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  Subjects -> TRANSPORTATION (Total: 165 journals)
    - AIR TRANSPORT (8 journals)
    - AUTOMOBILES (21 journals)
    - RAILROADS (5 journals)
    - ROADS AND TRAFFIC (6 journals)
    - SHIPS AND SHIPPING (31 journals)
    - TRANSPORTATION (94 journals)

TRANSPORTATION (94 journals)

Showing 1 - 53 of 53 Journals sorted alphabetically
Accident Analysis & Prevention     Partially Free   (Followers: 77)
Analytic Methods in Accident Research     Hybrid Journal   (Followers: 2)
Archives of Transport     Open Access   (Followers: 16)
Botswana Journal of Technology     Full-text available via subscription  
Case Studies on Transport Policy     Hybrid Journal   (Followers: 9)
Cities in the 21st Century     Open Access   (Followers: 13)
Economics of Transportation     Partially Free   (Followers: 13)
Emission Control Science and Technology     Hybrid Journal   (Followers: 2)
EURO Journal of Transportation and Logistics     Hybrid Journal   (Followers: 9)
European Transport Research Review     Open Access   (Followers: 21)
Geosystem Engineering     Hybrid Journal   (Followers: 1)
IATSS Research     Open Access  
IEEE Vehicular Technology Magazine     Full-text available via subscription   (Followers: 8)
IET Electrical Systems in Transportation     Hybrid Journal   (Followers: 9)
IET Intelligent Transport Systems     Hybrid Journal   (Followers: 8)
IFAC-PapersOnLine     Open Access  
International Journal of Applied Logistics     Full-text available via subscription   (Followers: 7)
International Journal of Crashworthiness     Hybrid Journal   (Followers: 7)
International Journal of e-Navigation and Maritime Economy     Open Access   (Followers: 2)
International Journal of Electric and Hybrid Vehicles     Hybrid Journal   (Followers: 9)
International Journal of Heavy Vehicle Systems     Hybrid Journal   (Followers: 6)
International Journal of Intelligent Transportation Systems Research     Hybrid Journal   (Followers: 9)
International Journal of Micro-Nano Scale Transport     Full-text available via subscription   (Followers: 2)
International Journal of Mobile Communications     Hybrid Journal   (Followers: 9)
International Journal of Ocean Systems Management     Hybrid Journal   (Followers: 3)
International Journal of Physical Distribution & Logistics Management     Hybrid Journal   (Followers: 10)
International Journal of Services Technology and Management     Hybrid Journal  
International Journal of Sustainable Transportation     Hybrid Journal   (Followers: 10)
International Journal of Traffic and Transportation Engineering     Open Access   (Followers: 14)
International Journal of Transportation Science and Technology     Full-text available via subscription   (Followers: 9)
International Journal of Vehicle Systems Modelling and Testing     Hybrid Journal   (Followers: 3)
International Journal of Vehicular Technology     Open Access   (Followers: 4)
Journal of Advanced Transportation     Hybrid Journal   (Followers: 11)
Journal of Mechatronics, Electrical Power, and Vehicular Technology     Open Access   (Followers: 5)
Journal of Modern Transportation     Full-text available via subscription   (Followers: 6)
Journal of Navigation     Hybrid Journal   (Followers: 173)
Journal of Sport & Social Issues     Hybrid Journal   (Followers: 11)
Journal of Sustainable Mobility     Full-text available via subscription   (Followers: 1)
Journal of Traffic and Transportation Engineering (English Edition)     Open Access   (Followers: 5)
Journal of Transport & Health     Hybrid Journal   (Followers: 6)
Journal of Transport and Supply Chain Management     Open Access   (Followers: 11)
Journal of Transport Geography     Hybrid Journal   (Followers: 22)
Journal of Transport History     Hybrid Journal   (Followers: 15)
Journal of Transportation Safety & Security     Hybrid Journal   (Followers: 8)
Journal of Transportation Security     Hybrid Journal   (Followers: 3)
Journal of Transportation Systems Engineering and Information Technology     Full-text available via subscription   (Followers: 14)
Journal of Transportation Technologies     Open Access   (Followers: 14)
Journal of Waterway Port Coastal and Ocean Engineering     Full-text available via subscription   (Followers: 6)
Les Dossiers du Grihl     Open Access   (Followers: 1)
Logistics & Sustainable Transport     Open Access   (Followers: 2)
Logistique & Management     Full-text available via subscription  
Modern Transportation     Open Access   (Followers: 10)
Nonlinear Dynamics     Hybrid Journal   (Followers: 5)
Open Journal of Safety Science and Technology     Open Access   (Followers: 8)
Packaging, Transport, Storage & Security of Radioactive Material     Hybrid Journal   (Followers: 2)
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: 12)
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   (Followers: 1)
Romanian Journal of Transport Infrastructure     Open Access   (Followers: 1)
SourceOCDE Transports     Full-text available via subscription   (Followers: 2)
Sport, Education and Society     Hybrid Journal   (Followers: 12)
Sport, Ethics and Philosophy     Hybrid Journal   (Followers: 2)
Streetnotes     Open Access   (Followers: 1)
Synthesis Lectures on Mobile and Pervasive Computing     Full-text available via subscription   (Followers: 2)
Tire Science and Technology     Full-text available via subscription   (Followers: 3)
Transactions on Transport Sciences     Open Access   (Followers: 5)
Transport     Hybrid Journal   (Followers: 13)
Transport and Telecommunication Journal     Open Access   (Followers: 4)
Transport in Porous Media     Hybrid Journal   (Followers: 1)
Transport Problems     Open Access   (Followers: 1)
Transport Reviews: A Transnational Transdisciplinary Journal     Hybrid Journal   (Followers: 9)
Transportation     Hybrid Journal   (Followers: 27)
Transportation Geotechnics     Full-text available via subscription   (Followers: 1)
Transportation Infrastructure Geotechnology     Hybrid Journal   (Followers: 8)
Transportation Journal     Full-text available via subscription   (Followers: 12)
Transportation Letters : The International Journal of Transportation Research     Hybrid Journal   (Followers: 3)
Transportation Research Part A: Policy and Practice     Hybrid Journal   (Followers: 31)
Transportation Research Part B: Methodological     Hybrid Journal   (Followers: 29)
Transportation Research Part C: Emerging Technologies     Hybrid Journal   (Followers: 20)
Transportation Research Procedia     Open Access   (Followers: 4)
Transportation Research Record : Journal of the Transportation Research Board     Full-text available via subscription   (Followers: 34)
Transportation Science     Full-text available via subscription   (Followers: 20)
TRANSPORTES     Open Access   (Followers: 5)
Transportmetrica A : Transport Science     Hybrid Journal   (Followers: 4)
Transportmetrica B : Transport Dynamics     Hybrid Journal   (Followers: 2)
Travel Behaviour and Society     Full-text available via subscription   (Followers: 5)
Travel Medicine and Infectious Disease     Hybrid Journal   (Followers: 2)
Urban, Planning and Transport Research     Open Access   (Followers: 26)
Vehicular Communications     Full-text available via subscription   (Followers: 3)
World Review of Intermodal Transportation Research     Hybrid Journal   (Followers: 5)
Транспортні системи та технології перевезень     Open Access  
Journal Cover Transportation Research Part C: Emerging Technologies
  [SJR: 2.062]   [H-I: 72]   [20 followers]  Follow
    
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 0968-090X
   Published by Elsevier Homepage  [3040 journals]
  • On the tactical and operational train routing selection problem
    • Authors: Marcella Samà; Paola Pellegrini; Andrea D’Ariano; Joaquin Rodriguez; Dario Pacciarelli
      Pages: 1 - 15
      Abstract: Publication date: March 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 76
      Author(s): Marcella Samà, Paola Pellegrini, Andrea D’Ariano, Joaquin Rodriguez, Dario Pacciarelli
      In the real-time railway traffic management problem, the number of alternative routings available to each train strongly affects the size of the problem and the time required to optimally solve it. The train routing selection problem identifies a suitable subset of alternative routings to be used for each train in the real-time railway traffic management. This paper analyzes the impact of solving the train routing selection problem at different levels. The problem can be solved at tactical level right after the timetabling process, using historical traffic data and with abundant computation time. In this case the problem constitutes an integration step between the timetabling and the real-time traffic management. Alternatively, the problem can be solved at operational level right before the real-time railway traffic management problem solution, using up to date traffic perturbation and a real-time time limit of computation. Experiments are performed on two French test cases, the line around Rouen and the Lille station area, for several disturbed and disrupted scenarios. The results show that the best approach depends on the type of traffic disturbance tackled.

      PubDate: 2017-01-11T08:55:14Z
      DOI: 10.1016/j.trc.2016.12.010
      Issue No: Vol. 76 (2017)
       
  • Modelling contact mode and frequency of interactions with social network
           members using the multiple discrete–continuous extreme value model
    • Authors: Chiara Calastri; Stephane Hess; Andrew Daly; Michael Maness; Matthias Kowald; Kay Axhausen
      Pages: 16 - 34
      Abstract: Publication date: March 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 76
      Author(s): Chiara Calastri, Stephane Hess, Andrew Daly, Michael Maness, Matthias Kowald, Kay Axhausen
      Communication patterns are an integral component of activity patterns and the travel induced by these activities. The present study aims to understand the determinants of the communication patterns (by the modes face-to-face, phone, e-mail and SMS) between people and their social network members. The aim is for this to eventually provide further insights into travel behaviour for social and leisure purposes. A social network perspective brings value to the study and modelling of activity patterns since leisure activities are influenced not only by traditional trip measures such as time and cost but also motivated extensively by the people involved in the activity. By using a multiple discrete-continuous extreme value model (Bhat, 2005), we can investigate the means of communication chosen to interact with a given social network member (multiple discrete choices) and the frequency of interaction by each mode (treated as continuous) at the same time. The model also allows us to investigate satiation effects for different modes of communication. Our findings show that in spite of people having increasingly geographically widespread networks and more diverse communication technologies, a strong underlying preference for face-to-face contact remains. In contrast with some of the existing work, we show that travel-related variables at the ego level are less important than specific social determinants which can be considered while making use of social network data.

