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  Subjects -> TRANSPORTATION (Total: 134 journals)
    - AIR TRANSPORT (5 journals)
    - AUTOMOBILES (20 journals)
    - RAILROADS (4 journals)
    - ROADS AND TRAFFIC (4 journals)
    - SHIPS AND SHIPPING (15 journals)
    - TRANSPORTATION (86 journals)

TRANSPORTATION (86 journals)

Accident Analysis & Prevention     Partially Free   (Followers: 17)
AI & Society     Hybrid Journal   (Followers: 2)
Archives of Transport     Open Access   (Followers: 4)
Bitácora Urbano-Territorial     Open Access   (Followers: 2)
Cities in the 21st Century     Open Access   (Followers: 10)
Economics of Transportation     Partially Free   (Followers: 12)
EURO Journal of Transportation and Logistics     Hybrid Journal   (Followers: 4)
European Transport Research Review     Open Access   (Followers: 10)
Geosystem Engineering     Hybrid Journal   (Followers: 3)
IATSS Research     Open Access  
IEEE Vehicular Technology Magazine     Full-text available via subscription   (Followers: 5)
IET Electrical Systems in Transportation     Hybrid Journal   (Followers: 3)
IET Intelligent Transport Systems     Hybrid Journal   (Followers: 4)
International Innovation – Transport     Open Access   (Followers: 2)
International Journal of Applied Logistics     Full-text available via subscription   (Followers: 4)
International Journal of Crashworthiness     Hybrid Journal   (Followers: 5)
International Journal of Critical Infrastructure Protection     Hybrid Journal   (Followers: 5)
International Journal of Electric and Hybrid Vehicles     Hybrid Journal   (Followers: 3)
International Journal of Electronic Transport     Hybrid Journal   (Followers: 2)
International Journal of Heavy Vehicle Systems     Hybrid Journal   (Followers: 6)
International Journal of Intelligent Transportation Systems Research     Hybrid Journal   (Followers: 6)
International Journal of Micro-Nano Scale Transport     Full-text available via subscription   (Followers: 2)
International Journal of Mobile Communications     Hybrid Journal   (Followers: 7)
International Journal of Ocean Systems Management     Hybrid Journal   (Followers: 3)
International Journal of Physical Distribution & Logistics Management     Hybrid Journal   (Followers: 6)
International Journal of Services Technology and Management     Hybrid Journal  
International Journal of Sustainable Transportation     Hybrid Journal   (Followers: 6)
International Journal of Traffic and Transportation Engineering     Open Access   (Followers: 14)
International Journal of Transportation Science and Technology     Full-text available via subscription   (Followers: 4)
International Journal of Vehicle Systems Modelling and Testing     Hybrid Journal   (Followers: 4)
International Journal of Vehicular Technology     Open Access   (Followers: 2)
Journal of Advanced Transportation     Hybrid Journal   (Followers: 10)
Journal of Modern Transportation     Full-text available via subscription   (Followers: 1)
Journal of Navigation     Hybrid Journal   (Followers: 19)
Journal of Sport & Social Issues     Hybrid Journal   (Followers: 7)
Journal of Sustainable Mobility     Full-text available via subscription  
Journal of the Transportation Research Forum     Open Access   (Followers: 3)
Journal of Transport and Land Use     Open Access   (Followers: 9)
Journal of Transport and Supply Chain Management     Open Access   (Followers: 5)
Journal of Transport Geography     Hybrid Journal   (Followers: 12)
Journal of Transport History     Full-text available via subscription   (Followers: 10)
Journal of Transport Literature     Open Access  
Journal of Transportation Safety & Security     Hybrid Journal   (Followers: 6)
Journal of Transportation Security     Hybrid Journal   (Followers: 2)
Journal of Transportation Systems Engineering and Information Technology     Full-text available via subscription   (Followers: 12)
Journal of Transportation Technologies     Open Access   (Followers: 8)
Journal of Waterway Port Coastal and Ocean Engineering     Full-text available via subscription   (Followers: 5)
Les Dossiers du Grihl     Open Access  
Logistique & Management     Full-text available via subscription  
Mechatronics, Electrical Power, and Vehicular Technology     Open Access  
Modern Transportation     Open Access   (Followers: 2)
Nonlinear Dynamics     Hybrid Journal   (Followers: 5)
Open Journal of Safety Science and Technology     Open Access   (Followers: 3)
Pervasive and Mobile Computing     Hybrid Journal   (Followers: 9)
Proceedings of the Institution of Mechanical Engineers Part F: Journal of Rail and Rapid Transit     Hybrid Journal   (Followers: 4)
PS: Political Science & Politics     Full-text available via subscription   (Followers: 18)
Public Transport     Hybrid Journal   (Followers: 10)
Recherche Transports Sécurité     Hybrid Journal   (Followers: 1)
Research in Transportation Business and Management     Partially Free   (Followers: 3)
Revista Transporte y Territorio     Open Access   (Followers: 1)
SourceOCDE Transports     Full-text available via subscription   (Followers: 1)
Sport, Education and Society     Hybrid Journal   (Followers: 10)
Sport, Ethics and Philosophy     Hybrid Journal   (Followers: 2)
Streetnotes     Open Access   (Followers: 2)
Synthesis Lectures on Mobile and Pervasive Computing     Full-text available via subscription   (Followers: 2)
Tire Science and Technology     Full-text available via subscription  
Transactions on Transport Sciences     Open Access   (Followers: 3)
Transport     Hybrid Journal   (Followers: 7)
Transport and Telecommunication Journal     Open Access   (Followers: 2)
Transport in Porous Media     Hybrid Journal  
Transport Reviews: A Transnational Transdisciplinary Journal     Hybrid Journal   (Followers: 5)
Transportation     Hybrid Journal   (Followers: 13)
Transportation Infrastructure Geotechnology     Hybrid Journal   (Followers: 3)
Transportation Journal     Full-text available via subscription   (Followers: 5)
Transportation Research Part A: Policy and Practice     Hybrid Journal   (Followers: 21)
Transportation Research Part B: Methodological     Hybrid Journal   (Followers: 20)
Transportation Research Part C: Emerging Technologies     Hybrid Journal   (Followers: 12)
Transportation Research Record : Journal of the Transportation Research Board     Full-text available via subscription   (Followers: 26)
Transportation Science     Full-text available via subscription   (Followers: 15)
TRANSPORTES     Open Access   (Followers: 2)
Transportmetrica A : Transport Science     Hybrid Journal   (Followers: 1)
Transportmetrica B : Transport Dynamics     Hybrid Journal  
Travel Medicine and Infectious Disease     Hybrid Journal   (Followers: 2)
Urban, Planning and Transport Research     Open Access   (Followers: 2)
World Review of Intermodal Transportation Research     Hybrid Journal   (Followers: 4)
Транспортні системи та технології перевезень     Open Access  
Journal Cover Transportation Research Part C: Emerging Technologies
   Journal TOC RSS feeds Export to Zotero [14 followers]  Follow    
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
     ISSN (Print) 0968-090X
     Published by Elsevier Homepage  [2563 journals]   [SJR: 1.605]   [H-I: 47]
  • Estimating risk effects of driving distraction: A dynamic errorable
           car-following model
    • Abstract: Publication date: Available online 10 September 2014
      Source:Transportation Research Part C: Emerging Technologies
      Author(s): Jay Przybyla , Jeffrey Taylor , Jason Jupe , Xuesong Zhou
      This paper aims to estimate the risk effects of distracted driving, by incorporating a dynamic, data-driven car-following model in an algorithmic framework. The model was developed to predict the situational risk associated with distracted driving. To obtain longitudinal driving patterns, this paper analyzed and synthesized the NGSIM naturalistic driver and traffic database, through a dynamic time warping algorithm, to identify essential driver behavior and characteristics. Cognitive psychology concepts, distracted driving simulator, and experimental data were adapted to examine the probabilistic nature of distracted driving due to internal vehicle distractions. An extended microscopic car-following model was developed and validated, which can be fully integrated with the naturalistic data and incorporate the probabilities of driver distraction.


      PubDate: 2014-09-13T23:31:52Z
       
  • A user equilibrium, traffic assignment model of network route and parking
           lot choice, with search circuits and cruising flows
    • Abstract: Publication date: Available online 11 September 2014
      Source:Transportation Research Part C: Emerging Technologies
      Author(s): Fabien Leurent , Houda Boujnah
      The paper provides a novel network model of parking and route choice. Parking supply is represented by parking type, management strategy including the fare, capacity and occupancy rate of parking lot, and network location, in relation to access routes along the roadway network. Trip demand is segmented according to origin–destination pair, the disposal of private parking facilities and the individual preferences for parking quality of service. Each traveller is assumed to make a two stage choice of, first, network route on the basis of the expected cost of route and parking and, second, local diversion on the basis of a discrete choice model. Search circuits are explicitly considered on the basis of the success probability to get a slot at a given lot and of the transition probabilities between lots in case of failure. The basic endogenous model variables are the route flows, the lot success probabilities and the transition probabilities between lots. These give rise to the cost of a travel route up to a target lot and to the expected cost of search and park from that lot to the destination. Traffic equilibrium is defined in a static setting. It is characterized by a mixed problem of variational inequality and fixed point. Equilibrium is shown to exist under mild conditions and a Method of Successive Averages is put forward to solve for it. Lastly, a planning instance is given to illustrate the effects of insufficient parking capacity on travel costs and network flows.


