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  Subjects -> TRANSPORTATION (Total: 134 journals)
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    - TRANSPORTATION (86 journals)

TRANSPORTATION (86 journals)

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Journal Cover Transportation Research Part C: Emerging Technologies
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   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]
  • A traffic assignment model for passenger transit on a capacitated network:
           Bi-layer framework, line sub-models and large-scale application
    • Abstract: Publication date: Available online 17 September 2014
      Source:Transportation Research Part C: Emerging Technologies
      Author(s): Fabien Leurent , Ektoras Chandakas , Alexis Poulhès
      In the urban setting, the roadway and railway modes of mass transit are basically purported to carry large flows of passengers. Thus the issue of flowing capacity is crucial in the design and planning of a transit network. As a transit system involves two types of traffic units, respectively passengers and vehicles, there is a broad range of capacity phenomena: (i) as a vehicle has given seat capacity, additional riders have to stand which is less comfortable and more exposed to in-vehicle crowding, (ii) the total capacity in a vehicle, including sitting and standing places, influences the wait time on platform if it is exceeded by the number of candidate riders, (iii) the exchange capacity at vehicle doors influences the vehicle dwell time at a station, (iv) from the station dwell times stems the run time of vehicles – hence of passengers – and in turn the service frequency, (v) vehicle traffic is constrained by dwell time and operating margins, which may reduce the frequency delivered, etc. The paper provides a static, macroscopic model of traffic assignment to a transit network, in which these capacity phenomena are captured. A key feature is the line sub-model that deals with a line of operations, comprised of one or several service routes, by using the topological order of stations. From a matrix of flows by pair of access-egress stations, the sub-model derives the matrix of average passenger costs by access-egress pair, as well as local passenger wait time and the apparent frequency of each leg. At the network level, passenger route choice is modeled by optimal hyperpaths that are route-based (as in De Cea and Fernandez, 1989). It is shown that there exists a state of traffic equilibrium. A Method of Successive Averages is put forward to compute equilibrium. A large scale application to the whole transit network of greater Paris is presented, with focus on capacity issues.


      PubDate: 2014-09-18T23:55:16Z
       
  • Safety-based path finding in urban areas for older drivers and bicyclists
    • Abstract: Publication date: November 2014
      Source:Transportation Research Part C: Emerging Technologies, Volume 48
      Author(s): Shailesh Chandra
      This paper presents a safety-based path finding methodology for older drivers and bicyclists in an urban area. The paths are estimated based on costs consisting of both safety and travel time. Safety is evaluated against potential risk of a crash involving an older driver (or a bicyclist) with other vehicles present on the road. To accomplish this, simple formulations are developed for safety indicators of streets and intersections, which are actually generic irrespective of the type of road user. Traffic attributes such as speed and density, driver attributes such as perception-reaction time and street attributes of length and tire-to-road friction coefficient are taken into account in building the safety indicators. Thus, the safety indicators do not necessarily require historical crash data which may or may not be available during path finding. Subsequently, a multi-objective shortest path algorithm is presented that identifies the best path (the non-inferior path) from amongst a set of selected safest paths with due considerations to travel time incurred on each. A simple application example of the proposed methodology is demonstrated on an existing street network system from the City of College Station, Texas. The contributions of this research are twofold – first, the safety indicators can be used by planners in determining high crash potential sites – streets and/or intersections – and second, the safety-based path finding methodology developed in this paper can be integrated with modern day route planning devices and tools in guiding older drivers and bicyclists within an Intelligent Transportation Systems framework.


      PubDate: 2014-09-18T23:55:16Z
       
  • Urban traffic state estimation: Fusing point and zone based data
    • Abstract: Publication date: November 2014
      Source:Transportation Research Part C: Emerging Technologies, Volume 48
      Author(s): Ashish Bhaskar , Takahiro Tsubota , Le Minh Kieu , Edward Chung
      Loop detectors are the oldest and widely used traffic data source. On urban arterials, they are mainly installed for signal control. Recently state-of-the art Bluetooth MAC Scanners (BMS) has significantly captured the interest of stakeholders for exploiting it for area-wide traffic monitoring. Loop detectors provide flow – a fundamental traffic parameter; whereas BMS provides individual vehicle travel time between BMS stations. Hence, these two data sources complement each other, and if integrated should increase the accuracy and reliability of the traffic state estimation. This paper proposed a model that integrates loops and BMS data for seamless travel time and density estimation for urban signalised network. The proposed model is validated using both real and simulated data and the results indicate that the accuracy of the proposed model is over 90%.