      PubDate: 2017-01-11T08:55:14Z
      DOI: 10.1016/j.trc.2016.12.012
      Issue No: Vol. 76 (2017)
       
  • Are you in the loop? Using gaze dispersion to understand driver visual
           attention during vehicle automation
    • Authors: Tyron Louw; Natasha Merat
      Pages: 35 - 50
      Abstract: Publication date: March 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 76
      Author(s): Tyron Louw, Natasha Merat
      This driving simulator study, conducted as part of the EC-funded AdaptIVe project, assessed drivers’ visual attention distribution during automation and on approach to a critical event, and examined whether such attention changes following repeated exposure to an impending collision. Measures of drivers’ horizontal and vertical gaze dispersion during both conventional and automated (SAE Level 2) driving were compared on approach to such critical events. Using a between-participant design, 60 drivers (15 in each group) experienced automation with one of four screen manipulations: (1) no manipulation, (2) manipulation by light fog, (3) manipulation by heavy fog, and (4) manipulation by heavy fog with a secondary task, which were used to induce varying levels of engagement with the driving task. Results showed that, during automation, drivers’ horizontal gaze was generally more dispersed than that observed during manual driving. Drivers clearly looked around more when their view of the driving scene was completely blocked by an opaque screen in the heavy fog condition. By contrast, horizontal gaze dispersion was (unsurprisingly) more concentrated when drivers performed a visual secondary task, which was overlaid on the opaque screen. However, once the manipulations ceased and an uncertainty alert captured drivers’ attention towards an impending incident, a similar gaze pattern was found for all drivers, with no carry-over effects observed after the screen manipulations. Results showed that drivers’ understanding of the automated system increased as time progressed, and that scenarios that encourage driver gaze towards the road centre are more likely to increase situation awareness during high levels of automation.

      PubDate: 2017-01-11T08:55:14Z
      DOI: 10.1016/j.trc.2017.01.001
      Issue No: Vol. 76 (2017)
       
  • Understanding ridesplitting behavior of on-demand ride services: An
           ensemble learning approach
    • Authors: Xiqun (Michael) Chen; Majid Zahiri; Shuaichao Zhang
      Pages: 51 - 70
      Abstract: Publication date: March 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 76
      Author(s): Xiqun (Michael) Chen, Majid Zahiri, Shuaichao Zhang
      In this paper, we present an ensemble learning approach for better understanding ridesplitting behavior of passengers of ridesourcing companies who provide prearranged and on-demand transportation services. An ensemble learning model is a weighted combination of multiple classification models or week classifiers to form a strong classification model. The goal of ensemble learning is to combine decisions or predictions of several base classifiers to improve prediction, generalizability, and robustness over a single classifier. This paper employs the Boosting ensemble by growing individual decision trees sequentially and then assembling these trees to produce a powerful classification model. To improve the prediction accuracy of ridesplitting choices, we explored real-world individual level data extracted from the on-demand ride service platform of DiDi in Hangzhou, China. Over one million trips of the four service types, i.e., Taxi Hailing Service, Express, Private Car Service, and Hitch, are explored with descriptive statistics. A variety of features that may impact ridesplitting behavior are ranked and selected by using the ReliefF algorithm, such as trip travel time, trip costs, trip length, waiting time fee, travel time reliability of origins/destinations and so on. The Boosting ensemble trees with full features and selected features are trained and validated using two independent datasets. This paper also verifies that ensemble learning is particularly useful and powerful in the ridesplitting analysis and outperforms three other widely used classifiers. This paper is one of the first quantitative studies that empirically reveal the real-world demand and supply pattern by exploring the city-wide data of an on-demand ride service platform.

      PubDate: 2017-01-11T08:55:14Z
      DOI: 10.1016/j.trc.2016.12.018
      Issue No: Vol. 76 (2017)
       
  • Flexing service schedules: Assessing the potential for demand-adaptive
           hybrid transit via a stated preference approach
    • Authors: Charlotte Frei; Michael Hyland; Hani S. Mahmassani
      Pages: 71 - 89
      Abstract: Publication date: March 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 76
      Author(s): Charlotte Frei, Michael Hyland, Hani S. Mahmassani
      This paper assesses the demand for a flexible, demand-adaptive transit service, using the Chicago region as an example. We designed and implemented a stated-preference survey in order to (1) identify potential users of flexible transit, and (2) inform the service design of the flexible transit mode. Multinomial logit, mixed-logit, and panel mixed-logit choice models were estimated using the data obtained from the survey. The survey instrument employed a dp-efficient design and the Google Maps API to capture precise origins and destinations in order to create realistic choice scenarios. The stated-preference experiments offered respondents a choice between traditional transit, car, and a hypothetical flexible transit mode. Wait time, access time, travel time, service frequency, cost, and number of transfers varied across the choice scenarios. The choice model results indicate mode-specific values of in-vehicle travel time ranging between $16.3 per hour (car) and $21.1 per hour (flexible transit). The estimated value of walking time to transit is $25.9 per hour. The estimated value of waiting time at one’s point of origin for a flexible transit vehicle is $11.3 per hour; this value is significantly lower than the disutility typically associated with waiting at a transit stop/station indicating that the ‘at-home’ pick-up option of flexible transit is a highly desirable feature. The choice model results also indicate that respondents who use active-transport modes or public transit for their current commute trip, or are bikeshare members, were significantly more likely to choose flexible and traditional transit than car commuters in the choice experiments. The implications of these and other relevant model results for the design and delivery of flexible, technology-enabled services are discussed.

      PubDate: 2017-01-11T08:55:14Z
      DOI: 10.1016/j.trc.2016.12.017
      Issue No: Vol. 76 (2017)
       
  • A flexible traffic stream model and its three representations of traffic
           flow
    • Authors: Liang Zheng; Zhengbing He; Tian He
      Pages: 136 - 167
      Abstract: Publication date: February 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 75
      Author(s): Liang Zheng, Zhengbing He, Tian He
      To connect microscopic driving behaviors with the macro-correspondence (i.e., the fundamental diagram), this study proposes a flexible traffic stream model, which is derived from a novel car-following model under steady-state conditions. Its four driving behavior-related parameters, i.e., reaction time, calmness parameter, speed- and spacing-related sensitivities, have an apparent effect in shaping the fundamental diagram. Its boundary conditions and homogenous case are also analyzed in detail and compared with other two models (i.e., Longitudinal Control Model and Intelligent Driver Model). Especially, these model formulations and properties under Lagrangian coordinates provide a new perspective to revisit the traffic flow and complement with those under Eulerian coordinate. One calibration methodology that incorporates the monkey algorithm with dynamic adaptation is employed to calibrate this model, based on real-field data from a wide range of locations. Results show that this model exhibits the well flexibility to fit these traffic data and performs better than other nine models. Finally, a concrete example of transportation application is designed, in which the impact of three critical parameters on vehicle trajectories and shock waves with three representations (i.e., respectively defined in x-t, n-t and x-n coordinates) is tested, and macro- and micro-solutions on shock waves well agree with each other. In summary, this traffic stream model with the advantages of flexibility and efficiency has the good potential in level of service analysis and transportation planning.

      PubDate: 2017-01-01T02:50:05Z
      DOI: 10.1016/j.trc.2016.12.006
      Issue No: Vol. 75 (2017)
       
  • An integrated metro operation optimization to minimize energy consumption
    • Authors: Ning Zhao; Clive Roberts; Stuart Hillmansen; Zhongbei Tian; Paul Weston; Lei Chen
      Pages: 168 - 182
      Abstract: Publication date: February 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 75
      Author(s): Ning Zhao, Clive Roberts, Stuart Hillmansen, Zhongbei Tian, Paul Weston, Lei Chen
      Energy efficient techniques are receiving increasing attention because of rising energy prices and environmental concerns. Railways, along with other transport modes, are facing increasing pressure to provide more intelligent and efficient power management strategies. This paper presents an integrated optimization method for metro operation to minimize whole day substation energy consumption by calculating the most appropriate train trajectory (driving speed profile) and timetable configuration. A train trajectory optimization algorithm and timetable optimization algorithm are developed specifically for the study. The train operation performance is affected by a number of different systems that are closely interlinked. Therefore, an integrated optimization process is introduced to obtain the optimal results accurately and efficiently. The results show that, by using the optimal train trajectory and timetable, the substation energy consumption and load can be significantly reduced, thereby improving the system performance and stability. This also has the effect of reducing substation investment costs for new metros.

      PubDate: 2017-01-01T02:50:05Z
      DOI: 10.1016/j.trc.2016.12.013
      Issue No: Vol. 75 (2017)
       
  • Bike route choice modeling using GPS data without choice sets of paths
    • Authors: Maëlle Zimmermann; Tien Mai; Emma Frejinger
      Pages: 183 - 196
      Abstract: Publication date: February 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 75
      Author(s): Maëlle Zimmermann, Tien Mai, Emma Frejinger
      Concerned by the nuisances of motorized travel on urban life, policy makers are faced with the challenge of making cycling a more attractive alternative for everyday transportation. Route choice models can help achieve this objective by gaining insights into the trade-offs cyclists make when choosing their routes and by allowing the effect of infrastructure improvements to be analyzed. We estimate a link-based bike route choice model from a sample of GPS observations in the city of Eugene on a network comprising over 40,000 links. The so-called recursive logit (RL) model (Fosgerau et al., 2013) does not require to sample any choice set of paths. We show the advantages of this approach in the context of prediction by focusing on two applications of the model: link flows and accessibility measures. Compared to the path-based approach which requires to generate choice sets, the RL model proves to make significant gains in computational time and to avoid paradoxical accessibility measure results discussed in previous works, e.g. Nassir et al. (2014).