      PubDate: 2014-09-13T23:31:52Z
       
  • Editorial Board/Copyright Information
    • Abstract: Publication date: September 2014
      Source:Transportation Research Part C: Emerging Technologies, Volume 46




      PubDate: 2014-09-08T22:58:12Z
       
  • Evaluation and spatial analysis of automated red-light running enforcement
           cameras
    • Abstract: Publication date: Available online 4 September 2014
      Source:Transportation Research Part C: Emerging Technologies
      Author(s): Mohamed M. Ahmed , Mohamed Abdel-Aty
      Red light cameras may have a demonstrable impact on reducing the frequency of red light running violations; however, their effect on the overall safety at intersections is still up for debate. This paper examined the safety impacts of Red Light Cameras (RLCs) on traffic crashes at signalized intersections using the Empirical Bayes (EB) method. Data were obtained from the Florida Department of Transportation for twenty-five RLC equipped intersections in Orange County, Florida. Additional fifty intersections that remained with no photo enforcement in the vicinity of the treated sites were collected to examine the spillover effects on the same corridors. The safety evaluation was performed at three main levels; only target approaches where RLCs were installed, all approaches on RLC intersections, and non-RLC intersections located on the same travel corridors as the camera equipped intersections. Moreover, the spatial spillover effects of RLCs were also examined on an aggregate level to evaluate the safety impacts on driver behavior at a regional scale. The results from this study indicated that there was a consistent significant reduction in angle and left-turn crashes and a significant increase in rear-end crashes on target approaches, in addition, the magnitude and the direction of these effects, to a lesser degree, were found similar on the whole intersection. Similar trends in shift of crash types were spilled-over to non-RLC intersections in the proximity of the treated sites. On an aggregate county level, there was a moderate spillover benefits with a notable crash migration to the boundary of the county.


      PubDate: 2014-09-08T22:58:12Z
       
  • Optimal aircraft scheduling and routing at a terminal control area during
           disturbances
    • Abstract: Publication date: Available online 4 September 2014
      Source:Transportation Research Part C: Emerging Technologies
      Author(s): Marcella Samà , Andrea D’Ariano , Paolo D’Ariano , Dario Pacciarelli
      This paper addresses the real-time problem of aircraft scheduling and routing in terminal control area. A main task of traffic controllers is to mitigate the effects of severe traffic disturbances on the day of operations in the Terminal Control Area (TCA) of an airport. When managing disturbed take-off and landing operations, they need to minimize the delay propagation and, in addition, to reduce the aircraft travel time and energy consumption. The paper tackles the problem of developing effective decision support tools for air traffic monitoring and control in a busy TCA. To this purpose, centralized and rolling horizon traffic control paradigms are implemented and compared. The mathematical formulation is a detailed model of air traffic flows in the TCA based on alternative graphs, that are generalized disjunctive graphs. As for the aircraft scheduling and (re-)routing approaches, the First-In-First-Out (FIFO) rule, used as a surrogate for the behavior of air traffic controllers, is compared with various optimization-based approaches including a branch and bound algorithm for aircraft scheduling with fixed routes, a combined branch and bound and tabu search algorithm for aircraft scheduling and re-routing, and a mixed integer linear programming formulation for simultaneous scheduling and routing. Various hypothetical disturbance scenarios are simulated for a real-world airport case study, Milano Malpensa, and the proposed timing and routing approaches are compared in terms of their performance in the different scenarios. The disturbed traffic situations are generated by simulating multiple delayed arriving/departing aircraft and a temporarily disrupted runway. In general, the optimization approaches are found to improve the solutions significantly compared to FIFO, in terms of aircraft delay minimization. However, there are some trade-offs involved in picking the right approach and paradigms for practical implementations.


      PubDate: 2014-09-08T22:58:12Z
       
  • Applying telecommunications methodology to road safety for rear-end
           collision avoidance
    • Abstract: Publication date: Available online 19 August 2014
      Source:Transportation Research Part C: Emerging Technologies
      Author(s): Francesco Benedetto , Alessandro Calvi , Fabrizio D’Amico , Gaetano Giunta
      This work aims at applying telecommunications methodologies to road safety for preventing rear-end collisions. This contribution can be considered as a pilot study to verify and assess the reliability of a new model and procedure for collision warning system based on low-cost inter-vehicular communications (only a cheap radio transmitter/receiver mounted on each vehicle is needed), where Global Positioning Systems (GPS) and other distance vector-based networks are not employed. A signal processing method, namely the binomial test, aimed at detecting approaching sources in infrastructure-less vehicular communications is here proposed and discussed. The detection probability of the method is evaluated versus several driving conditions, in terms of relative speeds and distances between vehicles. In addition, the Time To Collision (TTC), generally required before declaring a correct detection by existing collision systems implemented in recent vehicles, is evaluated for several driving scenarios characterized by different setting parameters. Our numerical results confirm the validity of such an approach in preventing rear-end collisions, allowing a fast detection of approaching sources.


      PubDate: 2014-09-02T22:23:01Z
       
  • The impact of mobile phone distraction on the braking behaviour of young
           drivers: A hazard-based duration model
    • Abstract: Publication date: Available online 23 August 2014
      Source:Transportation Research Part C: Emerging Technologies
      Author(s): Md. Mazharul Haque , Simon Washington
      Braking is a crucial driving task with a direct relationship with crash risk, as both excess and inadequate braking can lead to collisions. The objective of this study was to compare the braking profile of young drivers distracted by mobile phone conversations to non-distracted braking. In particular, the braking behaviour of drivers in response to a pedestrian entering a zebra crossing was examined using the CARRS-Q Advanced Driving Simulator. Thirty-two licensed drivers drove the simulator in three phone conditions: baseline (no phone conversation), hands-free, and handheld. In addition to driving the simulator, each participant completed questionnaires related to driver demographics, driving history, usage of mobile phones while driving, and general mobile phone usage history. The drivers were 18–26years old and split evenly by gender. A linear mixed model analysis of braking profiles along the roadway before the pedestrian crossing revealed comparatively increased decelerations among distracted drivers, particularly during the initial 20kph of deceleration. Drivers’ initial 20kph deceleration time was modelled using a parametric accelerated failure time (AFT) hazard-based duration model with a Weibull distribution with clustered heterogeneity to account for the repeated measures experiment design. Factors found to significantly influence the braking task included vehicle dynamics variables like initial speed and maximum deceleration, phone condition, and driver-specific variables such as licence type, crash involvement history, and self-reported experience of using a mobile phone whilst driving. Distracted drivers on average appear to reduce the speed of their vehicle faster and more abruptly than non-distracted drivers, exhibiting excess braking comparatively and revealing perhaps risk compensation. The braking appears to be more aggressive for distracted drivers with provisional licenses compared to drivers with open licenses. Abrupt or excessive braking by distracted drivers might pose significant safety concerns to following vehicles in a traffic stream.


      PubDate: 2014-09-02T22:23:01Z
       
  • Inter-national benchmarking of road safety: State of the art
    • Abstract: Publication date: Available online 26 August 2014
      Source:Transportation Research Part C: Emerging Technologies
      Author(s): Yongjun Shen , Elke Hermans , Qiong Bao , Tom Brijs , Geert Wets , Wuhong Wang
      Road traffic injuries and fatalities have nowadays been recognized as one of the most important public health issues that requires concerted efforts for effective and sustainable prevention. Given the fact that more and more countries are taking steps to improve their road safety situation, there is a growing need for these countries to work together more closely, because there are quite a number of common problems that can be identified in close cooperation, and improvement can be expected by learning lessons from existing best practices in other countries. As a consequence, comparison between a range of countries in terms of their road safety performance and development or – using state-of-the-art terminology – inter-national benchmarking of road safety, is currently widely advocated by most countries and international bodies as an emerging methodology for road safety improvement. However, performing a successful road safety benchmarking practice is by no means easy. Challenges exist from the definition of benchmarking framework at the very beginning to the final decisions in terms of identification of best practices and establishment of a continuous process of mutual learning. In this paper, the theoretical background of the benchmarking approach is introduced, and a specific benchmarking cycle for road safety is established which consists of five core activities. Moreover, as a valuable benchmarking tool, the development of a road safety index is highlighted, and some theoretical and practical issues on this subject are discussed.
      Graphical abstract image Highlights

      PubDate: 2014-09-02T22:23:01Z
       
  • Simulating vehicle dynamics on both design plans and laser-scanned road
           geometry to guide highway design policy
    • Abstract: Publication date: Available online 27 August 2014
      Source:Transportation Research Part C: Emerging Technologies
      Author(s): Alexander Brown , Sean Brennan
      Increasingly, roadway designers use simulations to analyze how roadway design choices affect vehicle dynamics and ultimately safety. When using commercial multi-body simulations for analysis of vehicle dynamics, engineers are usually able to trust that the vehicle states predicted by simulations are reasonably accurate. This is because simulation software companies spend significant research and development dollars making sure that vehicle models and numerical solvers give realistic results. However, when using vehicle dynamic simulations for the analysis of roadway designs, the road environment must be defined by the user. Researchers are often left to wonder whether the roads they simulate in software are representative of what construction crews actually built in the field. This paper compares the results of simulations using both a road’s design geometry, i.e., the CAD plans, versus a three-dimensional point-cloud scan of its actual geometry. For this comparison, high-fidelity commercial vehicle simulation software (CarSim and TruckSim) was used. Research-grade sensing equipment allowed for the digitization of road geometries during highway traversals in the field to create a simulated mesh of the real highway geometry. After comparing simulation results for traversals of design geometry and measured road geometry with collected vehicle data, the road safety implications of discrepancies seen between the predicted and measured vehicle states are also discussed.


