions. Second, we develop two portfolio choice models (PCMs), which jointly model choice dimensions to assess multi-dimensional evacuation choice. We find several similarities between wildfires including a joint preference for within-county and nighttime evacuations and a joint dislike for within-county and highway evacuations. Altogether, this paper provides evidence of heterogeneity in response to mandatory evacuation orders for wildfires, distinct membership of populations to different classes of people for evacuating or staying/defending, and clear correlation among key wildfire evacuation choices that necessitates joint modeling to holistically understanding wildfire evacuation behavior.
      PubDate: 2022-04-02
       
  • Understanding the effects of travel demand management on metro
           commuters’ behavioural loyalty: a hybrid choice modelling approach

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      Abstract: Abstract As part of efforts to promote sustainable mobility, many cities are currently experiencing the rapid expansion of their metro network. The consequent growth in ridership motivates a broad range of travel demand management (TDM) policies, both in terms of passenger flow control and dynamic pricing strategies. This work aims to reveal the impact of TDM on metro commuters’ behavioural loyalty using stated-preference data collected in Guangzhou, China. Commuters’ behavioural response to TDM strategies is investigated in terms of the possible shift in departure time and travel mode. A hybrid choice model framework is used to incorporate four latent variables of interest, i.e., service quality, overall impression, external attractiveness and switching cost, into the discrete choice model and thereby capture the relationships between the attitudinal factors and observed variables. The model estimation results indicate that the four latent variables all prove useful in interpreting commuters’ behavioural loyalty. Commuters’ perceived service quality and overall impression both show a positive effect on their willingness to continue travelling by metro and are thus instructive for ridership retention. External attractiveness is found to be significant only in the case of the tendency to shift to a private car. Switching costs reveal commuters’ emotional attachment to their already developed commuting habit. These insights into commuters’ behavioural change intention enable metro operators to enhance commuters’ loyalty to their service and develop more effective TDM strategies in future practice.
      PubDate: 2022-04-01
       
  • Dynamic pricing of free-floating carsharing networks with sensitivity to
           travellers’ attitudes towards risk

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      Abstract: Abstract Free-floating carsharing (FFCS) systems are characterised by volatile fleet distribution as well as customers’ heterogeneous price sensitivity and spatiotemporal flexibility. There is thus an opportunity for operators to employ dynamic pricing to manage various aspects of fleet allocation: which customer is provided which vehicle, at what time and price, and the agreed pick-up and drop-off location. While there are emerging examples of dynamic pricing in FFCS, there is as yet no general framework for the interaction of consumer and operator behaviours in this context, most particularly consumer response to the inherent risks and uncertainties in the journey characteristics noted above. In this study, we propose a choice-based framework for modelling the supply/demand interaction, drawing on behavioural models of decision-making in risky choice contexts and empirical stated-choice data of user preferences in a dynamically priced FFCS market. In addition to the ‘spot market’ mechanism of dynamic pricing, the proposed framework is capable of evaluating operator strategies of allowing (at an agreed price) customers to make guaranteed advance reservations. We demonstrate that this approach allows the system operator to set an optimal pricing strategy regardless of whether user risk preferences are risk-seeking or risk-averse. We also demonstrate the applicability of the proposed framework when the operator seeks to maximise revenue (as with a private operator) vs social welfare (as with a public operator). In the case study which employs empirical user preferences, we show that users’ risk preferences have a relatively small impact on revenue, however the impacts are much larger if there is a mismatch between users’ actual risk preferences and the system operator’s assumptions regarding users’ risk preferences.
      PubDate: 2022-04-01
       
  • The demand impacts of train punctuality in great britain: systematic
           review, meta-analysis and some new econometric insights

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      Abstract: Abstract This paper updates and extends the systematic review and meta-analysis of Wardman and Batley (Transportation 41:1041–1069, 2014), which hitherto was the most comprehensive study of the impacts of punctuality on passenger rail demand in the literature. Whereas the 2014 paper covered 51 elasticities from 6 studies in Great Britain published between 2003 and 2011, this updated paper adds 11 subsequent British studies yielding a further 201 observations. The meta-model recovers a range of significant effects, relating to whether the elasticity was short versus long run, flow type and distance, season versus nonseason tickets, the relevant measure of lateness, and whether the purpose of the study was specifically the estimation of late time elasticities. Allowance was also made for study quality-related issues. The data indicated that, despite dynamic models being commonplace, there is some uncertainty as to how long the long run is. Alongside the meta-model, the paper also reports new econometric evidence that addresses some gaps in existing evidence and knowledge, especially in relation to functional form and non-linearity of effects. Findings from both strands of analysis would seem to suggest that rail industry guidance has tended to overstate the demand impacts of punctuality.
      PubDate: 2022-04-01
       