      PubDate: 2017-01-01T02:50:05Z
      DOI: 10.1016/j.trc.2016.12.009
      Issue No: Vol. 75 (2017)
       
  • Exploring the capacity of social media data for modelling travel
           behaviour: Opportunities and challenges
    • Authors: Taha H. Rashidi; Alireza Abbasi; Mojtaba Maghrebi; Samiul Hasan; Travis S. Waller
      Pages: 197 - 211
      Abstract: Publication date: February 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 75
      Author(s): Taha H. Rashidi, Alireza Abbasi, Mojtaba Maghrebi, Samiul Hasan, Travis S. Waller
      In the past few years, the social science literature has shown significance attention to extracting information from social media to track and analyse human movements. In this paper the transportation aspect of social media is investigated and reviewed. A detailed discussion is provided about how social media data from different sources can be used to indirectly and with minimal cost extract travel attributes such as trip purpose, mode of transport, activity duration and destination choice, as well as land use variables such as home, job and school location and socio-demographic attributes including gender, age and income. The evolution of the field of transport and travel behaviour around applications of social media over the last few years is studied. Further, this paper presents results of a qualitative survey from travel demand modelling experts around the world on applicability of social media data for modelling daily travel behaviour. The result of the survey reveals positive view of the experts about usefulness of such data sources.

      PubDate: 2017-01-01T02:50:05Z
      DOI: 10.1016/j.trc.2016.12.008
      Issue No: Vol. 75 (2017)
       
  • Robust identification of air traffic flow patterns in Metroplex terminal
           areas under demand uncertainty
    • Authors: Stavros Sidiropoulos; Ke Han; Arnab Majumdar; Washington Y. Ochieng
      Pages: 212 - 227
      Abstract: Publication date: February 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 75
      Author(s): Stavros Sidiropoulos, Ke Han, Arnab Majumdar, Washington Y. Ochieng
      Multi-Airport Systems (MAS), or Metroplexes, serve air traffic demand in cities with two or more airports. Due to the spatial proximity and operational interdependency of the airports, Metroplex airspaces are characterized by high complexity, and current system structures fail to provide satisfactory utilization of the available airspace resources. In order to support system-level design and management towards increased operational efficiency in such systems, an accurate depiction of major demand patterns is a prerequisite. This paper proposes a framework for the robust identification of significant air traffic flow patterns in Metroplex systems, which is aligned with the dynamic route service policy for the effective management of Metroplex operations. We first characterize deterministic demand through a spatio-temporal clustering algorithm that takes into account changes in the traffic flows over the planning horizon. Then, in order to handle uncertainties in the demand, a Distributionally Robust Optimization (DRO) approach is proposed, which takes into account demand variations and prediction errors in a robust way to ensure the reliability of the demand identification. The DRO-based approach is applied on pre-tactical (i.e. one-day planning) as well as operational levels (i.e. 2-h rolling horizon). The framework is applied to Time Based Flow Management (TBFM) data from the New York Metroplex. The framework and results are validated by Subject Matter Experts (SMEs).

      PubDate: 2017-01-01T02:50:05Z
      DOI: 10.1016/j.trc.2016.12.011
      Issue No: Vol. 75 (2017)
       
  • Hybrid cyclicity: Combining the benefits of cyclic and non-cyclic
           timetables
    • Authors: Tomáš Robenek; Shadi Sharif Azadeh; Yousef Maknoon; Michel Bierlaire
      Pages: 228 - 253
      Abstract: Publication date: February 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 75
      Author(s): Tomáš Robenek, Shadi Sharif Azadeh, Yousef Maknoon, Michel Bierlaire
      We propose a new type of timetable that would combine both the regularity of the cyclic timetables and the flexibility of the non-cyclic ones. In order to do so, several combinations of the two timetables are considered. The regularity is incorporated in their design and the flexibility is evaluated using the passenger satisfaction (in monetary units). Each of the tested timetables is constructed using the Passenger Centric Train Timetabling Problem (PCTTP), that is solved using a simulated annealing heuristic. Note that the PCTTP, unlike the traditional Train Timetabling Problem (TTP), does not take into account the conflicts among trains. The aim of the PCTTP is to design such timetables that the passengers’ satisfaction is maximized and it remains the aim of the TTP to remove any potential conflicts. The performance of each of the considered timetables is assessed on the real network of Israeli Railways. The results of the case study show that our proposed hybrid cyclic timetable can provide the benefits of the cyclic and the non-cyclic timetable simultaneously. This timetable consists of 75% of cyclic trains (securing the regularity of the service) and of 25% of non-cyclic trains (deployed as supplementary trains during the peak hours and capturing the demand fluctuation). The level of the passenger satisfaction of the hybrid cyclic timetable is similar to the level of the non-cyclic one, which has about 18.5% of improvement as compared to the purely cyclic one.

      PubDate: 2017-01-11T08:55:14Z
      DOI: 10.1016/j.trc.2016.12.015
      Issue No: Vol. 75 (2017)
       
  • Corrigendum to “Adaptive scheduling for real-time and temporal
           information services in vehicular networks” [Transport. Res. Part C 71
           (2016) 313–332]
    • Authors: Penglin Dai; Kai Liu; Liang Feng; Qingfeng Zhuge; Victor C.S. Lee; Sang H. Son
      Abstract: Publication date: Available online 31 December 2016
      Source:Transportation Research Part C: Emerging Technologies
      Author(s): Penglin Dai, Kai Liu, Liang Feng, Qingfeng Zhuge, Victor C.S. Lee, Sang H. Son


      PubDate: 2017-01-11T08:55:14Z
      DOI: 10.1016/j.trc.2016.12.014
       
  • Large-scale dynamic transportation network simulation: A space-time-event
           parallel computing approach
    • Authors: Yunchao Qu; Xuesong Zhou
      Pages: 1 - 16
      Abstract: Publication date: February 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 75
      Author(s): Yunchao Qu, Xuesong Zhou
      This paper describes a computationally efficient parallel-computing framework for mesoscopic transportation simulation on large-scale networks. By introducing an overall data structure for mesoscopic dynamic transportation simulation, we discuss a set of implementation issues for enabling flexible parallel computing on a multi-core shared memory architecture. First, we embed an event-based simulation logic to implement a simplified kinematic wave model and reduce simulation overhead. Second, we present a space-time-event computing framework to decompose simulation steps to reduce communication overhead in parallel execution and an OpenMP-based space-time-processor implementation method that is used to automate task partition tasks. According to the spatial and temporal attributes, various types of simulation events are mapped to independent logical processes that can concurrently execute their procedures while maintaining good load balance. We propose a synchronous space-parallel simulation strategy to dynamically assign the logical processes to different threads. The proposed method is then applied to simulate large-scale, real-world networks to examine the computational efficiency under different numbers of CPU threads. Numerical experiments demonstrate that the implemented parallel computing algorithm can significantly improve the computational efficiency and it can reach up to a speedup of 10 on a workstation with 32 computing threads.
      Graphical abstract image

      PubDate: 2016-12-25T02:49:54Z
      DOI: 10.1016/j.trc.2016.12.003
      Issue No: Vol. 75 (2016)
       
  • Impacts of weather on public transport ridership: Results from mining data
           from different sources
    • Authors: Meng Zhou; Donggen Wang; Qingquan Li; Yang Yue; Wei Tu; Rui Cao
      Pages: 17 - 29
      Abstract: Publication date: February 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 75
      Author(s): Meng Zhou, Donggen Wang, Qingquan Li, Yang Yue, Wei Tu, Rui Cao
      The existing studies concerning the influence of weather on public transport have mainly focused on the impacts of average weather conditions on the aggregate ridership of public transit. Not much research has examined these impacts at disaggregate levels. This study aims to fill this gap by accounting for intra-day variations in weather as well as public transport ridership and investigating the effect of weather on the travel behavior of individual public transit users. We have collected smart card data for public transit and meteorological records from Shenzhen, China for the entire month of September 2014. The data allow us to establish association between the system-wide public transit ridership and weather condition on not only daily, but also hourly basis and for each metro station. In addition, with the detailed trip records of individual card holders, the travel pattern by public transit are constructed for card holders and this pattern is linked to the weather conditions he/she has experienced. Multivariate modeling approach is applied to analyze the influence of weather on public transit ridership and the travel behavior of regular transit users. Results show that some weather elements have more influence than others on public transportation. Metro stations located in urban areas are more vulnerable to outdoor weather in regard to ridership. Regular transit users are found to be rather resilient to changes in weather conditions. Findings contribute to a more in-depth understanding of the relationship between everyday weather and public transit travels and also provide valuable information for short-term scheduling in transit management.