      PubDate: 2014-09-02T22:23:01Z
       
  • Real time traffic flow outlier detection using short-term traffic
           conditional variance prediction
    • Abstract: Publication date: Available online 27 August 2014
      Source:Transportation Research Part C: Emerging Technologies
      Author(s): Jianhua Guo , Wei Huang , Billy M. Williams
      Outliers in traffic flow series represent uncommon events occurring in the roadway systems and outlier detection and investigation will help to unravel the mechanism of such events. However, studies on outlier detection and investigations are fairly limited in transportation field where a vast volume of traffic condition data has been collected from traffic monitoring devices installed in many roadway systems. Based on an online algorithm that has the ability of jointly predict the level and the conditional variance of the traffic flow series, a real time outlier detection method is proposed and implemented. Using real world data collected from four regions in both the United States and the United Kingdom, it was found that outliers can be detected using the proposed detection strategy. In addition, through a comparative experimental study, it was shown that the information contained in the outliers should be assimilated into the forecasting system to enhance its ability of adapting to the changing patterns of the traffic flow series. Moreover, the investigation into the effects of outliers on the forecasting system structure showed a significant connection between the outliers and the forecasting system parameters changes. General conclusions are provided concerning the analyses with future work recommended to investigate the underlying outlier generating mechanism and outlier treatment strategy in transportation applications.


      PubDate: 2014-09-02T22:23:01Z
       
  • A traffic congestion detection and information dissemination scheme for
           urban expressways using vehicular networks
    • Abstract: Publication date: Available online 27 August 2014
      Source:Transportation Research Part C: Emerging Technologies
      Author(s): Quan Yuan , Zhihan Liu , Jinglin Li , Junming Zhang , Fangchun Yang
      The cooperative vehicle-infrastructure technologies have enabled vehicles to collect and exchange traffic information in real time. Therefore, it is possible to use Vehicular Ad-hoc NETworks (VANETs) for detecting traffic congestion on urban expressways. However, because of the special topology of urban expressways (consisting of both major and auxiliary roadways), the existing traffic congestion detection methods using VANETs do not work very well. In addition, the existing dissemination methods of congestion information lack the necessary control mechanism, so the information may be disseminated to irrelevant geographical areas. This paper proposes a congestion detection and notification scheme using VANETs for urban expressways. The scheme adopts a simplified Doppler frequency shift method to estimate and differentiate traffic conditions for major and auxiliary roadways. Vehicular cooperation and human cognition are introduced to improve the estimation accuracy and to describe the overall traffic conditions. Additionally, the scheme develops a spatial–temporal effectiveness model based on the potential energy theory to control the dissemination area and survival time of the congestion information. Meanwhile, the proposed scheme uses several broadcast control mechanisms to alleviate vehicular network congestion. Simulations through TransModeler indicate that our scheme ensures the accuracy of the estimation of congestion degree. Consequently, the scheme can provide effective references for driving decision-making and path-planning.


      PubDate: 2014-09-02T22:23:01Z
       
  • Crash frequency analysis of left-side merging and diverging areas on urban
           freeway segments – A case study of I-75 through downtown Dayton,
           Ohio
    • Abstract: Publication date: Available online 1 September 2014
      Source:Transportation Research Part C: Emerging Technologies
      Author(s): Deogratias Eustace , Aline Aylo , Worku Y. Mergia
      This paper analyzes the effect of left- and right-side merging and diverging areas and other variables such as light condition, roadway pavement condition, drivers’ age and presence of construction work zones on the occurrence frequency of crashes. A 6.5-mile (10.5-km) section of I-75 that passes through downtown Dayton, Ohio was considered. The area of interest has a high traffic volume and consists of different geometric design challenges including closely spaced merging and diverging ramps. A four-year record of crash data (2005–2008) and a statistical modeling technique that assumes a negative binomial distribution on generalized linear models (GLMs) were used to develop separate models for merging and diverging areas. The model results show that left-side merging and diverging areas are critical elements in crash frequency in the vicinity of ramps on freeways. In addition, pavement condition, light condition, and work zones were found to be significant predictors of crash frequency. Specifically, the results indicate that crashes are about 7.88 times more likely to occur on merging areas located on the left side of the freeway lanes compared to those on the right. For diverging areas, about 2.26 times more crashes are likely to occur near diverging areas on the left compared to those diverging on the right side of the freeway. In addition, adverse pavement conditions (such as wet pavement, snow, and ice), adverse light conditions (such as darkness and glare), and presence of work zone were found to be significant variables in the occurrence of crashes.


      PubDate: 2014-09-02T22:23:01Z
       
  • A method of vehicle motion prediction and collision risk assessment with a
           simulated vehicular cyber physical system
    • Abstract: Publication date: Available online 2 September 2014
      Source:Transportation Research Part C: Emerging Technologies
      Author(s): Chaozhong Wu , Liqun Peng , Zhen Huang , Ming Zhong , Duanfeng Chu
      Vehicular cyber physical system (VCPS) can comprehensively acquire road traffic safety related information, and provide drivers with early warning or driving assistance in emergency, in order to assist them avoid vehicle crash in the driving process. Literature review shows that previous studies mainly rely on observed vehicle motion/location data for assessing vehicle collision risk, where predicted vehicle motion/location, driver behavior and road geometry (e.g., curvature) are rarely considered. In this study, based on the simulated VCPS, a collision avoidance system that can explicitly consider the above issues is designed and presented in detail. Within the proposed collision avoidance system, an assessment method, which can predict collision risk by comprehensively considering vehicles motion/location, driver behavior and road geometry information from the VCPS, is developed. Firstly, the short-term motion of the objective vehicle and surrounding vehicles are predicted based on the Kalman Filter (KF) algorithm and the vehicle motion model. Furthermore, the proposed method that can explicitly take driver behavior and road curvature into account is used to predict vehicle location and calculate the traveled distance among vehicles in real-time. Then, the predicted vehicle gaps are compared with a safe distance threshold and the vehicle collision risk is predicted. Finally, the accuracy of the proposed collision risk assessment method is examined with a receiver operating characteristic (ROC) curve analysis over a section of curved road. Simulation results show that the proposed method is effective for detecting collision risk and providing accurate warnings in a timely fashion.


      PubDate: 2014-09-02T22:23:01Z
       
  • Integrity of estimates of the two-fluid model and gender impacts
    • Abstract: Publication date: Available online 2 September 2014
      Source:Transportation Research Part C: Emerging Technologies
      Author(s): Anurag Pande , James Loy , Vinayak V. Dixit , Katherine Spansel , Brian Wolshon
      This paper summarizes a research study to develop a methodology for utilizing naturalistic Global Positioning System (GPS) driving data for two-fluid model estimation. The two-fluid vehicular traffic flow model describes traffic flow on a street network as a mix of stopped and running vehicles. The parameters of the model essentially represent ‘free flow’ travel time and the level of interaction among vehicles. These parameters have traditionally been used to evaluate roadway networks and corridors with partially limited access. However, the two-fluid model has been found to be a direct result of driver behavior, and can also be used to represent behavioral aspects of driver populations, e.g., aggressiveness, passiveness, etc. Through these behavioral aspects they can also be related to safety on roadways. Due to which the two-fluid model can be considered to be a safety footprint for a particular road or individual driver. Due to which it is critical to understand factors that influence the two-fluid model. In this study, two-fluid models were estimated using naturalistic driving data collected with GPS data loggers in San Luis Obispo (SLO), California. Linear referencing in ArcMap was used to link the GPS data with roadway characteristic data for each element of the roadway network. The linear referencing methodology is the key to relate the GPS driving data with the elements of roadway network. This study explores two fundamental questions: (1) how sensitive are the estimates of the two fluid parameters to various samples? This question is fundamentally important to help define the integrity of the two-fluid model for planning and operational purposes. To this end we use a random sampling approach to address this question. (2) Are there behavioral differences across gender? This provides important behavioral insights on driving behavior across gender. Significant differences were observed between male and female drivers, with female drivers being more aggressive.


      PubDate: 2014-09-02T22:23:01Z
       
  • Self-organizing traffic signals using secondary extension and dynamic
           coordination
    • Abstract: Publication date: November 2014
      Source:Transportation Research Part C: Emerging Technologies, Volume 48
      Author(s): Burak Cesme , Peter G. Furth
      Actuated traffic signal control logic has many advantages because of its responsiveness to traffic demands, short cycles, effective use of capacity leading to and recovering from oversaturation, and amenability to aggressive transit priority. Its main drawback has been its inability to provide good progression along arterials. However, the traditional way of providing progression along arterials, coordinated–actuated control with a common, fixed cycle length, has many drawbacks stemming from its long cycle lengths, inflexibility in recovering from priority interruptions, and ineffective use of capacity during periods of oversaturation. This research explores a new paradigm for traffic signal control, “self-organizing signals,” based on local actuated control but with some additional rules that create coordination mechanisms. The primary new rules proposed are for secondary extensions, in which the green may be held to serve an imminently arriving platoon, and dynamic coordination, in which small groups of closely spaced signals communicate with one another to cycle synchronously with the group’s critical intersection. Simulation tests in VISSIM performed on arterial corridors in Massachusetts and Arizona show overall delay reductions of up to 14% compared to an optimized coordinated–actuated scheme where there is no transit priority, and more than 30% in scenarios with temporary oversaturation. Tests also show that with self-organizing control, transit signal priority can be more effective than with coordinated–actuated control, reducing transit delay by about 60%, or 12 to 14s per intersection with little impact on traffic delay.