  • Impacts of Pokémon GO on route and mode choice decisions: exploring the
           potential for integrating augmented reality, gamification, and social
           components in mobile apps to influence travel decisions

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      Abstract: Abstract This study aims to understand the impacts of Pokémon GO, a popular location-based augmented reality (AR) mobile gaming app, on route and mode choices. Pokémon GO leverages AR to introduce virtual objects at fixed and dynamic locations that translate through the app interface to incentives in the real world that potentially influence users’ route and mode choices. Its gaming nature and social components can possibly enhance long-term user engagement through applying the characteristics of game elements and providing opportunities for competition, collaboration, companionship, and social reinforcement. An online survey is conducted to collect the self-reported behavior of a group of Pokémon GO users to explore its impacts on the following aspects of travel behavior: (1) the frequency of changing the route to interact with virtual objects; (2) the likelihood of carpooling more instead of driving alone for more in-app collaboration; and (3) the likelihood of shifting mode from drive alone to public transit, walking, and cycling if provided with additional incentives. The ordered survey responses including frequency and likelihood are analyzed using random parameters ordered probit models to account for the unobserved heterogeneity across users and identify subpopulations of travelers who are more susceptible to the influence of Pokémon GO. The modeling results identify four types of variables (attitude and perceptions related to Pokémon GO, app engagement, play style, and sociodemographic characteristics) that affect users’ travel behavior. The results illustrate that such apps with integrated AR, gamification, and social components can be used by policymakers to influence various aspects of travel behavior. The study findings and insights can provide valuable feedback to system operators for designing such apps to dynamically manage traffic in real-time and promote long-term sustainable mode shifts.
      PubDate: 2022-04-01
       
  • Sentiment analysis of popular-music references to automobiles, 1950s to
           2010s

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      Abstract: Abstract In recent years, there has been a scholarly debate regarding the decrease in automobile-related mobility indicators (car ownership, driving license holding, VMT, etc.). Broadly speaking, two theories have been put forward to explain this trend: (1) economic factors whose impacts are well-understood in principle, but whose occurrence among young adults as a demographic sub-group had been overlooked, and (2) less well-understood shifts in cultural mores, values and sentiment towards the automobile. This second theory is devilishly difficult to study, due primarily to limitations in standard data resources such as the National Household Travel Survey and international peer datasets. In this study we first compiled a database of lyrics to popular music songs from 1956 to 2015 (defined by inclusion in the annual “top 40”), and subsequently identified references to automobiles within this corpus. We then evaluated whether there is support for theory #2 above within popular music, by looking at changes from the 1950s to the 2010s. We demonstrate that the frequency of references to automobility tended for many years to increase over time, however there has more recently been a decline after the late 2000s (decade). In terms of the sentiment of popular music lyrics that reference automobiles, our results are mixed as to whether the references are becoming increasingly positive or negative (machine analysis suggests increasing negativity, while human analysis did not find a significant association), however a consistent observation is that sentiment of automobile references have over time become more positive relative to sentiment of song lyrics overall. We also show that sentiment towards automobile references differs systematically by genre, e.g. automobile references within ‘Rock’ lyrics are in general more negative than similar references to cars in other music genres). The data generated on this project have been archived and made available open access for use by future researchers; details are in the full paper.
      PubDate: 2022-04-01
       
  • Changes in private car ownership associated with car sharing: gauging
           differences by residential location and car share typology

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      Abstract: Abstract While a large body of literature shows that car share encourages low car ownership, the evidence is rather limited in the context of different types of car share (fleet-based versus peer-to-peer) and geographic settings (inner versus middle suburbs). This study was an in-depth investigation of the impact of (round-trip) car share on ownership, including forgone or delayed purchasing across different car share systems. An online survey was conducted with car share members (n = 651) and non-members (n = 290) in Melbourne, Australia. All respondents had a shared car available within a 10-min walk of their home. The first part of the paper compared member and non-member householders (socio-demographically and geographically adjusted) and found that members owned significantly fewer cars than non-members. In the second part of the paper, a quasi-longitudinal comparison of car share members was conducted. One in three households reduced car ownership, and most reductions occurred in the year prior to joining car share. Fleet-based car share members reported a larger reduction in car ownership compared to peer-to-peer car share members. Residents of inner and middle suburbs of Melbourne reported similar "net" reductions in car ownership, the reasons differed. Residents in densely populated inner suburbs used car share to avoid or delay car ownership while middle suburb residents used car share to avoid purchasing a second car. Findings provide valuable insights for transport policy settings which have the potential to influence car share availability and thereby support broader policy objectives to reduce dependency on private car ownership and use.
      PubDate: 2022-04-01
       