      PubDate: 2016-12-25T02:49:54Z
      DOI: 10.1016/j.trc.2016.12.001
      Issue No: Vol. 75 (2016)
       
  • Predicting travel time reliability using mobile phone GPS data
    • Authors: Dawn Woodard; Galina Nogin; Paul Koch; David Racz; Moises Goldszmidt; Eric Horvitz
      Pages: 30 - 44
      Abstract: Publication date: February 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 75
      Author(s): Dawn Woodard, Galina Nogin, Paul Koch, David Racz, Moises Goldszmidt, Eric Horvitz
      Estimates of road speeds have become commonplace and central to route planning, but few systems in production provide information about the reliability of the prediction. Probabilistic forecasts of travel time capture reliability and can be used for risk-averse routing, for reporting travel time reliability to a user, or as a component of fleet vehicle decision-support systems. Many of these uses (such as those for mapping services like Bing or Google Maps) require predictions for routes in the road network, at arbitrary times; the highest-volume source of data for this purpose is GPS data from mobile phones. We introduce a method (TRIP) to predict the probability distribution of travel time on an arbitrary route in a road network at an arbitrary time, using GPS data from mobile phones or other probe vehicles. TRIP captures weekly cycles in congestion levels, gives informed predictions for parts of the road network with little data, and is computationally efficient, even for very large road networks and datasets. We apply TRIP to predict travel time on the road network of the Seattle metropolitan region, based on large volumes of GPS data from Windows phones. TRIP provides improved interval predictions (forecast ranges for travel time) relative to Microsoft’s engine for travel time prediction as used in Bing Maps. It also provides deterministic predictions that are as accurate as Bing Maps predictions, despite using fewer explanatory variables, and differing from the observed travel times by only 10.1% on average over 35,190 test trips. To our knowledge TRIP is the first method to provide accurate predictions of travel time reliability for complete, large-scale road networks.

      PubDate: 2016-12-25T02:49:54Z
      DOI: 10.1016/j.trc.2016.10.011
      Issue No: Vol. 75 (2016)
       
  • A mesoscopic integrated urban traffic flow-emission model
    • Authors: Anahita Jamshidnejad; Ioannis Papamichail; Markos Papageorgiou; Bart De Schutter
      Pages: 45 - 83
      Abstract: Publication date: February 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 75
      Author(s): Anahita Jamshidnejad, Ioannis Papamichail, Markos Papageorgiou, Bart De Schutter
      Due to the noticeable environmental and economical problems caused by traffic congestion and by the emissions produced by traffic, analysis and control of traffic is essential. One of the various traffic analysis approaches is the model-based approach, where a mathematical model of the traffic system is developed/used based on the governing physical rules of the system. In this paper, we propose a framework to interface and integrate macroscopic flow models and microscopic emission models. As a result, a new mesoscopic integrated flow-emission model is obtained that provides a balanced trade-off between high accuracy and low computation time. The proposed approach considers an aggregated behavior for different groups of vehicles (mesoscopic) instead of considering the behavior of individual vehicles (microscopic) or the entire group of vehicles (macroscopic). A case study is done to evaluate the proposed framework, considering the performance of the resulting mesoscopic integrated flow-emission model. The traffic simulation software SUMO combined with the microscopic emission model VT-micro is used as the comparison platform. The results of the case study prove that the proposed approach provides excellent results with high accuracy levels. In addition, the mesoscopic nature of the integrated flow-emission model guarantees a low CPU time, which makes the proposed framework suitable for real-time model-based applications.

      PubDate: 2016-12-25T02:49:54Z
      DOI: 10.1016/j.trc.2016.11.024
      Issue No: Vol. 75 (2016)
       
  • Evolution of public transit modes in a commuter corridor
    • Authors: Yanshuo Sun; Qianwen Guo; Paul Schonfeld; Zhongfei Li
      Pages: 84 - 102
      Abstract: Publication date: February 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 75
      Author(s): Yanshuo Sun, Qianwen Guo, Paul Schonfeld, Zhongfei Li
      This paper explores how the selection of public transit modes can be optimized over a planning horizon. This conceptual analysis sacrifices geographic detail in order to better highlight the relations among important factors. First, a set of static models is proposed to identify which type of service, e.g., bus only, rail only, or bus and rail, is the most cost-effective in terms of the average trip cost for given demand. After analyzing essential factors in a long-term planning process, e.g., economies of scale in rail extension and future cost discounting, a dynamic model incorporating such considerations is formulated to optimize the decision over a planning horizon. While analytical solutions can be obtained for some decision variables, the final model is solved with a graphical method by exploring the tradeoffs between the initial and recurring costs. Major findings from this study include: (a) there exists a minimum economic length for a rail line, which can be determined numerically; (b) economies of scale favor large extensions and excess supplied capacity; (c) the rail-only service is largely dominated by the feeder-trunk service, even in the long run.

      PubDate: 2016-12-25T02:49:54Z
      DOI: 10.1016/j.trc.2016.12.007
      Issue No: Vol. 75 (2016)
       
  • A two-dimensional simulation model for modelling turning vehicles at
           mixed-flow intersections
    • Authors: Zian Ma; Jian Sun; Yunpeng Wang
      Pages: 103 - 119
      Abstract: Publication date: February 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 75
      Author(s): Zian Ma, Jian Sun, Yunpeng Wang
      The turning behavior is one of the most challenging driving maneuvers under non-protected phase at mixed-flow intersections. Currently, one-dimensional simulation models focus on car-following and gap-acceptance behaviors in pre-defined lanes with few lane-changing behaviors, and they cannot model the lateral and longitudinal behaviors simultaneously, which has limitation in representing the realistic turning behavior. This paper proposes a three-layered “plan-decision-action” (PDA) framework to obtain acceleration and angular velocity in the turning process. The plan layer firstly calculates the two-dimensional optimal path and dynamically adjusts the trajectories according to interacting objects. The decision layer then uses the decision tree method to select a suitable behavior in three alternatives: car-following, turning and yielding. Finally, in the action layer, a set of corresponding operational models specify the decided behavior into control parameters. The proposed model is tested by reproducing 210 trajectories of left-turn vehicles at a two-phase mixed-flow intersection in Shanghai. As a result, the simulation reproduces the variation of trajectories, while the coverage rate of the trajectories is 88.8%. Meanwhile, both the travel time and post-encroachment time of simulation and empirical turning vehicles are similar and do not show statistically significant difference.

      PubDate: 2016-12-25T02:49:54Z
      DOI: 10.1016/j.trc.2016.12.005
      Issue No: Vol. 75 (2016)
       
  • System energy optimisation strategies for metros with regeneration
    • Authors: Zhongbei Tian; Paul Weston; Ning Zhao; Stuart Hillmansen; Clive Roberts; Lei Chen
      Pages: 120 - 135
      Abstract: Publication date: February 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 75
      Author(s): Zhongbei Tian, Paul Weston, Ning Zhao, Stuart Hillmansen, Clive Roberts, Lei Chen
      Energy and environmental sustainability in transportation are becoming ever more important. In Europe, the transportation sector is responsible for about 30% of the final end use of energy. Electrified railway systems play an important role in contributing to the reduction of energy usage and CO2 emissions compared with other transport modes. For metro-transit systems with frequently motoring and braking trains, the effective use of regenerated braking energy is a significant way to reduce the net energy consumption. Although eco-driving strategies have been studied for some time, a comprehensive understanding of how regeneration affects the overall system energy consumption has not been developed. This paper proposes a multi-train traction power network modelling method to determine the system energy flow of the railway system with regenerating braking trains. The initial results show that minimising traction energy use is not the same as minimising the system energy usage in a metro system. An integrated optimisation method is proposed to solve the system energy-saving problem, which takes train movement and electrical power flow into consideration. The results of a study of the Beijing Yizhuang metro line indicate that optimised operation could reduce the energy consumption at the substations by nearly 38.6% compared to that used with the existing ATO operation.

      PubDate: 2016-12-25T02:49:54Z
      DOI: 10.1016/j.trc.2016.12.004
      Issue No: Vol. 75 (2016)
       
  • Estimation of trip travel time distribution using a generalized Markov
           chain approach
    • Authors: Zhenliang Ma; Haris N. Koutsopoulos; Luis Ferreira; Mahmoud Mesbah
      Pages: 1 - 21
      Abstract: Publication date: January 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 74
      Author(s): Zhenliang Ma, Haris N. Koutsopoulos, Luis Ferreira, Mahmoud Mesbah
      The increasing availability of opportunistic and dedicated sensors is transforming a once data-starved transport field into one of the most data-rich. While link-level travel time information can be derived or inferred from this data, methods for estimation of trip travel times between an origin and a destination pair are still evolving and limited, especially in the context of probability distribution estimation. This paper proposes a generalized Markov chain approach for estimating the probability distribution of trip travel times from link travel time distributions and takes into consideration correlations in time and space. The proposed approach consists of three major components, namely state definition, transition probabilities estimation and probability distribution estimation. A heuristic clustering method, based on Gaussian mixture models, has been developed to cluster link travel time observations with regard to their homogeneity and underlying traffic conditions. A transition probability estimation model is developed as a function of link characteristics and trip conditions using a logit model. By applying a Markov chain procedure, the probability distribution of trip travel times is estimated as the combination of Markov path travel time distributions weighted by their corresponding occurrence probabilities. The link travel time distribution is conditioned on the traffic conditions of the current link that can be estimated from historical observations. A moment generating function based algorithm is used to approximate the Markov path travel time distribution as the sum of correlated link travel time distributions conditional on traffic conditions. The proposed approach is applied in a transit case study using automatic vehicle location data. The results indicate that the method is effective and efficient, especially when correlations and multimodal distributions exist.

      PubDate: 2016-11-18T22:15:22Z
      DOI: 10.1016/j.trc.2016.11.008
      Issue No: Vol. 74 (2016)
       
  • Crash prediction with behavioral and physiological features for advanced
           vehicle collision avoidance system
    • Authors: Yutao Ba; Wei Zhang; Qinhua Wang; Ronggang Zhou; Changrui Ren
      Pages: 22 - 33
      Abstract: Publication date: January 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 74
      Author(s): Yutao Ba, Wei Zhang, Qinhua Wang, Ronggang Zhou, Changrui Ren
      Real-time crash prediction is the key component of the Vehicle Collision Avoidance System (VCAS) and other driver assistance systems. The further improvements of predictability requires the systemic estimation of crash risks in the driver-vehicle-environment loop. Therefore, this study designed and validated a prediction method based on the supervised learning model with added behavioral and physiological features. The data samples were extracted from 130 drivers’ simulator driving, and included various features generated from synchronized recording of vehicle dynamics, distance metrics, driving behaviors, fixations and physiological measures. In order to identify the optimal configuration of proposed method, the Discriminant Analysis (DA) with different features and models (i.e. linear or quadratic) was tested to classify the crash samples and non-crash samples. The results demonstrated the significant improvements of accuracy and specificity with added visual and physiological features. The different models also showed significant effects on the characteristics of sensitivity and specificity. These results supported the effectiveness of crash prediction by quantifying drivers’ risky states as inputs. More importantly, such an approach also provides opportunities to integrate the driver state monitoring into other vehicle-mounted systems at the software level.