      PubDate: 2014-09-02T22:23:01Z
       
  • Emerging technologies special issue of ICTIS 2013
    • Abstract: Publication date: Available online 15 August 2014
      Source:Transportation Research Part C: Emerging Technologies
      Author(s): Liping Fu , Ming Zhong



      PubDate: 2014-08-16T20:48:09Z
       
  • Treating uncertainty in the estimation of speed from smartphone traffic
           probes
    • Abstract: Publication date: Available online 10 August 2014
      Source:Transportation Research Part C: Emerging Technologies
      Author(s): Giuseppe Guido , Vincenzo Gallelli , Frank Saccomanno , Alessandro Vitale , Daniele Rogano , Demetrio Festa
      Before smartphone probes can be used to obtain instantaneous vehicle speeds and other dynamic characteristics, the accuracy of these estimates needs to be established under varying degrees of satellite signal interruption commonly found with varying road and traffic conditions. This paper presents the results of several vehicle tracking tests comparing smartphone speeds to benchmark values obtained for three types of routes. Benchmark values were obtained using a high frequency calibrated V-Box mounted on the test vehicle with four Android OS smartphone units. A relationship is established linking error in smartphone instantaneous speeds to the corresponding signal Circular Error Probable (CEP) range for different road and traffic conditions. This relationship is used to provide speed adjustment factors for the smartphone probe estimates subject to varying satellite signal strength. The CEP test is a reported GPS unit indicator of precision based on a known ground control benchmark. Smartphone speeds (adjusted and unadjusted) are compared to aggregate speed profiles from a stationary radar detector placed at a given location along SS106 in southern Italy. The smartphone devices were found to replicate closely the observed speed profiles obtained from the fixed detector station. Simple t-tests suggest that the means of the smartphone speeds for the unadjusted case differed significantly from the means obtained from the radar detector, when the smartphone estimates were adjusted for uncertainty (CEP range related), however, the difference in mean speeds between the smartphone probes and the radar detector profile was not found to be statistically significant.


      PubDate: 2014-08-12T20:31:52Z
       
  • From traces to trajectories: How well can we guess activity locations from
           mobile phone traces?
    • Abstract: Publication date: September 2014
      Source:Transportation Research Part C: Emerging Technologies, Volume 46
      Author(s): Cynthia Chen , Ling Bian , Jingtao Ma
      Passively generated mobile phone dataset is emerging as a new data source for research in human mobility patterns. Information on individuals’ trajectories is not directly available from such data; they must be inferred. Many questions remain in terms how well we can capture human mobility patterns from these datasets. Only one study has compared the results from a mobile phone dataset to those from the National Household Travel Survey (NHTS), though the comparison is on two different populations and samples. This study is a very first attempt that develops a procedure to generate a simulated mobile phone dataset containing the ground truth information. This procedure can be used by other researchers and practitioners who are interested in using mobile phone data and want to formally evaluate the effectiveness of an algorithm. To identify activity locations from mobile phone traces, we develop an ensemble of methods: a model-based clustering method to identify clusters, a logistic regression model to distinguish between activity and travel clusters, and a set of behavior-based algorithms to detect types of locations visited. We show that the distribution of the activity locations identified from the simulated mobile phone dataset resembles the ground truth better than the existing studies. For home locations, 70% and 97% of identified homes are within 100 and 1000 m from the truth, respectively. For work places, 65% and 86% of the identified work places are within 100 and 1000 m from the true ones, respectively. These results point to the possibility of using these passively generated mobile phone datasets to supplement or even replace household travel surveys in transportation planning in the future.


      PubDate: 2014-08-06T20:04:45Z
       
  • Hybrid model predictive control for freeway traffic using discrete speed
           limit signals
    • Abstract: Publication date: September 2014
      Source:Transportation Research Part C: Emerging Technologies, Volume 46
      Author(s): José Ramón D. Frejo , Alfredo Núñez , Bart De Schutter , Eduardo F. Camacho
      In this paper, two hybrid Model Predictive Control (MPC) approaches for freeway traffic control are proposed considering variable speed limits (VSL) as discrete variables as in current real world implementations. These discrete characteristics of the speed limits values and some necessary constraints for the actual operation of VSL are usually underestimated in the literature, so we propose a way to include them using a macroscopic traffic model within an MPC framework. For obtaining discrete signals, the MPC controller has to solve a highly non-linear optimization problem, including mixed-integer variables. Since solving such a problem is complex and difficult to execute in real-time, we propose some methods to obtain reasonable control actions in a limited computation time. The first two methods ( θ -exhaustive and θ -genetic discretization) consist of first relaxing the discrete constraints for the VSL inputs; and then, based on this continuous solution and using a genetic or an exhaustive algorithm, to find discrete solutions within a distance θ of the continuous solution that provide a good performance. The second class of methods split the problem in a continuous optimization for the ramp metering signals and in a discrete optimization for speed limits. The speed limits optimization, which is much more time-consuming than the ramp metering one, is solved by a genetic or an exhaustive algorithm in communication with a non-linear solver for the ramp metering. The proposed methods are tested by simulation, showing not only a good performance, but also keeping the computation time reduced.


      PubDate: 2014-08-02T19:54:04Z
       
  • Improving the accessibility of urban transportation networks for people
           with disabilities
    • Abstract: Publication date: August 2014
      Source:Transportation Research Part C: Emerging Technologies, Volume 45
      Author(s): Laura Ferrari , Michele Berlingerio , Francesco Calabrese , Jon Reades
      What is the most effective way to enhance the accessibility of our oldest and largest public transportation systems for people with reduced mobility? The intersection of limits to government support with the growing mobility needs of the elderly and of people with disabilities calls for the development of tools that enable us to better prioritise investment in those areas that would deliver the greatest benefits to travellers. In principle and, to a lesser extent, in practice, many trains and buses are already accessible to nearly all users, leaving the stations and interchanges as the single largest and most expensive challenge facing operators trying to improve overall access to the network. Focussing on travel time and interchange differences, we present a method that uses network science and spatio-temporal analysis to rank stations in a way that minimises the divergence between accessible and non-accessible routes. Taking London as case study, we show that 50% of the most frequently followed journeys become 50% longer when wheelchair accessibility becomes a constraint. Prioritising accessibility upgrades using our network approach yields a total travel time that is more than 8 times better than a solution based on random choice, and 30% more effective than a solution that seeks solely to minimise the number of interchanges facing those with mobility constraints. These results highlight the potential for the analysis of ‘smart card’ data to enable network operators to obtain maximum value from their infrastructure investments in support of expanded access to all users.


      PubDate: 2014-07-28T19:34:45Z
       
  • An integrated traffic-driving simulation framework: Design,
           implementation, and validation
    • Abstract: Publication date: August 2014
      Source:Transportation Research Part C: Emerging Technologies, Volume 45
      Author(s): Yunfei Hou , Yunjie Zhao , Kevin F. Hulme , Shan Huang , Yaqin Yang , Adel W. Sadek , Chunming Qiao
      This paper first describes the process of integrating two distinct transportation simulation platforms, Traffic Simulation models and Driving Simulators, so as to broaden the range of applications for which either type of simulator is applicable. To integrate the two distinct simulation platforms, several technical challenges needed to be overcome including reconciling differences in update frequency, coordinate systems, and the fidelity levels of the vehicle dynamics models and graphical rendering requirements of the two simulators. Following the successful integration, the integrated simulator was validated by having several human subjects drive a 2.5mile long segment of a signalized arterial in both the virtual environment of the integrated simulator, and in the real-world during the evening “rush hour”. Several aspects of driving behavior were then compared between the human subjects’ driving in the “virtual” and the real world. The comparisons revealed generally similar behavior, in terms of average corridor-level travel time, deceleration/acceleration patterns, lane-changing behavior, as well as energy consumption and emissions production. The paper concludes by suggesting possible extensions of the developed prototype which the researchers are currently pursuing, including integration with a computer networking simulator, to facilitate Connected Vehicle (CV) and Vehicle Ad-hoc Network (VANET) related studies, and a multiple participant component that allows several human drivers to interact simultaneously within the integrated simulator.


      PubDate: 2014-07-28T19:34:45Z
       
  • Improving rail network velocity: A machine learning approach to predictive
           maintenance
    • Abstract: Publication date: August 2014
      Source:Transportation Research Part C: Emerging Technologies, Volume 45
      Author(s): Hongfei Li , Dhaivat Parikh , Qing He , Buyue Qian , Zhiguo Li , Dongping Fang , Arun Hampapur
      Rail network velocity is defined as system-wide average speed of line-haul movement between terminals. To accommodate increased service demand and load on rail networks, increase in network velocity, without compromising safety, is required. Among many determinants of overall network velocity, a key driver is service interruption, including lowered operating speed due to track/train condition and delays caused by derailments. Railroads have put significant infrastructure and inspection programs in place to avoid service interruptions. One of the key measures is an extensive network of wayside mechanical condition detectors (temperature, strain, vision, infrared, weight, impact, etc.) that monitor the rolling-stock as it passes by. The detectors are designed to alert for conditions that either violate regulations set by governmental rail safety agencies or deteriorating rolling-stock conditions as determined by the railroad. Using huge volumes of historical detector data, in combination with failure data, maintenance action data, inspection schedule data, train type data and weather data, we are exploring several analytical approaches including, correlation analysis, causal analysis, time series analysis and machine learning techniques to automatically learn rules and build failure prediction models. These models will be applied against both historical and real-time data to predict conditions leading to failure in the future, thus avoiding service interruptions and increasing network velocity. Additionally, the analytics and models can also be used for detecting root cause of several failure modes and wear rate of components, which, while do not directly address network velocity, can be proactively used by maintenance organizations to optimize trade-offs related to maintenance schedule, costs and shop capacity. As part of our effort, we explore several avenues to machine learning techniques including distributed learning and hierarchical analytical approaches.