  • Perceived risk of lock-in in the front-end phase of major transportation
           projects

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      Abstract: Abstract Lock-in is defined as the tendency to continue with an inefficient decision or project proposal. The front-end phase is critical to project success, yet most studies have focused on lock-in in the implementation phase. Moreover, little is known about the way in which decision-makers perceive the risk of lock-in. In this paper we identify determinants of lock-in in the front-end phase and we reveal decision-makers’ perceptions of risk of lock-in. Our findings show that risk attitudes towards lock-in vary with the level of risk aversion. However, this is not sufficiently acute to drive the level of regret needed to avoid lock-in. This implies that decision-makers do not accurately assess the risk of lock-in and as such their risk perceptions are a mediating factor in the formation of lock-in. Based on escalation of commitment, path dependency, and prospect theory, the main contribution lies in providing a more comprehensive understanding of lock-in in the front-end phase.
      PubDate: 2022-04-01
       
  • A cluster analysis of cyclists in Europe: common patterns, behaviours, and
           attitudes

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      Abstract: Abstract This study uses cluster analysis on a sample of regular cyclists from six European countries (the U.K., the Netherlands, Sweden, Hungary, Italy, and Spain) to shed light on common cycling patterns, demographic characteristics, and attitudes. Participants completed an online survey on cycling behaviour, attitudes towards cycling, discomfort while cycling in mixed traffic, cycling environment and comparative cycling risk perception. A two-step cluster analysis was performed to identify segments of cyclists based on cycling patterns, and a multinomial logistic regression analysis was used to profile the segments. The two-step cluster analysis yielded three components. Leisure-time cyclists cycled almost exclusively for leisure/training, had a clear preference for car use relative to bicycle, and low riding frequency. Resolute Cyclists were characterised by a high variety of cycling trip purpose, a clear preference for bicycle use relative to the car, and high riding frequency. Convenience Cyclists were characterised by cycling for personal business or leisure/training but not for commuting, no evident preference for bicycle vs car, and medium riding frequency. The value of the present study is to highlight commonalities in patterns, characteristics, and attitudes of cyclists in Europe. Our study showed that cycling patterns and habits are linked to psychosocial variables such as attitudes and the cycling environment, explicitly highlighting the importance of discomfort in mixed traffic and the relationship with cycling culture.
      PubDate: 2022-04-01
       
  • The changing accuracy of traffic forecasts

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      Abstract: Abstract Researchers have improved travel demand forecasting methods in recent decades but invested relatively little to understand their accuracy. A major barrier has been the lack of necessary data. We compiled the largest known database of traffic forecast accuracy, composed of forecast traffic, post-opening counts and project attributes for 1291 road projects in the United States and Europe. We compared measured versus forecast traffic and identified the factors associated with accuracy. We found measured traffic is on average 6% lower than forecast volumes, with a mean absolute deviation of 17% from the forecast. Higher volume roads, higher functional classes, shorter time spans, and the use of travel models all improved accuracy. Unemployment rates also affected accuracy—traffic would be 1% greater than forecast on average, rather than 6% lower, if we adjust for higher unemployment during the post-recession years (2008 to 2014). Forecast accuracy was not consistent over time: more recent forecasts were more accurate, and the mean deviation changed direction. Traffic on projects that opened from the 1980s through early 2000s was higher on average than forecast, while traffic on more recent projects was lower on average than forecast. This research provides insight into the degree of confidence that planners and policy makers can expect from traffic forecasts and suggests that we should view forecasts as a range of possible outcomes rather than a single expected outcome.
      PubDate: 2022-04-01
       
  • Do transportation network companies increase or decrease transit
           ridership' Empirical evidence from San Francisco

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      Abstract: Abstract Transportation network companies (TNCs), such as Uber and Lyft, have been hypothesized to both complement and compete with public transit. Existing research on the topic is limited by a lack of detailed data on the timing and location of TNC trips. This study overcomes that limitation by using data scraped from the Application Programming Interfaces of two TNCs, combined with Automated Passenger Count data on transit use and other supporting data. Using a panel data model of the change in bus ridership in San Francisco between 2010 and 2015, and confirming the result with a separate time-series model, we find that TNCs are responsible for a net ridership decline of about 10%, offsetting net gains from other factors such as service increases and population growth. We do not find a statistically significant effect on light rail ridership. Cities and transit agencies should recognize the transit-competitive nature of TNCs as they plan, regulate and operate their transportation systems.
      PubDate: 2022-04-01
       
 
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