      PubDate: 2016-11-18T22:15:22Z
      DOI: 10.1016/j.trc.2016.11.009
      Issue No: Vol. 74 (2016)
       
  • An on-road evaluation of connected motorcycle crash warning interface with
           different motorcycle types
    • Authors: Miao Song; Shane McLaughlin; Zachary Doerzaph
      Pages: 34 - 50
      Abstract: Publication date: January 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 74
      Author(s): Miao Song, Shane McLaughlin, Zachary Doerzaph
      Crash warning systems have been deployed in the high-end vehicle market segment for some time and are trickling down to additional motor vehicle industry segments each year. The motorcycle segment, however, has no deployed crash warning system to date. With the active development of next generation crash warning systems based on connected vehicle technologies, this study explored possible interface designs for motorcycle crash warning systems and evaluated their rider acceptance and effectiveness in a connected vehicle context. Four prototype warning interface displays covering three warning mode alternatives (auditory, visual, and haptic) were designed and developed for motorcycles. They were tested on-road with three connected vehicle safety applications - intersection movement assist, forward collision warning, and lane departure warning - which were selected according to the most impactful crash types identified for motorcycles. Combined auditory and haptic displays showed considerable promise for implementation. Auditory display is easily implemented given the adoption rate of in-helmet auditory systems. Its weakness of presenting directional information in this study may be remedied by using simple speech or with the help of haptic design, which performed well at providing such information and was also found to be attractive to riders. The findings revealed both opportunities and challenges of visual displays for motorcycle crash warning systems. More importantly, differences among riders of three major motorcycle types (cruiser, sport, and touring) in terms of rider acceptance of a motorcycle crash warning system were revealed. Based on the results, recommendations were provided for an appropriate crash warning interface design for motorcycles and riders in a connected vehicle environment.

      PubDate: 2016-11-18T22:15:22Z
      DOI: 10.1016/j.trc.2016.11.005
      Issue No: Vol. 74 (2016)
       
  • Optimizing train operational plan in an urban rail corridor based on the
           maximum headway function
    • Authors: Feng Shi; Shuo Zhao; Zhao Zhou; Pu Wang; Michael G.H. Bell
      Pages: 51 - 80
      Abstract: Publication date: January 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 74
      Author(s): Feng Shi, Shuo Zhao, Zhao Zhou, Pu Wang, Michael G.H. Bell
      The train operational plan (TOP) plays a crucial role in the efficient and effective operation of an urban rail system. We optimize the train operational plan in a special network layout, an urban rail corridor with one terminal yard, by decomposing it into two sub-problems, i.e., the train departure profile optimization and the rolling stock circulation optimization. The first sub-problem synthetically optimizes frequency setting, timetabling and the rolling stock circulation at the terminal without a yard. The maximum headway function is generated to ensure the service of the train operational plan without considering travel demand, then we present a model to minimize the number of train trips, and design a heuristic algorithm to maximize the train headway. On the basis of a given timetable, the rolling stock circulation optimization only involves the terminal with a yard. We propose a model to minimize the number of trains and yard–station runs, and an algorithm to find the optimal assignment of train-trip pair connections is designed. The computational complexities of the two algorithms are both linear. Finally, a real case study shows that the train operational plan developed by our approach enables a better match of train headway and travel demand, and reduces the operational cost while satisfying the requirement of the level of service.

      PubDate: 2016-11-18T22:15:22Z
      DOI: 10.1016/j.trc.2016.11.007
      Issue No: Vol. 74 (2016)
       
  • Bus arrival time calculation model based on smart card data
    • Authors: Yuyang Zhou; Lin Yao; Yanyan Chen; Yi Gong; Jianhui Lai
      Pages: 81 - 96
      Abstract: Publication date: January 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 74
      Author(s): Yuyang Zhou, Lin Yao, Yanyan Chen, Yi Gong, Jianhui Lai
      Bus arrival time is usually estimated using the boarding time of the first passenger at each station. However, boarding time data are not recorded in certain double-ticket smart card systems. As many passengers usually swipe the card much before their alighting, the first or the average alighting time cannot represent the actual bus arrival time, either. This lack of data creates difficulties in correcting bus arrival times. This paper focused on developing a model to calculate bus arrival time that combined the alighting swiping time from smart card data with the actual bus arrival time by the manual survey data. The model was built on the basis of the frequency distribution and the regression analysis. The swiping time distribution, the occupancy and the seating capacity were considered as the key factors in creating a method to calculate bus arrival times. With 1011 groups of smart card data and 360 corresponding records from a manual survey of bus arrival times, the research data were divided into two parts stochastically, a training set and a test set. The training set was used for the parameter determination, and the test set was used to verify the model’s precision. Furthermore, the regularity of the time differences between the bus arrival times and the card swiping times was analyzed using the “trend line” of the last swiping time distribution. Results from the test set achieved mean and standard error rate deviations of 0.6% and 3.8%, respectively. The proposed model established in this study can improve bus arrival time calculations and potentially support state prediction and service level evaluations for bus operations.

      PubDate: 2016-11-26T01:34:51Z
      DOI: 10.1016/j.trc.2016.11.014
      Issue No: Vol. 74 (2016)
       
  • Editorial for the virtual special issue on “Advances in alternative fuel
           vehicle transportation systems”
    • Authors: Eric Yongxi Huang; Michael Kuby; Joseph Y.J. Chow
      Pages: 97 - 98
      Abstract: Publication date: January 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 74
      Author(s): Eric Yongxi Huang, Michael Kuby, Joseph Y.J. Chow


      PubDate: 2016-11-18T22:15:22Z
      DOI: 10.1016/j.trc.2016.11.012
      Issue No: Vol. 74 (2016)
       
  • Airline crew pairing with fatigue: Modeling and analysis
    • Authors: Burak C. Yildiz; Fatma Gzara; Samir Elhedhli
      Pages: 99 - 112
      Abstract: Publication date: January 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 74
      Author(s): Burak C. Yildiz, Fatma Gzara, Samir Elhedhli
      Crew fatigue is one of the main causes of airline accidents. Regulatory authorities such as the Federal Aviation Agency constantly introduce new fatigue regulations, often in the form of hard constraints on the length of duty and rest periods. The complex nature of travel-related fatigue, however, makes it difficult to account for it indirectly through such constraints. Recent studies show that fatigue depends on human factors such as the homeostatic process and the circadian body clock as well as time-zone differences. In this work, we explicitly account for fatigue in crew pairing optimization through the Three Process Model of Alertness, one of the most comprehensive fatigue models available in the literature. We provide a mathematical model for the crew pairing problem that incorporates fatigue and solve it using a column generation approach. Numerical analysis on two real data sets reveals that the proposed approach is able to reduce the crew fatigue levels substantially with minimal impact on cost. In particular, it is shown that hard constraints on fatigue may still lead to high fatigue levels and that jet-lag and time-zone differences have a major impact. The results of the tests also show that some of the rules and regulations in practice may be omitted if the fatigue is accounted for directly.

      PubDate: 2016-11-26T01:34:51Z
      DOI: 10.1016/j.trc.2016.11.002
      Issue No: Vol. 74 (2016)
       
  • Estimation of driving style in naturalistic highway traffic using maneuver
           transition probabilities
    • Authors: Guofa Li; Shengbo Eben Li; Bo Cheng; Paul Green
      Pages: 113 - 125
      Abstract: Publication date: January 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 74
      Author(s): Guofa Li, Shengbo Eben Li, Bo Cheng, Paul Green
      Accurately estimating driving styles is crucial to designing useful driver assistance systems and vehicle control systems for autonomous driving that match how people drive. This paper presents a novel way to identify driving style not in terms of the durations or frequencies of individual maneuver states, but rather the transition patterns between them to see how they are interrelated. Driving behavior in highway traffic was categorized into 12 maneuver states, based on which 144 (12×12) maneuver transition probabilities were obtained. A conditional likelihood maximization method was employed to extract typical maneuver transition patterns that could represent driving style strategies, from the 144 probabilities. Random forest algorithm was adopted to classify driving styles using the selected features. Results showed that transitions concerning five maneuver states – free driving, approaching, near following, constrained left and right lane changes – could be used to classify driving style reliably. Comparisons with traditional methods were presented and discussed in detail to show that transition probabilities between maneuvers were better at predicting driving style than traditional maneuver frequencies in behavioral analysis.
      Graphical abstract image

      PubDate: 2016-11-26T01:34:51Z
      DOI: 10.1016/j.trc.2016.11.011
      Issue No: Vol. 74 (2016)
       
  • Strategic assessment of capacity consumption in railway networks:
           Framework and model
    • Authors: Lars Wittrup Jensen; Alex Landex; Otto Anker Nielsen; Leo G. Kroon; Marie Schmidt
      Pages: 126 - 149
      Abstract: Publication date: January 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 74
      Author(s): Lars Wittrup Jensen, Alex Landex, Otto Anker Nielsen, Leo G. Kroon, Marie Schmidt
      In this paper, we develop a new framework for strategic planning purposes to calculate railway infrastructure occupation and capacity consumption in networks, independent of a timetable. Furthermore, a model implementing the framework is presented. In this model different train sequences are generated and assessed to obtain timetable independence. A stochastic simulation of delays is used to obtain the capacity consumption. The model is tested on a case network where four different infrastructure scenarios are considered. Both infrastructure occupation and capacity consumption results are obtained efficiently with little input. The case illustrates the model’s ability to quantify the capacity gain from infrastructure scenario to infrastructure scenario which can be used to increase the number of trains or improve the robustness of the system.