      PubDate: 2014-07-28T19:34:45Z
       
  • Temporal and weather related variation patterns of urban travel time:
           Considerations and caveats for value of travel time, value of variability,
           and mode choice studies
    • Abstract: Publication date: August 2014
      Source:Transportation Research Part C: Emerging Technologies, Volume 45
      Author(s): Camille Kamga , M. Anıl Yazıcı
      By merging a large data set containing GPS records of taxi trips and historical weather records for New York City (NYC), the descriptive statistics of travel time (e.g. average travel time (ATT), standard deviation (SDTT), and coefficient of variation (CoV)) are calculated for each hourly period throughout the week and various weather conditions. Then, a Classification and Regression Trees methodology is used to determine the temporal patterns of ADTT, SDTT, and CoV, again for all time periods and weather conditions. Finally, the identified temporal patterns are discussed with respect to the findings and assumptions of value of time (VOT), value of reliability (VOR), and mode choice studies in the literature. The analysis shows that traditional peak hours are not necessarily the most congested periods and that the peak periods also exhibit inter-period heterogeneity in terms of ATT and SDTT. As opposed to ATT and SDTT, the coefficient of variation was shown to exhibit more consistent patterns among the days. In this respect, caution is advised for VOT–VOR studies regarding the temporal discrepancies in ATT and SDTT patterns; and CoV is suggested to be considered in VOT studies as a more robust measure. In terms of weather impacts, inclement weather is shown to have the potential to decrease SDTT and CoV at certain time periods, resulting in higher travel time reliability. This counter-intuitive finding is discussed with regards to traveler perceptions and possible implications on route and mode choice.


      PubDate: 2014-07-28T19:34:45Z
       
  • Editorial Board/Copyright Information
    • Abstract: Publication date: August 2014
      Source:Transportation Research Part C: Emerging Technologies, Volume 45




      PubDate: 2014-07-28T19:34:45Z
       
  • Advances in computing and communications technologies and their impact on
           transportation science and applications
    • Abstract: Publication date: August 2014
      Source:Transportation Research Part C: Emerging Technologies, Volume 45
      Author(s): Adel W. Sadek , Chunming Qiao



      PubDate: 2014-07-28T19:34:45Z
       
  • Estimating vehicle speed with embedded inertial sensors
    • Abstract: Publication date: September 2014
      Source:Transportation Research Part C: Emerging Technologies, Volume 46
      Author(s): Eyal Levenberg
      Pavements were instrumented with inertial sensors, and the possibility of estimating the speed of a passing vehicle was investigated numerically and experimentally from the measurements of two embedded accelerometers. The sensors were spaced apart in the travel direction, and subsequently the speed was directly related to the time delay between the received signals. No assumption was made regarding the vehicle and pavement properties. Model accelerations were presented, studied, and contrasted against field measurements; the latter were shown to be dominated by random vibration sources. Two calculation techniques were offered and applied to handle the noisy data. The first was based on time-centroids, and the second was based on cross-correlation with kernel presmoothing. The overall concept is deemed promising not only for inferring speeds but also for extracting additional traffic characteristics such as axle spacing and relative axle load distributions.


      PubDate: 2014-07-28T19:34:45Z
       
  • Demand-driven timetable design for metro services
    • Abstract: Publication date: September 2014
      Source:Transportation Research Part C: Emerging Technologies, Volume 46
      Author(s): Lijun Sun , Jian Gang Jin , Der-Horng Lee , Kay W. Axhausen , Alexander Erath
      Timetable design is crucial to the metro service reliability. A straightforward and commonly adopted strategy in daily operation is a peak/off-peak-based schedule. However, such a strategy may fail to meet dynamic temporal passenger demand, resulting in long passenger waiting time at platforms and over-crowding in trains. Thanks to the emergence of smart card-based automated fare collection systems, we can now better quantify spatial–temporal demand on a microscopic level. In this paper, we formulate three optimization models to design demand-sensitive timetables by demonstrating train operation using equivalent time (interval). The first model aims at making the timetable more dynamic; the second model is an extension allowing for capacity constraints. The third model aims at designing a capacitated demand-sensitive peak/off-peak timetable. We assessed the performance of these three models and conducted sensitivity analyzes on different parameters on a metro line in Singapore, finding that dynamical timetable built with capacity constraints is most advantageous. Finally, we conclude our study and discuss the implications of the three models: the capacitated model provides a timetable which shows best performance under fixed capacity constraints, while the uncapacitated model may offer optimal temporal train configuration. Although we imposed capacity constraints when designing the optimal peak/off-peak timetable, its performance is not as good as models with dynamical headways. However, it shows advantages such as being easier to operate and more understandable to the passengers.


      PubDate: 2014-07-28T19:34:45Z
       
  • Scheduling of airport runway operations using stochastic branch and bound
           methods
    • Abstract: Publication date: August 2014
      Source:Transportation Research Part C: Emerging Technologies, Volume 45
      Author(s): Gustaf Sölveling , John-Paul Clarke
      In this paper we present a solution methodology based on the stochastic branch and bound algorithm to find optimal, or close to optimal, solutions to the stochastic airport runway scheduling problem. The objective of the scheduling problem is to find a sequence of aircraft operations on one or several runways that minimizes the total makespan, given uncertain aircraft availability at the runway. Enhancements to the general stochastic branch and bound algorithm are proposed and we give the specific details pertaining to runway scheduling. We show how the algorithm can be terminated early with solutions that are close to optimal, and investigate the impact of the uncertainty level. The computational experiment indicates that the sequences obtained using the stochastic branch and bound algorithm have, on average, 5–7% shorter makespans than sequences obtained using deterministic sequencing models. In addition, the proposed algorithm is able to solve instances with 14 aircraft using less than 1min of computation time.


      PubDate: 2014-07-28T19:34:45Z
       
  • Within day rescheduling microsimulation combined with macrosimulated
           traffic
    • Abstract: Publication date: August 2014
      Source:Transportation Research Part C: Emerging Technologies, Volume 45
      Author(s): Luk Knapen , Tom Bellemans , Muhammad Usman , Davy Janssens , Geert Wets
      The concept of rescheduling is essential to activity-based modeling in order to calculate effects of both unexpected incidents and adaptation of individuals to traffic demand management measures. When collaboration between individuals is involved or timetable based public transportation modes are chosen, rescheduling becomes complex. This paper describes a new framework to investigate algorithms for rescheduling at a large scale. The framework allows to explicitly model the information flow between traffic information services and travelers. It combines macroscopic traffic assignment with microscopic simulation of agents adapting their schedules. Perception filtering is introduced to allow for traveler specific interpretation of perceived macroscopic data and for information going unnoticed; perception filters feed person specific short term predictions about the environment required for schedule adaptation. Individuals are assumed to maximize schedule utility. Initial agendas are created by the FEATHERS activity-based schedule generator for mutually independent individuals using an undisturbed loaded transportation network. The new framework allows both actor behavior and external phenomena to influence the transportation network state; individuals interpret the state changes via perception filtering and start adapting their schedules, again affecting the network via updated traffic demand. The first rescheduling mechanism that has been investigated uses marginal utility that monotonically decreases with activity duration and a monotonically converging relaxation algorithm to efficiently determine the new activity timing. The current framework implementation is aimed to support re-timing, re-location and activity re-sequencing; re-routing at the level of the individual however, requires microscopic travel simulation.


      PubDate: 2014-07-28T19:34:45Z
       
  • Multi-agent simulation of individual mobility behavior in carpooling
    • Abstract: Publication date: August 2014
      Source:Transportation Research Part C: Emerging Technologies, Volume 45
      Author(s): Stéphane Galland , Luk Knapen , Ansar-Ul-Haque Yasar , Nicolas Gaud , Davy Janssens , Olivier Lamotte , Abderrafiaa Koukam , Geert Wets
      Carpooling is an emerging alternative transportation mode that is eco-friendly and sustainable as it enables commuters to save time, travel resource, reduce emission and traffic congestion. The procedure of carpooling consists of a number of steps namely; (i) create a motive to carpool, (ii) communicate this motive with other agents, (iii) negotiate a plan with the interested agents, (iv) execute the agreed plans, and (v) provide a feedback to all concerned agents. In this paper, we present a conceptual design of an agent-based model (ABM) for the carpooling a that serves as a proof of concept. Our model for the carpooling application is a computational model that is used for simulating the interactions of autonomous agents and to analyze the effects of change in factors related to the infrastructure, behavior and cost. In our carpooling application, we use agent profiles and social networks to initiate our agent communication model and then employ a route matching algorithm, and a utility function to trigger the negotiation process between agents. We developed a prototype of our agent-based carpooling application based on the work presented in this paper and carried out a validation study of our results with real data collected in Flanders, Belgium.


      PubDate: 2014-07-28T19:34:45Z
       
  • Robust sampled-data cruise control scheduling of high speed train
    • Abstract: Publication date: September 2014
      Source:Transportation Research Part C: Emerging Technologies, Volume 46
      Author(s): Shukai Li , Lixing Yang , Keping Li , Ziyou Gao
      This paper investigates the robust cruise control scheduling of high speed train based on sampled-data. The dynamics model of a high speed train is modeled by a cascade of cars which are connected by flexible couplers, and is subject to rolling mechanical resistance, aerodynamic drag and wind gust. The robust cruise controller is designed for high speed train based on sampled-data. By using the method of converting the sampling period into a bounded time-varying delay, the addressed problem is transformed to the problem of stability analysis of time-varying delays system. Based on Lyapunov stability theory, sufficient conditions for the existence of robust sampled-data cruise control scheduling are given in terms of linear matrix inequality (LMI), under which the high speed train can track the desired speed, the relative spring displacement between the two neighbouring cars is robustly stable at the equilibrium state, and a prescribed H ∞ disturbance attenuation level with respect to the wind gust is guaranteed, which ensures the safety and comfort of the operating of high speed train. Numerical examples are given to illustrate the effectiveness of the proposed methods.