      PubDate: 2014-09-18T23:55:16Z
       
  • Using automated walking gait analysis for the identification of pedestrian
           attributes
    • Abstract: Publication date: November 2014
      Source:Transportation Research Part C: Emerging Technologies, Volume 48
      Author(s): Mohamed H. Zaki , Tarek Sayed
      Collecting microscopic pedestrian behavior and characteristics data is important for optimizing the design of pedestrian facilities for safety, efficiency, and comfortability. This paper provides a framework for the automated classification of pedestrian attributes such as age and gender based on information extracted from their walking gait behavior. The framework extends earlier work on the automated analysis of gait parameters to include analysis of the gait acceleration data which can enable the quantification of the variability, rhythmic pattern and stability of pedestrian’s gait. In this framework, computer vision techniques are used for the automatic detection and tracking of pedestrians in an open environment resulting in pedestrian trajectories and the speed and acceleration dynamic profiles. A collection of gait features are then derived from those dynamic profiles and used for the classification of pedestrian attributes. The gait features include conventional gait parameters such as gait length and frequency and dynamic parameters related to gait variations and stability measures. Two different techniques are used for the classification: a supervised k-Nearest Neighbors (k-NN) algorithm and a newly developed semi-supervised spectral clustering. The classification framework is demonstrated with two case studies from Vancouver, British Columbia and Oakland, California. The results show the superiority of features sets including gait variations and stability measures over features relying only on conventional gait parameters. For gender, correct classification rates (CCR) of 80% and 94% were achieved for the Vancouver and Oakland case studies, respectively. The classification accuracy for gender was higher in the Oakland case which only considered pedestrians walking alone. Pedestrian age classification resulted in a CCR of 90% for the Oakland case study.


      PubDate: 2014-09-18T23:55:16Z
       
  • Infrastructure based approach for roadway departure risk assessment
    • Abstract: Publication date: November 2014
      Source:Transportation Research Part C: Emerging Technologies, Volume 48
      Author(s): Guillaume Rey , David Clair , Michel Fogli , Frédéric Bernardin
      This paper presents a warning device to prevent the roadway departure of light vehicles while cornering. The proposed risk assessment methodology is based on recent works from the authors (Rey et al., 2011b,a; Rey, 2010). Given the random variability arising from the driver, the vehicle and the infrastructure at the entrance to the curve, a probabilistic strategy is adopted to assess the roadway departure risk. The infrastructure-based methodology enables the real curve characteristics to be considered and an alarm triggering decision to be made. Two safety criteria are tested and the potential safety benefits of the proposed warning device are evaluated. Contrary to existing roadway departure warning systems, the proposed approach does not require extra equipment for vehicles; it only requires that the measuring and warning devices be part of the road infrastructure, which is a great advantage in terms of economic cost.


      PubDate: 2014-09-18T23:55:16Z
       
  • Tracking daily travel; Assessing discrepancies between GPS-derived and
           self-reported travel patterns
    • Abstract: Publication date: November 2014
      Source:Transportation Research Part C: Emerging Technologies, Volume 48
      Author(s): Douglas Houston , Thuy T. Luong , Marlon G. Boarnet
      Global Positioning Systems (GPS) technologies have been used in conjunction with traditional one- or two-day travel diaries to audit respondent reporting patterns, but we used GPS-based monitoring to conduct the first assessment to our knowledge of travel reporting patterns using a seven-day travel log instrument, which could reduce response burden and provide multiple-day, policy-relevant information for evaluation studies. We found substantial agreement between participant-reported daily travel patterns and GPS-derived patterns among 116 adult residents of a largely low-income and non-white transportation corridor in urbanized Los Angeles in 2011–2013. For all modes, the average difference between daily GPS- and log-derived trip counts was only about 0.39 trips and the average difference between daily GPS- and log-derived walking duration was about −11.8min. We found that the probability that a day would be associated with agreement or discrepancies between these measurement tools varied by travel mode and participant socio-demographic characteristics. Future research is needed to investigate the potential and limitations of this and other self-report instruments for a larger sample and a wider range of population groups and travel patterns.


      PubDate: 2014-09-18T23:55:16Z
       
  • A cell-based logit-opportunity taxi customer-search model
    • Abstract: Publication date: November 2014
      Source:Transportation Research Part C: Emerging Technologies, Volume 48
      Author(s): R.C.P. Wong , W.Y. Szeto , S.C. Wong
      This paper proposes a cell-based model to predict local customer-search movements of vacant taxi drivers, which incorporates the modeling principles of the logit-based search model and the intervening opportunity model. The local customer-search movements were extracted from the global positioning system data of 460 Hong Kong urban taxis and inputted into a cell-based taxi operating network to calibrate the model and validate the modeling concepts. The model results reveal that the taxi drivers’ local search decisions are significantly affected by the (cumulative) probability of successfully picking up a customer along the search route, and that the drivers do not search their customers under the random walk principle. The proposed model helps predict the effects of the implementation of the policies in adjusting the taxi fleet size and the changes in passenger demand on the customer-search distance and time of taxi drivers.