      PubDate: 2016-11-26T01:34:51Z
      DOI: 10.1016/j.trc.2016.10.013
      Issue No: Vol. 74 (2016)
       
  • A new methodology for vehicle trajectory reconstruction based on wavelet
           analysis
    • Authors: Mehdi Rafati Fard; Afshin Shariat Mohaymany; Matin Shahri
      Pages: 150 - 167
      Abstract: Publication date: January 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 74
      Author(s): Mehdi Rafati Fard, Afshin Shariat Mohaymany, Matin Shahri
      Vehicle trajectories with high spatial and temporal resolution are known as the most ideal source of data for developing innovative microscopic traffic models. Aside from the method applied for collecting the vehicle trajectories, such data are more or less error-infected. The ever-increasing noise amplitude during the process of deriving the data (such as speed and acceleration) required for developing models, might change or even hide the structure of data and lead to useful information being overlooked. This highlights the importance of presenting the efficient methods which are adequate to remove noise and enhance the quality of vehicle trajectory data. Accordingly, in this paper a simple two-step technique based on wavelet analysis has been recommended for filtering errors and reconstructing trajectory data. Primarily, by using wavelet transform a special treatment was employed to identify and modify the outliers. Next, the noise in trajectory data was eliminated by applying the wavelet-based filter. The results of applying the proposed method to the synthetic noise-infected trajectory and the NGSIM dataset reveal how appropriate its performance is compared with other methodologies in terms of quantitative criteria.

      PubDate: 2016-11-26T01:34:51Z
      DOI: 10.1016/j.trc.2016.11.010
      Issue No: Vol. 74 (2016)
       
  • Short-term traffic flow prediction using time-varying Vasicek model
    • Authors: Yalda Rajabzadeh; Amir Hossein Rezaie; Hamidreza Amindavar
      Pages: 168 - 181
      Abstract: Publication date: January 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 74
      Author(s): Yalda Rajabzadeh, Amir Hossein Rezaie, Hamidreza Amindavar
      This paper provides a two-step approach based on the stochastic differential equations (SDEs) to improve short-term prediction. In the first step of this framework, a Hull-White (HW) model is applied to obtain a baseline prediction model from previous days. Then, the extended Vasicek model (EV) is employed for modeling the difference between observations and baseline predictions (residuals) during an individual day. The parameters of this time-varying model are estimated at each sample using the residuals in a short duration of time before the time point of prediction; so it provides a real time prediction. The extracted model recovers the valuable local variation information during each day. The performance of our method in comparison with other methods improves significantly in terms of root mean squared error (RMSE), mean absolute error (MAE) and mean relative error (MRE) for real data from Tehran’s highways and the open-access PeMS database. We also demonstrate that the proposed model is appropriate for imputing the missing data in traffic dataset and it is more efficient than the probabilistic principal component analysis (PPCA) and k-Nearest neighbors (k-NN) methods.

      PubDate: 2016-12-03T08:41:05Z
      DOI: 10.1016/j.trc.2016.11.001
      Issue No: Vol. 74 (2016)
       
  • Integrated planning of park-and-ride facilities and transit service
    • Authors: Ziqi Song; Yi He; Lihui Zhang
      Pages: 182 - 195
      Abstract: Publication date: January 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 74
      Author(s): Ziqi Song, Yi He, Lihui Zhang
      This paper proposes an integrated planning framework to locate park-and-ride (P&R) facilities and optimize their capacities as well as transit service frequencies simultaneously. P&R users’ route choice behavior is explicitly considered, and a link-based multimodal user equilibrium model is established. The optimal location and capacity of P&R facilities and transit service design problem is formulated as a mathematical program with complementarity constraints (MPCC), and a solution algorithm based on the active-set approach is developed to solve the optimal design problem effectively. A numerical example is employed to demonstrate that the optimal design shifts commuters from the automobile mode to transit and P&R modes and, hence improves the net social benefit dramatically.

      PubDate: 2016-12-03T08:41:05Z
      DOI: 10.1016/j.trc.2016.11.017
      Issue No: Vol. 74 (2016)
       
  • Recent success stories on integrated optimization of railway systems
    • Authors: Ralf Borndörfer; Torsten Klug; Leonardo Lamorgese; Carlo Mannino; Markus Reuther; Thomas Schlechte
      Pages: 196 - 211
      Abstract: Publication date: January 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 74
      Author(s): Ralf Borndörfer, Torsten Klug, Leonardo Lamorgese, Carlo Mannino, Markus Reuther, Thomas Schlechte
      Planning and operating railway transportation systems is an extremely hard task due to the combinatorial complexity of the underlying discrete optimization problems, the technical intricacies, and the immense size of the problem instances. Because of that, however, mathematical models and optimization techniques can result in large gains for both railway customers and operators, e.g., in terms of cost reductions or service quality improvements. In the last years a large and growing group of researchers in the OR community have devoted their attention to this domain developing mathematical models and optimization approaches to tackle many of the relevant problems in the railway planning process. However, there is still a gap to bridge between theory and practice (e.g. Cacchiani et al., 2014; Borndörfer et al., 2010), with a few notable exceptions. In this paper we address three individual success stories, namely, long-term freight train routing (part I), mid-term rolling stock rotation planning (part II), and real-time train dispatching (part III). In each case, we describe real-life, successful implementations. We will discuss the individual problem setting, survey the optimization literature, and focus on particular aspects addressed by the mathematical models. We demonstrate on concrete applications how mathematical optimization can support railway planning and operations. This gives proof that mathematical optimization can support the planning of railway resources. Thus, mathematical models and optimization can lead to a greater efficiency of railway operations and will serve as a powerful and innovative tool to meet recent challenges of the railway industry.

      PubDate: 2016-12-03T08:41:05Z
      DOI: 10.1016/j.trc.2016.11.015
      Issue No: Vol. 74 (2016)
       
  • Designing an integrated distribution system for catering services for
           high-speed railways: A three-echelon location routing model with tight
           time windows and time deadlines
    • Authors: Xin Wu; Lei Nie; Meng Xu
      Pages: 212 - 244
      Abstract: Publication date: January 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 74
      Author(s): Xin Wu, Lei Nie, Meng Xu
      An emerging task in catering services for high-speed railways (CSHR) is to design a distribution system for the delivery of high-quality perishable food products to trains in need. This paper proposes a novel model for integrating location decision making with daily rail catering operations, which are affected by various aspects of rail planning, to meet time-sensitive passenger demands. A three-echelon location routing problem with time windows and time budget constraints (3E-LRPTWTBC) is thus proposed toward formulating this integrated distribution system design problem. This model attempts to determine the capacities/locations of distribution centers and to optimize the number of meals delivered to stations. The model also attempts to generate a schedule for refrigerated cars traveling from distribution centers to rail stations for train loading whereby meals can be catered to trains within tight time windows and sold before a specified time deadline. By relaxing the time-window constraints, a relaxation model that can be solved using an off-the-shelf mixed integer programming (MIP) solver is obtained to provide a lower bound on the 3E-LRPTWTBC. A hybrid cross entropy algorithm (HCEA) is proposed to solve the 3E-LRPTWTBC. A small-scale case study is implemented, which reveals a 9.3% gap between the solution obtained using the HCEA and that obtained using the relaxation model (RM). A comparative analysis of the HCEA and an exhaustive enumeration algorithm indicates that the HCEA shows good performance in terms of computation time. Finally, a case study considering 156 trains on the Beijing-Shanghai high-speed corridor and a large-scale case study considering 1130 trains on the Chinese railway network are addressed in a comprehensive study to demonstrate the applicability of the proposed models and algorithm.

      PubDate: 2016-12-03T08:41:05Z
      DOI: 10.1016/j.trc.2016.11.006
      Issue No: Vol. 74 (2016)
       
  • A systemic modelling of ground handling services using the functional
           resonance analysis method
    • Authors: Milena Studic; Arnab Majumdar; Wolfgang Schuster; Washington Y. Ochieng
      Pages: 245 - 260
      Abstract: Publication date: January 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 74
      Author(s): Milena Studic, Arnab Majumdar, Wolfgang Schuster, Washington Y. Ochieng
      In contrast to air transport safety, safety in ground handling is not concerned only with aircraft accidents but also the Occupational Health and Safety of the employees who work at airport aprons. Ground handling safety costs the aviation industry tens of billions USD every year which raises the questions about the effectiveness of linear safety risk management of Ground Handling Services (GHS). This paper uses the state-of-the-art safety theory to justify and highlight the need for a systemic approach to safety risk management of GHS on the apron. A hybrid Total Apron Safety Management (TASM) framework, based on the combination of Functional Resonance Analysis Method (FRAM), Grounded Theory, Template Analysis and Goals-Means Task Analysis (GMTA) was developed to support systemic safety modelling of GHS. The data that underpins the TASM framework includes extensive literature review, 15 observations, 43 interviews and expert judgement across five international airports. While the TASM framework can be applied in retrospective, prospective and system design analysis to improve both the safety management and the efficiency of apron operations, this paper showcases only one of its application on a case study of a historical safety occurrence. The results of the investigation carried out in this paper clearly demonstrate the benefits of the systemic as opposed to the existing linear approaches to retrospective safety analyses and the suitability of the TASM framework for occurrence analysis and prevention.