      PubDate: 2014-07-28T19:34:45Z
       
  • Optimal placement of omnidirectional sensors in a transportation network
           for effective emergency response and crash characterization
    • Abstract: Publication date: August 2014
      Source:Transportation Research Part C: Emerging Technologies, Volume 45
      Author(s): Tejswaroop Geetla , Rajan Batta , Alan Blatt , Marie Flanigan , Kevin Majka
      Rapid motor vehicle crash detection and characterization is possible through the use of Intelligent Transportation Systems (ITS) and sensors are an integral part of any ITS system. The major focus of this paper is on developing optimal placement of accident detecting omnidirectional sensors to maximize incident detection capabilities and provide ample opportunities for data fusion and crash characterization. Both omnidirectional sensors (placed in suitable infrastructure locations) and mobile sensors are part of our analysis. The surrogates used are acoustic sensors (omnidirectional) and Advanced Automated Crash Notification (AACN) sensors (mobile). This data fusion rich placement is achieved through a hybrid optimization model comprising of an explicit–implicit coverage model followed by an evaluation and local search optimization using simulation. The compound explicit–implicit model delivers good initial solutions and improves the detection and data fusion capabilities compared to the explicit model alone. The results of the studies conducted quantify the use of a data fusion capable environment in crash detection scenarios, and the simulation tool developed helps a decision maker evaluate sensor placement strategy.


      PubDate: 2014-07-28T19:34:45Z
       
  • A Hybrid Queue-based Bayesian Network framework for passenger facilitation
           modelling
    • Abstract: Publication date: September 2014
      Source:Transportation Research Part C: Emerging Technologies, Volume 46
      Author(s): Paul Pao-Yen Wu , Jegar Pitchforth , Kerrie Mengersen
      This paper presents a novel framework for the modelling of passenger facilitation in a complex environment. The research is motivated by the challenges in the airport complex system, where there are multiple stakeholders, differing operational objectives and complex interactions and interdependencies between different parts of the airport system. Traditional methods for airport terminal modelling do not explicitly address the need for understanding causal relationships in a dynamic environment. Additionally, existing Bayesian Network (BN) models, which provide a means for capturing causal relationships, only present a static snapshot of a system. A method to integrate a BN complex systems model with stochastic queuing theory is developed based on the properties of the Poisson and exponential distributions. The resultant Hybrid Queue-based Bayesian Network (HQBN) framework enables the simulation of arbitrary factors, their relationships, and their effects on passenger flow and vice versa. A case study implementation of the framework is demonstrated on the inbound passenger facilitation process at Brisbane International Airport. The predicted outputs of the model, in terms of cumulative passenger flow at intermediary and end points in the inbound process, are found to have an R 2 goodness of fit of 0.9994 and 0.9982 respectively over a 10h test period. The utility of the framework is demonstrated on a number of usage scenarios including causal analysis and ‘what-if’ analysis. This framework provides the ability to analyse and simulate a dynamic complex system, and can be applied to other socio-technical systems such as hospitals.


      PubDate: 2014-07-28T19:34:45Z
       
  • Ensemble based traffic light control for city zones using a reduced number
           of sensors
    • Abstract: Publication date: September 2014
      Source:Transportation Research Part C: Emerging Technologies, Volume 46
      Author(s): Dan Pescaru , Daniel-Ioan Curiac
      Rapid advances in computing, sensing and telecommunication technology offer unprecedented opportunities for artificial intelligence concepts to expand their applications in the field of traffic management and control. Our methodology gravitates around a powerful decision-making method: ensemble-based systems. This technique is used to accurately classify the near future traffic conditions and to make efficient decisions for adapting the traffic lights sequences within an urban area to optimize the traffic flows. The proposed approach requires only measurements provided by traffic sensors located along the principal roads entering the zone. This reduced number of sensors are considered to be enough relevant for classifying the near future state of the traffic and moreover, their measurements can be validated through analytical/hardware redundancy. Our methodology is meant to be implemented within the framework of a wireless sensor and actuator network and is confirmed by computer simulation, including normal or abnormal traffic conditions, for the central part of the city of Timisoara-Romania.


      PubDate: 2014-07-28T19:34:45Z
       
  • Hybrid powertrain optimization with trajectory prediction based on
           inter-vehicle-communication and vehicle-infrastructure-integration
    • Abstract: Publication date: August 2014
      Source:Transportation Research Part C: Emerging Technologies, Volume 45
      Author(s): Mohd Azrin Mohd Zulkefli , Jianfeng Zheng , Zongxuan Sun , Henry X. Liu
      Recent advances in Inter-Vehicle Communications (IVC) and Vehicle-Infrastructure Integration (VII) paved ways to real-time information sharing among vehicles, which are beneficial for vehicle energy management strategies (EMS). This is especially valuable for power-split hybrid electrical vehicles (HEV) in order to determine the optimal power-split between two different power sources at any particular time. Certainly, researches in this area have been done, but tradeoffs between optimality, driving-cycle sensitivity, speed of calculation and charge-sustaining (CS) conditions have not been cohesively addressed before. In light of this, a combined approach of a time-efficient powertrain optimization strategy, utilizing trajectory prediction based on IVC and VII is proposed. First, Gipps’ car following model for traffic prediction is used to predict the interactions between vehicles, combined with the cell-transmission-model (CTM) for the leading vehicle trajectory prediction. Secondly, a computationally efficient charge-sustaining (CS) HEV powertrain optimization strategy is analytically derived and simulated, based on the Pontryagin’s Minimum Principle and a CS-condition constraint. A 3D lookup-map, generated offline to interpolate the optimizing parameters based on the predicted speed, is also utilized to speed up the calculations. Simulations are conducted for 6-mile and 15-mile cases with different prediction update timings to test the performance of the proposed strategy against a Rule-Based (RB) control strategy. Results for accurate-prediction cases show 9.6% average fuel economy improvements in miles-per-gallon (MPG) over RB for the 6-mile case and 7% improvements for the 15-mile case. Prediction-with-error cases show smaller average MPG’s improvements, with 1.6% to 4.3% improvements for the 6-mile case and 2.6% to 3.4% improvements for the 15-mile case.


      PubDate: 2014-07-28T19:34:45Z
       
  • An optimal variable speed limits system to ameliorate traffic safety risk
    • Abstract: Publication date: September 2014
      Source:Transportation Research Part C: Emerging Technologies, Volume 46
      Author(s): Rongjie Yu , Mohamed Abdel-Aty
      Active Traffic Management (ATM) systems have been emerging in recent years in the US and Europe. They provide control strategies to improve traffic flow and reduce congestion on freeways. This study investigates the feasibility of utilizing a Variable Speed Limits (VSL) system, one key part of ATM, to improve traffic safety on freeways. A proactive traffic safety improvement VSL control algorithm is proposed. First, an extension of the METANET (METANET: A macroscopic simulation program for motorway networks) traffic flow model is employed to analyze VSL’s impact on traffic flow. Then, a real-time crash risk evaluation model is estimated for the purpose of quantifying crash risk. Finally, optimal VSL control strategies are achieved by employing an optimization technique to minimize the total crash risk along the VSL implementation corridor. Constraints are setup to limit the increase of average travel time and the differences of the posted speed limits temporarily and spatially. This novel VSL control algorithm can proactively reduce crash risk and therefore improve traffic safety. The proposed VSL control algorithm is implemented and tested for a mountainous freeway bottleneck area through the micro-simulation software VISSIM. Safety impacts of the VSL system are quantified as crash risk improvements and speed homogeneity improvements. Moreover, three different driver compliance levels are modeled in VISSIM to monitor the sensitivity of VSL effects on driver compliance. Conclusions demonstrated that the proposed VSL system could improve traffic safety by decreasing crash risk and enhancing speed homogeneity under both the high and moderate compliance levels; while the VSL system fails to significantly enhance traffic safety under the low compliance scenario. Finally, future implementation suggestions of the VSL control strategies and related research topics are also discussed.


      PubDate: 2014-07-28T19:34:45Z
       
  • Behavioural data mining of transit smart card data: A data fusion approach
    • Abstract: Publication date: September 2014
      Source:Transportation Research Part C: Emerging Technologies, Volume 46
      Author(s): Takahiko Kusakabe , Yasuo Asakura
      The aim of this study is to develop a data fusion methodology for estimating behavioural attributes of trips using smart card data to observe continuous long-term changes in the attributes of trips. The method is intended to enhance understanding of travellers’ behaviour during monitoring the smart card data. In order to supplement absent behavioural attributes in the smart card data, this study developed a data fusion methodology of smart card data with the person trip survey data with the naïve Bayes probabilistic model. A model for estimating the trip purpose is derived from the person trip survey data. By using the model, trip purposes are estimated as supplementary behavioural attributes of the trips observed in the smart card data. The validation analysis showed that the proposed method successfully estimated the trip purposes in 86.2% of the validation data. The empirical data mining analysis showed that the proposed methodology can be applied to find and interpret the behavioural features observed in the smart card data which had been difficult to obtain from each independent dataset.