      PubDate: 2014-09-18T23:55:16Z
       
  • The time-dependent vehicle routing problem with soft time windows and
           stochastic travel times
    • Abstract: Publication date: November 2014
      Source:Transportation Research Part C: Emerging Technologies, Volume 48
      Author(s): Duygu Taş , Nico Dellaert , Tom van Woensel , Ton de Kok
      This paper studies a vehicle routing problem with time-dependent and stochastic travel times. In our problem setting, customers have soft time windows. A mathematical model is used in which both efficiency for service as well as reliability for customers are taken into account. Depending on whether service times are included or not, we consider two versions of this problem. Two metaheuristics are built: a Tabu Search and an Adaptive Large Neighborhood Search. We carry out our experiments for well-known problem instances and perform comprehensive analyses on the numerical results in terms of the computational time and the solution quality. Experiments confirm that the proposed procedure is effective to obtain very good solutions to be performed in real-life environment.


      PubDate: 2014-09-18T23:55:16Z
       
  • Spatio-temporal clustering for non-recurrent traffic congestion detection
           on urban road networks
    • Abstract: Publication date: November 2014
      Source:Transportation Research Part C: Emerging Technologies, Volume 48
      Author(s): Berk Anbaroglu , Benjamin Heydecker , Tao Cheng
      Non-Recurrent Congestion events (NRCs) frustrate commuters, companies and traffic operators because they cause unexpected delays. Most existing studies consider NRCs to be an outcome of incidents on motorways. The differences between motorways and urban road networks, and the fact that incidents are not the only cause of NRCs, limit the usefulness of existing automatic incident detection methods for identifying NRCs on urban road networks. In this paper we propose an NRC detection methodology to support the accurate detection of NRCs on large urban road networks. To achieve this, substantially high Link Journey Time estimates (LJTs) on adjacent links that occur at the same time are clustered. Substantially high LJTs are defined as those LJTs that are greater than a threshold. The threshold is calculated by multiplying the expected LJTs with a congestion factor. To evaluate the effectiveness of the proposed NRC detection method, we propose two novel criteria. The first criterion, high-confidence episodes, assesses to what extent substantially high LJTs that last for a minimum duration are detected. The second criterion, the Localisation Index, assesses to what extent detected NRCs could be associated with incidents. The proposed NRC detection methodology is tested for London’s urban road network. The optimum value of the congestion factor is determined by sensitivity analysis by using a Weighted Product Model (WPM). It is found out those LJTs that are at least 40% higher than their expected values should belong to an NRC; as such NRCs are found to maintain the best balance between the proposed evaluation criteria.


      PubDate: 2014-09-18T23:55:16Z
       
  • Analysis of hurricane evacuee mode choice behavior
    • Abstract: Publication date: November 2014
      Source:Transportation Research Part C: Emerging Technologies, Volume 48
      Author(s): Arif Mohaimin Sadri , Satish V. Ukkusuri , Pamela Murray-Tuite , Hugh Gladwin
      The purpose of this study is to explain the evacuee mode choice behavior of Miami Beach residents using survey data from a hypothetical category four hurricane to reveal different evacuees’ plans. Evacuation logistics should incorporate the needs of transit users and car-less populations with special attention and proper treatment. A nested logit model has been developed to explain the mode choice decisions for evacuees’ from Miami Beach who use non-household transportation modes, such as special evacuation bus, taxi, regular bus, riding with someone from another household and another type of mode denoted and aggregated as other. Specifically, the model explains that the mode choice decisions of evacuees’, who are likely to use different non-household transportation modes, are influenced by several determining factors related to evacuees’ socio-demographics, household characteristics, evacuation destination and previous experience. The findings of this study will help emergency planners and policy-makers to develop better evacuation plans and strategies for evacuees depending on others for their evacuation transportation.


      PubDate: 2014-09-18T23:55:16Z
       
  • 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
       
  • Editorial Board/Copyright Information
    • Abstract: Publication date: August 2014
      Source:Transportation Research Part C: Emerging Technologies, Volume 45




      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
       
  • 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
       
  • 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
       
  • 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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