      PubDate: 2016-12-03T08:41:05Z
      DOI: 10.1016/j.trc.2016.11.004
      Issue No: Vol. 74 (2016)
       
  • Optimization of horizontal alignment geometry in road design and
           reconstruction
    • Authors: Gerardo Casal; Duarte Santamarina; Miguel E. Vázquez-Méndez
      Pages: 261 - 274
      Abstract: Publication date: January 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 74
      Author(s): Gerardo Casal, Duarte Santamarina, Miguel E. Vázquez-Méndez
      This paper presents a general formulation for optimization of horizontal road alignment, composed of tangential segments and circular curves suitably connected with transition curves (clothoids). It consists of a constrained optimization problem where the objective function is given by a line integral along the layout. The integrand is a function representing the cost of the road going through each point and, by considering different costs, a wide range of problems can be included in this formulation. To show it, we apply this methodology to three different situations. The two first cases are related with the design of a new road layout and used to solve a pair of academic examples. The third problem deals with the improvement of a road adapting the old path to current legislation, and it is solved taking as case study the reconstruction project for a regional road (NA-601) in the north of Spain.

      PubDate: 2016-12-03T08:41:05Z
      DOI: 10.1016/j.trc.2016.11.019
      Issue No: Vol. 74 (2016)
       
  • Analytical and simulation approaches to understand combined effects of
           transit signal priority and road-space priority measures
    • Authors: Long Tien Truong; Graham Currie; Majid Sarvi
      Pages: 275 - 294
      Abstract: Publication date: January 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 74
      Author(s): Long Tien Truong, Graham Currie, Majid Sarvi
      Transit signal priority (TSP) may be combined with road-space priority (RSP) measures to increase its effectiveness. Previous studies have investigated the combination of TSP and RSP measures, such as TSP with dedicated bus lanes (DBLs) and TSP with queue jump lanes (QJLs). However, in these studies, combined effects are usually not compared with separate effects of each measure. In addition, there is no comprehensive study dedicated to understanding combined effects of TSP and RSP measures. It remains unclear whether combining TSP and RSP measures creates an additive effect where the combined effect of TSP and RSP measures is equal to the sum of their separate effects. The existence of such an additive effect would suggest considerable benefits from combining TSP and RSP measures. This paper explores combined effects of TSP and RSP measures, including TSP with DBLs and TSP with QJLs. Analytical results based on time-space diagrams indicate that at an intersection level, the combined effect on bus delay savings is smaller than the additive effect if there is no nearside bus stop and the traffic condition in the base case is under-saturated or near-saturated. With a near-side bus stop, the combined effect on bus delay savings at an intersection level can be better than the additive effect (or over-additive effect), depending on dwell time, distance from the bus stop to the stop line, traffic demand, and cycle length. In addition, analytical results suggest that at an arterial level, the combined effect on bus delay savings can be the over-additive effect with suitable signal offsets. These results are confirmed by a micro-simulation case study. Combined effects on arterial and side-street traffic delays are also discussed.

      PubDate: 2016-12-03T08:41:05Z
      DOI: 10.1016/j.trc.2016.11.020
      Issue No: Vol. 74 (2016)
       
  • Assessing the impact of reduced visibility on traffic crash risk using
           microscopic data and surrogate safety measures
    • Authors: Yichuan Peng; Mohamed Abdel-Aty; Qi Shi; Rongjie Yu
      Pages: 295 - 305
      Abstract: Publication date: January 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 74
      Author(s): Yichuan Peng, Mohamed Abdel-Aty, Qi Shi, Rongjie Yu
      Due to the difficulty of obtaining accurate real-time visibility and vehicle based traffic data at the same time, there are only few research studies that addressed the impact of reduced visibility on traffic crash risk. This research was conducted based on a new visibility detection system by mounting visibility sensor arrays combined with adaptive learning modules to provide more accurate visibility detections. The vehicle-based detector, Wavetronix SmartSensor HD, was installed at the same place to collect traffic data. Reduced visibility due to fog were selected and analyzed by comparing them with clear cases to identify the differences based on several surrogate measures of safety under different visibility classes. Moreover, vehicles were divided into different types and the vehicles in different lanes were compared in order to identify whether the impact of reduced visibility due to fog on traffic crash risk varies depending on vehicle types and lanes. Log-Inverse Gaussian regression modeling was then applied to explore the relationship between time to collision and visibility together with other traffic parameters. Based on the accurate visibility and traffic data collected by the new visibility and traffic detection system, it was concluded that reduced visibility would significantly increase the traffic crash risk especially rear-end crashes and the impact on crash risk was different for different vehicle types and for different lanes. The results would be helpful to understand the change in traffic crash risk and crash contributing factors under fog conditions. We suggest implementing the algorithms in real-time and augmenting it with ITS measures such as VSL and DMS to reduce crash risk.

      PubDate: 2016-12-03T08:41:05Z
      DOI: 10.1016/j.trc.2016.11.022
      Issue No: Vol. 74 (2016)
       
  • Development of signal optimization models for asymmetric two-leg
           continuous flow intersections
    • Authors: Xianfeng Yang; Yao Cheng
      Pages: 306 - 326
      Abstract: Publication date: January 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 74
      Author(s): Xianfeng Yang, Yao Cheng
      Despite extensive studies have been reported to address the operational issues of full Continuous Flow Intersection (CFI) in the literature, the asymmetric two-leg CFI, which is more applicable in practice, has not received adequate attentions yet. To satisfy such need, this study develops two signal optimization models for asymmetric CFI based on its unique geometric features. The first proposed model, following a two-step procedure, determines the cycle length, phase design and sequence, and green split in the first step and optimizes intersection offset in the second step. To benefit both intersections’ capacity maximization and signal progression design by optimizing phase plan and sequence, the second proposed model takes the Mixed-Integer-Linear-Programming (MILP) technique to concurrently optimize all signal control variables. With extensive case studies on a field site in Maryland, the simulation results prove that the proposed models can effectively provide signal progression to critical path-flows and prevent the potential queue spillover on the short turning bays/links. Further comparisons between the two proposed models reveal that the second model is more flexible in designing phase plan but the first model performs better in reducing link queue length.

      PubDate: 2016-12-03T08:41:05Z
      DOI: 10.1016/j.trc.2016.11.021
      Issue No: Vol. 74 (2016)
       
  • An optimization model for integrated planning of railway traffic and
           network maintenance
    • Authors: Tomas Lidén; Martin Joborn
      Pages: 327 - 347
      Abstract: Publication date: January 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 74
      Author(s): Tomas Lidén, Martin Joborn
      Railway transportation systems are important for society and have many challenging and important planning problems. Train services as well as maintenance of a railway network need to be scheduled efficiently, but have mostly been treated as two separate planning problems. Since these activities are mutually exclusive they must be coordinated and should ideally be planned together. In this paper we present a mixed integer programming model for solving an integrated railway traffic and network maintenance problem. The aim is to find a long term tactical plan that optimally schedules train free windows sufficient for a given volume of regular maintenance together with the wanted train traffic. A spatial and temporal aggregation is used for controlling the available network capacity. The properties of the proposed model are analyzed and computational experiments on various synthetic problem instances are reported. Model extensions and possible modifications are discussed as well as future research directions.

      PubDate: 2016-12-10T08:49:02Z
      DOI: 10.1016/j.trc.2016.11.016
      Issue No: Vol. 74 (2016)
       
  • Using survival models to estimate bus travel times and associated
           uncertainties
    • Authors: Zhengyao Yu; Jonathan S. Wood; Vikash V. Gayah
      Pages: 366 - 382
      Abstract: Publication date: January 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 74
      Author(s): Zhengyao Yu, Jonathan S. Wood, Vikash V. Gayah
      Transit agencies often provide travelers with point estimates of bus travel times to downstream stops to improve the perceived reliability of bus transit systems. Prediction models that can estimate both point estimates and the level of uncertainty associated with these estimates (e.g., travel time variance) might help to further improve reliability by tempering user expectations. In this paper, accelerated failure time survival models are proposed to provide such simultaneous predictions. Data from a headway-based bus route serving the Pennsylvania State University-University Park campus were used to estimate bus travel times using the proposed survival model and traditional linear regression frameworks for comparison. Overall, the accuracy of point estimates from the two approaches, measured using the root-mean-squared errors (RMSEs) and mean absolute errors (MAEs), was similar. This suggests that both methods predict travel times equally well. However, the survival models were found to more accurately describe the uncertainty associated with the predictions. Furthermore, survival model estimates were found to have smaller uncertainties on average, especially when predicted travel times were small. Tests for transferability over time suggested that the models did not over-fit the dataset and validated the predictive ability of models established with historical data. Overall, the survival model approach appears to be a promising method to predict both expected bus travel times and the uncertainty associated with these travel times.

      PubDate: 2016-12-10T08:49:02Z
      DOI: 10.1016/j.trc.2016.11.013
      Issue No: Vol. 74 (2016)
       
  • Algorithms to find shortest and alternative paths in free flow and
           congested traffic regimes
    • Authors: Alberto Faro; Daniela Giordano
      Pages: 1 - 29
      Abstract: Publication date: December 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 73
      Author(s): Alberto Faro, Daniela Giordano
      Location-based systems can be very helpful to mobile users if they are able to suggest shortest paths to destination taking into account the actual traffic conditions. This would allow to inform the drivers not only about the current shortest paths to destination but also about alternative, timely computed paths to avoid being trapped in the traffic jams signaled by cyber-physical-social systems. To this aim, the paper proposes a set of algorithms that solve very fast the All Pair Shortest Paths problem in both the free flow and congested traffic regimes, for road networks of medium-large size, thus enabling location-based systems to deal with emergencies and critical traffic conditions in city and metropolitan areas, whose transport networks typically range from some hundreds to many thousands of nodes, respectively. The paths to avoid being trapped in the traffic jams are computed by using a simulation of the shockwave propagation, instead of historical data. A parallel version of the algorithms is also proposed to solve the All Pair Shortest Paths problem for metropolitan areas with very large road networks. A time performance analysis of the proposed algorithms for transport networks of various size is carried out.