      PubDate: 2014-07-28T19:34:45Z
       
  • Improved vehicle classification from dual-loop detectors in congested
           traffic
    • Abstract: Publication date: September 2014
      Source:Transportation Research Part C: Emerging Technologies, Volume 46
      Author(s): Lan Wu , Benjamin Coifman
      Vehicle classification is an important traffic parameter for transportation planning and infrastructure management. Length-based vehicle classification from dual loop detectors is among the lowest cost technologies commonly used for collecting these data. Like many vehicle classification technologies, the dual loop approach works well in free flow traffic. Effective vehicle lengths are measured from the quotient of the detector dwell time and vehicle traversal time between the paired loops. This approach implicitly assumes that vehicle acceleration is negligible, but unfortunately at low speeds this assumption is invalid and length-based classification performance degrades in congestion. To addresses this problem, we seek a solution that relies strictly on the measured effective vehicle length and measured speed. We analytically evaluate the feasible range of true effective vehicle lengths that could underlie a given combination of measured effective vehicle length, measured speed, and unobserved acceleration at a dual loop detector. From this analysis we find that there are small uncertainty zones where the measured length class can differ from the true length class, depending on the unobserved acceleration. In other words, a given combination of measured speed and measured effective vehicle length falling in the uncertainty zones could arise from vehicles with different true length classes. Outside of the uncertainty zones, any error in the measured effective vehicle length due to acceleration will not lead to an error in the measured length class. Thus, by mapping these uncertainty zones, most vehicles can be accurately sorted to a single length class, while the few vehicles that fall within the uncertainty zones are assigned to two or more classes. We find that these uncertainty zones remain small down to about 10mph and then grow exponentially as speeds drop further. Using empirical data from stop-and-go traffic at a well-tuned loop detector station the best conventional approach does surprisingly well; however, our new approach does even better, reducing the classification error rate due to acceleration by at least a factor of four relative to the best conventional method. Meanwhile, our approach still assigns over 98% of the vehicles to a single class.


      PubDate: 2014-07-28T19:34:45Z
       
  • Use of infrared thermography for assessing HMA paving and compaction
    • Abstract: Publication date: September 2014
      Source:Transportation Research Part C: Emerging Technologies, Volume 46
      Author(s): Christina Plati , Panos Georgiou , Andreas Loizos
      The assessment of paving and compaction temperatures effect on Hot Mix Asphalt (HMA) properties has been the subject of various researches. The present study aims to build upon these researches, by investigating the effectiveness and practicality of infrared thermography (IRT) as an emerging technology to assess HMA paving and compaction. For this purpose a field experiment was performed using a thermographic system to investigate the impact of the temperature in a paving project where two different types of HMA were used. The recorded mat surface temperatures are used effectively for the identification of temperature differentials, as well the detection of pavement defects. In addition, density-growth curves are developed for the specific mixtures and compaction pattern being used. IRT data is further analyzed for the development of simple HMA cooling models, providing a quick and efficient means to estimate the compaction time. More details and discussion are outlined in the paper.


      PubDate: 2014-07-28T19:34:45Z
       
  • Integrated feedback ramp metering and mainstream traffic flow control on
           motorways using variable speed limits
    • Abstract: Publication date: September 2014
      Source:Transportation Research Part C: Emerging Technologies, Volume 46
      Author(s): Rodrigo Castelan Carlson , Ioannis Papamichail , Markos Papageorgiou
      Ramp metering (RM) is the most direct and efficient tool for the motorway traffic flow management. However, because of the usually short length of the on-ramps, RM is typically deactivated to avoid interference of the created ramp queue with adjacent street traffic. By the integration of local RM with mainstream traffic flow control (MTFC) enabled via variable speed limits (VSL), control operation upstream of active bottlenecks could be continued even if the on-ramp is full or if the RM lower bound has been reached. Such integration is proposed via the extension of an existing local cascade feedback controller for MTFC-VSL by use of a split-range-like scheme that allows different control periods for RM and MTFC-VSL. The new integrated controller remains simple yet efficient and suitable for field implementation. The controller is evaluated in simulation for a real motorway infrastructure (a ring-road) fed with real (measured) demands and compared to stand-alone RM or MTFC-VSL, both with feedback and optimal control results. The controller’s performance is shown to meet the specifications and to approach the optimal control results for the investigated scenario.


      PubDate: 2014-07-28T19:34:45Z
       
  • Local online kernel ridge regression for forecasting of urban travel times
    • Abstract: Publication date: September 2014
      Source:Transportation Research Part C: Emerging Technologies, Volume 46
      Author(s): James Haworth , John Shawe-Taylor , Tao Cheng , Jiaqiu Wang
      Accurate and reliable forecasting of traffic variables is one of the primary functions of Intelligent Transportation Systems. Reliable systems that are able to forecast traffic conditions accurately, multiple time steps into the future, are required for advanced traveller information systems. However, traffic forecasting is a difficult task because of the nonlinear and nonstationary properties of traffic series. Traditional linear models are incapable of modelling such properties, and typically perform poorly, particularly when conditions differ from the norm. Machine learning approaches such as artificial neural networks, nonparametric regression and kernel methods (KMs) have often been shown to outperform linear models in the literature. A bottleneck of the latter approach is that the information pertaining to all previous traffic states must be contained within the kernel, but the computational complexity of KMs usually scales cubically with the number of data points in the kernel. In this paper, a novel kernel-based machine learning (ML) algorithm is developed, namely the local online kernel ridge regression (LOKRR) model. Exploiting the observation that traffic data exhibits strong cyclic patterns characterised by rush hour traffic, LOKRR makes use of local kernels with varying parameters that are defined around each time point. This approach has 3 advantages over the standard single kernel approach: (1) It allows parameters to vary by time of day, capturing the time varying distribution of traffic data; (2) It allows smaller kernels to be defined that contain only the relevant traffic patterns, and; (3) It is online, allowing new traffic data to be incorporated as it arrives. The model is applied to the forecasting of travel times on London’s road network, and is found to outperform three benchmark models in forecasting up to 1h ahead.


      PubDate: 2014-06-18T16:10:35Z
       
  • A trade-off analysis between penetration rate and sampling frequency of
           mobile sensors in traffic state estimation
    • Abstract: Publication date: September 2014
      Source:Transportation Research Part C: Emerging Technologies, Volume 46
      Author(s): Christopher Bucknell , Juan C. Herrera
      The rapid-growth of smartphones with embedded navigation systems such as GPS modules provides new ways of monitoring traffic. These devices can register and send a great amount of traffic related data, which can be used for traffic state estimation. In such a case, the amount of data collected depends on two variables: the penetration rate of devices in traffic flow (P) and their data sampling frequency (z). Referring to data composition as the way certain number of observations is collected, in terms of P and z, we need to understand the relation between the amount and composition of data collected, and the accuracy achieved in traffic state estimation. This was accomplished through an in-depth analysis of two datasets of vehicle trajectories on freeways. The first dataset consists of trajectories over a real freeway, while the second dataset is obtained through microsimulation. Hypothetical scenarios of data sent by equipped vehicles were created, based on the composition of data collected. Different values of P and z were used, and each unique combination defined a specific scenario. Traffic states were estimated through two simple methods, and a more advanced one that incorporates traffic flow theory. A measure to quantify data to be collected was proposed, based on travel time, number of vehicles, penetration rate and sampling frequency. The error was below 6% for every scenario in each dataset. Also, increasing data reduced variability in data count estimation. The performance of the different estimation methods varied through each dataset and scenario. Since the same number of observations can be gathered with different combinations of P and z, the effect of data composition was analyzed (a trade-off between penetration rate and sampling frequency). Different situations were found. In some, an increase in penetration rate is more effective to reduce estimation error than an increase in sampling frequency, considering an equal increase in observations. In other areas, the opposite relationship was found. Between these areas, an indifference curve was found. In fact, this curve is the solution to the optimization problem of minimizing the error given any fixed number of observations. As a general result, increasing sampling frequency (penetration rate) is more beneficial when the current sampling frequency (penetration rate) is low, independent of the penetration rate (sampling frequency).


      PubDate: 2014-06-18T16:10:35Z
       
  • Using connected vehicle technology to improve the efficiency of
           intersections
    • Abstract: Publication date: September 2014
      Source:Transportation Research Part C: Emerging Technologies, Volume 46
      Author(s): S. Ilgin Guler , Monica Menendez , Linus Meier
      Information from connected vehicles, such as the position and speed of individual vehicles, can be used to optimize traffic operations at an intersection. This paper proposes such an algorithm for two one-way-streets assuming that only a certain percentage of cars are equipped with this technology. The algorithm enumerates different sequences of cars discharging from the intersection to minimize the objective function. Benefits of platooning (multiple cars consecutively discharging from a queue) and signal flexibility (adaptability to demand) are also considered. The goal is to gain insights about the value (in terms of delay savings) of using connected vehicle technology for intersection control. Simulations are conducted for different total demand values and demand ratios to understand the effects of changing the minimum green time at the signal and the penetration rate of connected cars. Using autonomous vehicle control systems, the signal could rapidly change the direction of priority without relying on the reaction of drivers. However, without this technology a minimum green time is necessary. The results of the simulations show that a minimum green time increases the delay only for the low and balanced demand scenarios. Therefore, the value of using cars with autonomous vehicle control can only be seen at intersections with this kind of demand patterns, and could result in up to 7% decrease in delay. On the other hand, using information from connected vehicles to better adapt the traffic signal has proven to be indeed very valuable. Increases in the penetration rate from 0% up to 60% can significantly reduce the average delay (in low demand scenarios a decrease in delay of up to 60% can be observed). That being said, after a penetration rate of 60%, while the delays continue to decrease, the rate of reduction decreases and the marginal value of information from communication technologies diminishes. Overall, it is observed that connected vehicle technology could significantly improve the operation of traffic at signalized intersections, at least under the proposed algorithm.