      PubDate: 2016-10-21T18:03:15Z
      DOI: 10.1016/j.trc.2016.09.009
      Issue No: Vol. 73 (2016)
       
  • Information-traffic coupled cell transmission model for information
           spreading dynamics over vehicular ad hoc network on road segments
    • Authors: Lili Du; Siyuan Gong; Lu Wang; Xiang-Yang Li
      Pages: 30 - 48
      Abstract: Publication date: December 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 73
      Author(s): Lili Du, Siyuan Gong, Lu Wang, Xiang-Yang Li
      Vehicular Ad Hoc Network (VANET) makes real-time traffic information accessible to vehicles en routes, thus possesses a great potential to improve traffic safety and mobility in the near future. Existing literature shows that we are still lack of approaches to track information spreading dynamics via VANET, which will prevent the potential applications from success. Motivated by this view, this research develops an information-traffic coupled cell transmission model (IT-CTM) to capture information spreading dynamics via VANET. More exactly, this study considers information spreading over a road segment forms a wave with a front and tail, each of which goes through the road segment following an intermittent transmission pattern due to traffic flow dynamics. The approach of IT-CTM discretizes a road segment into a number of cells. Each cell covers several intermittent transmissions. Mathematical methods are developed to capture the inner-cell and inter-cell movements of information front and tail, which enable us to track the information spreading dynamics along cells. Numerical experiments based on simulation and field data indicate that the IT-CTM can closely track the dynamic movements of information front and tail as well as the dynamic information coverage as a single or multiple piece(s) of information propagating via VANET on a one-way or two-way road segment. The mean absolute error (MAE) for tracking dynamic information coverage is <5% across all experiments in this study.

      PubDate: 2016-10-21T18:03:15Z
      DOI: 10.1016/j.trc.2016.10.007
      Issue No: Vol. 73 (2016)
       
  • A delay root cause discovery and timetable adjustment model for enhancing
           the punctuality of railway services
    • Authors: Wei-Hsun Lee; Li-Hsien Yen; Chien-Ming Chou
      Pages: 49 - 64
      Abstract: Publication date: December 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 73
      Author(s): Wei-Hsun Lee, Li-Hsien Yen, Chien-Ming Chou
      Knock-on delay, which is the key factor in punctuality of railway service, is mainly related to two factors including the quality of timetable in the planning phase and disturbances which may result in unscheduled trains’ waiting or meeting in operation phase. If the delay root cause and the interactions among the factors responsible for these can be clearly clarified, then the punctuality of railway operations can be enhanced by taking reactions such as timetable adjustment, rescheduling or rerouting of railway traffic in case of disturbances. These delay reasons can be used to predict the lengths of railway disruptions and effective reactions can be applied in disruption management. In this work, a delay root cause discovery model is proposed, which integrates heterogeneous railway operation data sources to reconstruct the details of the railway operations. A supervised decision tree method following the machine learning and data mining techniques is designed to estimate the key factors in knock-on delays. It discovers the root cause delay factor by logically analyzing the scheduled or un-scheduled trains meetings and overtaking behaviors, and the subsequent delay propagations. Experiment results show that the proposed decision tree can predict the delay reason with the accuracy of 83%, and it can be further enhance to 90% if the delay cause is only considered “prolonged passengers boarding” and “meeting or overtaking” factors. The delay root cause can be discovered by the proposed model, verified by frequency filtering in operation records, and resolved by the adjustment of timetable which is an important reference for the next timetable rescheduling. The results of this study can be applied to railway operation decision support and disruption management, especially with regard to timetable rescheduling, trains resequencing or rerouting, system reliability analysis, and service quality improvements.

      PubDate: 2016-10-28T21:44:40Z
      DOI: 10.1016/j.trc.2016.10.009
      Issue No: Vol. 73 (2016)
       
  • Editorial Board/Copyright Information
    • Abstract: Publication date: January 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 74


      PubDate: 2016-12-25T02:49:54Z
       
  • Incident detection methods using probe vehicles with on-board GPS
           equipment
    • Authors: Yasuo Asakura; Takahiko Kusakabe; Long Xuan Nguyen; Takamasa Ushiki
      Abstract: Publication date: Available online 4 December 2016
      Source:Transportation Research Part C: Emerging Technologies
      Author(s): Yasuo Asakura, Takahiko Kusakabe, Long Xuan Nguyen, Takamasa Ushiki
      Mobile communication instruments have made detecting traffic incidents possible by using floating traffic data. This paper studies the properties of traffic flow dynamics during incidents and proposes incident detection methods using floating data collected by probe vehicles equipped with on-board global positioning system (GPS) equipment. The proposed algorithms predict the time and location of traffic congestion caused by an incident. The detection rate and false rate of the models are examined using a traffic flow simulator, and the performance measures of the proposed methods are compared with those of previous methods.

      PubDate: 2016-12-10T08:49:02Z
      DOI: 10.1016/j.trc.2016.11.023
       
  • An eigenmodel for iterative line planning, timetabling and vehicle
           scheduling in public transportation
    • Authors: Anita
      Abstract: Publication date: January 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 74
      Author(s): Anita Schöbel
      Planning a public transportation system is a multi-objective problem which includes among others line planning, timetabling, and vehicle scheduling. For each of these planning stages, models are known and advanced solution techniques exist. Some of the models focus on costs, others on passengers’ convenience. Setting up a transportation system is usually done by optimizing each of these stages sequentially. In this paper we argue that instead of optimizing each single step further and further it would be more beneficial to consider the whole process in an integrated way. To this end, we develop and discuss a generic, bi-objective model for integrating line planning, timetabling, and vehicle scheduling. We furthermore propose an eigenmodel which we apply for these three planning stages and show how it can be used for the design of iterative algorithms as heuristics for the integrated problem. The convergence of the resulting iterative approaches is analyzed from a theoretical point of view. Moreover, we propose an agenda for further research in this field.

      PubDate: 2016-12-10T08:49:02Z
       
  • Editorial Board/Copyright Information
    • Abstract: Publication date: December 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 73


      PubDate: 2016-11-26T01:34:51Z
       
  • Mining and correlating traffic events from human sensor observations with
           official transport data using self-organizing-maps
    • Authors: Enrico Steiger; Bernd Resch Porto Albuquerque Alexander Zipf
      Abstract: Publication date: December 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 73
      Author(s): Enrico Steiger, Bernd Resch, João Porto de Albuquerque, Alexander Zipf
      Cities are complex systems, where related Human activities are increasingly difficult to explore within. In order to understand urban processes and to gain deeper knowledge about cities, the potential of location-based social networks like Twitter could be used a promising example to explore latent relationships of underlying mobility patterns. In this paper, we therefore present an approach using a geographic self-organizing map (Geo-SOM) to uncover and compare previously unseen patterns from social media and authoritative data. The results, which we validated with Live Traffic Disruption (TIMS) feeds from Transport for London, show that the observed geospatial and temporal patterns between special events (r =0.73), traffic incidents (r =0.59) and hazard disruptions (r =0.41) from TIMS, are strongly correlated with traffic-related, georeferenced tweets. Hence, we conclude that tweets can be used as a proxy indicator to detect collective mobility events and may help to provide stakeholders and decision makers with complementary information on complex mobility processes.

      PubDate: 2016-11-04T21:53:27Z
       
  • Railroad caller districting with reliability, contiguity, balance, and
           compactness considerations
    • Authors: Siyang Xie; Yanfeng Ouyang
      Abstract: Publication date: December 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 73
      Author(s): Siyang Xie, Yanfeng Ouyang
      Railroad companies rely on good call centers to reliably handle incoming crew/resource call demands so as to maintain efficient operations and customer services in their networks. This paper formulates a reliable caller districting problem which aims at partitioning an undirected network into a fixed number of districts. The demand of each district is assigned to crew caller desks (one primary desk, multiple backups) under possible desk disruption scenarios. We simultaneously take into account several operational criteria, such as district contiguity and compactness, workload balance, and caller desk service reliability. The resulted districting problem is modeled in the form of a challenging mixed-integer program, and we develop a customized heuristic algorithm (based on constructive heuristic and neighborhood search) to provide near-optimum solutions in a reasonable amount of time. Hypothetical and empirical numerical examples are presented to demonstrate the performance and effectiveness of our methodology for different network sizes and parameter settings. Managerial insights are also drawn.

      PubDate: 2016-11-04T21:53:27Z
       
  • A robust approach for road users classification using the motion cues
    • Authors: Haider Talib; Karim Ismail Ali Kassim
      Abstract: Publication date: December 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 73
      Author(s): Haider Talib, Karim Ismail, Ali Kassim
      Video monitoring of traffic is a common practice in major cities. The data generated by video monitoring has practical uses such as traffic analysis for city planning. However, the usefulness of video monitoring of traffic is limited unless there is also a reliable way to automatically classify road users. This paper presents an automated method of road users’ classification into vehicles, cyclists, and pedestrians by using their motion cues. In this method, the movement of road users was captured on sequences of video frames. The videos were analysed using a feature-based tracking system, which has returned the tracks of road users. The separate pieces of information gained from these tracks are hereafter called Classifiers. There are nineteen classifiers included in this method. The classifiers’ values were assessed and integrated into a fuzzy membership framework, which in turn required prior configurations to be available. This led to the final classification of road users. The performance of this method demonstrated promising results. An important contribution of this paper is the creation of a robust approach that can integrate different classifiers using fuzzy membership framework. The developed method also uses parametric classifiers, which do not depend on the specific geometry or traffic operation of the intersection. This is a key advantage because it enables transferability and improves the practicality and usefulness of the method.

      PubDate: 2016-11-04T21:53:27Z
       
 
 
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