      PubDate: 2014-06-18T16:10:35Z
       
  • Experimental evaluation of CAM and DENM messaging services in vehicular
           communications
    • Abstract: Publication date: September 2014
      Source:Transportation Research Part C: Emerging Technologies, Volume 46
      Author(s): José Santa , Fernando Pereñíguez , Antonio Moragón , Antonio F. Skarmeta
      The Cooperative Awareness Basic Service and Decentralized Environmental Notification Basic Service have been standardized by the European Telecommunications Standards Institute (ETSI) to support vehicular safety and traffic efficiency applications needing continuous status information about surrounding vehicles and asynchronous notification of events, respectively. These standard specifications detail not only the packet formats for both the Cooperative Awareness Message (CAM) and Decentralized Environmental Notification Message (DENM), but also the general message dissemination rules. These basic services, also known as facilities, have been developed as part of a set of standards in which both ISO and ETSI describe the Reference Communication Architecture for future Intelligent Transportation Systems (ITS). By using a communications stack that instantiates this reference architecture, this paper puts in practice the usage of both facilities in a real vehicular scenario. This research work details implementation decisions and evaluates the performance of CAM and DENM facilities through a experimental testbed deployed in a semi-urban environment that uses IEEE 802.11p (ETSI G5-compliant), which is a WiFi-like communication technology conceived for vehicular communications. On the one hand, this validation considers the development of two ITS applications using CAM and DENM functionalities for tracking vehicles and disseminating traffic incidences. In this case, CAM and DENM have demonstrated to be able to offer all the necessary functionality for the study case. On the other hand, both facilities have been also validated in a extensive testing campaign in order to analyze the influence in CAM and DENM performance of aspects such as vehicle speed, signal quality or message dissemination rules. In these tests, the line of sight, equipment installation point and hardware capabilities, have been found as key variables in the network performance, while the vehicle speed has implied a slight impact.


      PubDate: 2014-06-18T16:10:35Z
       
  • Multi-modal traffic signal control with priority, signal actuation and
           coordination
    • Abstract: Publication date: September 2014
      Source:Transportation Research Part C: Emerging Technologies, Volume 46
      Author(s): Qing He , K. Larry Head , Jun Ding
      Both coordinated-actuated signal control systems and signal priority control systems have been widely deployed for the last few decades. However, these two control systems are often conflicting with each due to different control objectives. This paper aims to address the conflicting issues between actuated-coordination and multi-modal priority control. Enabled by vehicle-to-infrastructure (v2i) communication in Connected Vehicle Systems, priority eligible vehicles, such as emergency vehicles, transit buses, commercial trucks, and pedestrians are able to send request for priority messages to a traffic signal controller when approaching a signalized intersection. It is likely that multiple vehicles and pedestrians will send requests such that there may be multiple active requests at the same time. A request-based mixed-integer linear program (MILP) is formulated that explicitly accommodate multiple priority requests from different modes of vehicles and pedestrians while simultaneously considering coordination and vehicle actuation. Signal coordination is achieved by integrating virtual coordination requests for priority in the formulation. A penalty is added to the objective function when the signal coordination is not fulfilled. This “soft” signal coordination allows the signal plan to adjust itself to serve multiple priority requests that may be from different modes. The priority-optimal signal timing is responsive to real-time actuations of non-priority demand by allowing phases to extend and gap out using traditional vehicle actuation logic. The proposed control method is compared with state-of-practice transit signal priority (TSP) both under the optimized signal timing plans using microscopic traffic simulation. The simulation experiments show that the proposed control model is able to reduce average bus delay, average pedestrian delay, and average passenger car delay, especially for highly congested condition with a high frequency of transit vehicle priority requests.


      PubDate: 2014-06-18T16:10:35Z
       
  • A finite mixture model of vehicle-to-vehicle and day-to-day variability of
           traffic network travel times
    • Abstract: Publication date: September 2014
      Source:Transportation Research Part C: Emerging Technologies, Volume 46
      Author(s): Jiwon Kim , Hani S. Mahmassani
      This study proposes an approach to modeling the effects of daily roadway conditions on travel time variability using a finite mixture model based on the Gamma–Gamma (GG) distribution. The GG distribution is a compound distribution derived from the product of two Gamma random variates, which represent vehicle-to-vehicle and day-to-day variability, respectively. It provides a systematic way of investigating different variability dimensions reflected in travel time data. To identify the underlying distribution of each type of variability, this study first decomposes a mixture of Gamma–Gamma models into two separate Gamma mixture modeling problems and estimates the respective parameters using the Expectation–Maximization (EM) algorithm. The proposed methodology is demonstrated using simulated vehicle trajectories produced under daily scenarios constructed from historical weather and accident data. The parameter estimation results suggest that day-to-day variability exhibits clear heterogeneity under different weather conditions: clear versus rainy or snowy days, whereas the same weather conditions have little impact on vehicle-to-vehicle variability. Next, a two-component Gamma–Gamma mixture model is specified. The results of the distribution fitting show that the mixture model provides better fits to travel delay observations than the standard (one-component) Gamma–Gamma model. The proposed method, the application of the compound Gamma distribution combined with a mixture modeling approach, provides a powerful and flexible tool to capture not only different types of variability—vehicle-to-vehicle and day-to-day variability—but also the unobserved heterogeneity within these variability types, thereby allowing the modeling of the underlying distributions of individual travel delays across different days with varying roadway disruption levels in a more effective and systematic way.


      PubDate: 2014-06-18T16:10:35Z
       
  • Transit network design by genetic algorithm with elitism
    • Abstract: Publication date: September 2014
      Source:Transportation Research Part C: Emerging Technologies, Volume 46
      Author(s): Muhammad Ali Nayeem , Md. Khaledur Rahman , M. Sohel Rahman
      The transit network design problem is concerned with the finding of a set of routes with corresponding schedules for a public transport system. This problem belongs to the class of NP-Hard problem because of the vast search space and multiple constraints whose optimal solution is really difficult to find out. The paper develops a Population based model for the transit network design problem. While designing the transit network, we give preference to maximize the number of satisfied passengers, to minimize the total number of transfers, and to minimize the total travel time of all served passengers. Our approach to the transit network design problem is based on the Genetic Algorithm (GA) optimization. The Genetic Algorithm is similar to evolution strategy which iterates through fitness assessment, selection and breeding, and population reassembly. In this paper, we will show two different experimental results performed on known benchmark problems. We clearly show that results obtained by Genetic Algorithm with increasing population is better than so far best technique which is really difficult for future researchers to beat.


      PubDate: 2014-06-18T16:10:35Z
       
  • Dynamics of connected vehicle systems with delayed acceleration feedback
    • Abstract: Publication date: September 2014
      Source:Transportation Research Part C: Emerging Technologies, Volume 46
      Author(s): Jin I. Ge , Gábor Orosz
      In this paper, acceleration-based connected cruise control (CCC) is proposed to increase roadway traffic mobility. CCC is designed to be able to use acceleration signals received from multiple vehicles ahead through wireless vehicle-to-vehicle (V2V) communication. We consider various connectivity structures in heterogeneous platoons comprised of human-driven and CCC vehicles. We show that inserting a few CCC vehicles with appropriately designed gains and delays into the flow, one can stabilize otherwise string unstable vehicle platoons. Exploiting the flexibility of ad-hoc connectivity, CCC can be applied in a large variety of traffic scenarios. Moreover, using acceleration feedback in a selective manner, CCC provides robust performance and remains scalable for large systems of connected vehicles. Our conclusions are verified by simulations at the nonlinear level.
      Graphical abstract image

      PubDate: 2014-06-18T16:10:35Z
       
  • Optimization of nonlinear control strategy for anti-lock braking system
           with improvement of vehicle directional stability on split-μ roads
    • Abstract: Publication date: September 2014
      Source:Transportation Research Part C: Emerging Technologies, Volume 46
      Author(s): Hossein Mirzaeinejad , Mehdi Mirzaei
      In a hard braking on a split-μ road, the achievement of shorter stopping distance while maintaining the vehicle in the straight line are of great importance. In this paper, to achieve these conflicting aims, an optimal nonlinear algorithm based on the prediction of vehicle responses is presented to distribute the wheel braking forces properly. The base of this algorithm is reducing the maximum achievable braking forces of one side wheels, as low as possible, so that the minimum stabilizing yaw moment is produced. The optimal property of the proposed control method makes it possible to get a trade-off between the shorter stopping distance and the less deviation of the vehicle heading from the straight line. The special case of this algorithm leads to the conventional anti-lock braking system (ABS) which generates the maximum braking forces for all wheels to attain the minimum stopping distance. However, the ABS cannot control the vehicle directional stability directly. The simulation results carried out using a nonlinear 8-DOF vehicle model demonstrate that the designed control system has a suitable performance to attain the desired purposes compared with the convectional ABS.


      PubDate: 2014-06-18T16:10:35Z
       
  • The time slot allocation problem under uncertain capacity
    • Abstract: Publication date: September 2014
      Source:Transportation Research Part C: Emerging Technologies, Volume 46
      Author(s): Luca Corolli , Guglielmo Lulli , Lewis Ntaimo
      This paper presents two stochastic programming models for the allocation of time slots over a network of airports. The proposed models address three key issues. First, they provide an optimization tool to allocate time slots, which takes several operational aspects and airline preferences into account; second, they execute the process on a network of airports; and third they explicitly include uncertainty. To the best of our knowledge, these are the first models for time slot allocation to consider both the stochastic nature of capacity reductions and the problem’s network structure. From a practical viewpoint, the proposed models provide important insights for the allocation of time slots. Specifically, they highlight the tradeoff between the schedule/request discrepancies, i.e., the time difference between allocated time slots and airline requests, and operational delays. Increasing schedule/request discrepancies enables a reduction in operational delays. Moreover, the models are computationally viable. A set of realistic test instances that consider the scheduling of four calendar days on different European airport networks has been solved within reasonable – for the application’s context – computation times. In one of our test instances, we were able to reduce the sum of schedule/request discrepancies and operational delays by up to 58%. This work provides slot coordinators with a valuable decision making tool, and it indicates that the proposed approach is very promising and may lead to relevant monetary savings for airlines and aircraft operators.


      PubDate: 2014-06-18T16:10:35Z
       
 
 
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