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  Subjects -> TRANSPORTATION (Total: 161 journals)
    - AIR TRANSPORT (7 journals)
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    - ROADS AND TRAFFIC (4 journals)
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    - TRANSPORTATION (99 journals)

TRANSPORTATION (99 journals)

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Journal Cover   Transportation Research Part C: Emerging Technologies
  [SJR: 1.943]   [H-I: 55]   [18 followers]  Follow
    
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 0968-090X
   Published by Elsevier Homepage  [2807 journals]
  • Spatial and temporal characterization of travel patterns in a traffic
           network using vehicle trajectories
    • Abstract: Publication date: Available online 26 July 2015
      Source:Transportation Research Part C: Emerging Technologies
      Author(s): Jiwon Kim, Hani S. Mahmassani
      This paper presents a trajectory clustering method to discover spatial and temporal travel patterns in a traffic network. The study focuses on identifying spatially distinct traffic flow groups using trajectory clustering and investigating temporal traffic patterns of each spatial group. The main contribution of this paper is the development of a systematic framework for clustering and classifying vehicle trajectory data, which does not require a pre-processing step known as map-matching and directly applies to trajectory data without requiring the information on the underlying road network. The framework consists of four steps: similarity measurement, trajectory clustering, generation of cluster representative subsequences, and trajectory classification. First, we propose the use of the Longest Common Subsequence (LCS) between two vehicle trajectories as their similarity measure, assuming that the extent to which vehicles’ routes overlap indicates the level of closeness and relatedness as well as potential interactions between these vehicles. We then extend a density-based clustering algorithm, DBSCAN, to incorporate the LCS-based distance in our trajectory clustering problem. The output of the proposed clustering approach is a few spatially distinct traffic stream clusters, which together provide an informative and succinct representation of major network traffic streams. Next, we introduce the notion of Cluster Representative Subsequence (CRS), which reflects dense road segments shared by trajectories belonging to a given traffic stream cluster, and present the procedure of generating a set of CRSs by merging the pairwise LCSs via hierarchical agglomerative clustering. The CRSs are then used in the trajectory classification step to measure the similarity between a new trajectory and a cluster. The proposed framework is demonstrated using actual vehicle trajectory data collected from New York City, USA. A simple experiment was performed to illustrate the use of the proposed spatial traffic stream clustering in application areas such as network-level traffic flow pattern analysis and travel time reliability analysis.


      PubDate: 2015-07-29T20:53:46Z
       
  • A real-time Active Routing approach via a database for airport surface
           movement
    • Abstract: Publication date: September 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 58, Part A
      Author(s): Michal Weiszer, Jun Chen, Paul Stewart
      Airports face challenges due to the increasing volume of air traffic and tighter environmental restrictions which result in a need to actively integrate speed profiles into conventional routing and scheduling procedure. However, only until very recently, the research on airport ground movement has started to take into account such a speed profile optimisation problem actively so that not only time efficiency but also fuel saving and decrease in airport emissions can be achieved at the same time. It is envisioned that the realism of planning could also be improved through speed profiles. However, due to the multi-objective nature of the problem and complexity of the investigated models (objective functions), the existing speed profile optimisation approach features high computational demand and is not suitable for an on-line application. In order to make this approach more competitive for real-world application and to meet limits imposed by International Civil Aviation Organization for on-line decision time, this paper introduces a pre-computed database acting as a middleware to effectively separate the planning (routing and scheduling) module and the speed profile generation module. Employing a database not only circumvents duplicative optimisation for the same taxiway segments, but also completely avoids the computation of speed profiles during the on-line decision support owing a great deal to newly proposed database initialization procedures. Moreover, the added layer of database facilitates, in the future, more complex and realistic models to be considered in the speed profile generation module, without sacrificing on-line decision time. The experimental results carried out using data from a major European hub show that the proposed approach is promising in speeding up the search process.


      PubDate: 2015-07-29T20:53:46Z
       
  • Vehicle path reconstruction using automatic vehicle identification data:
           An integrated particle filter and path flow estimator
    • Abstract: Publication date: September 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 58, Part A
      Author(s): Jianhao Yang, Jian Sun
      Automatic vehicle identification (AVI) can provide partial vehicle path data by matching the vehicle license plate on the detected links. However, the matched samples will rapidly degenerate with an increase in network size and a decrease in coverage rate and identification precision. In this paper, we propose an integrated macro–micro framework to reconstruct the complete vehicle path of realistic networks. The proposed framework integrates the individual path choice using particle filter (PF) at the microscopic level and the stochastic user equilibrium (SUE) principle with a path flow estimator (PFE) at the macroscopic level. The PF reconstructs the vehicle path by updating the state-space probability curve based on four observation models (i.e., path consistency model, AVI measurability criterion model, travel time consistency model and path attraction model) and incorporates a path flow constraint into the PFE model. The PFE minimizes the SUE objective while reproducing traffic counts on detected links and updates two of the four observation models (i.e., travel time consistency model and path attraction model) of the PF. The proposed method is tested on a realistic network for different AVI coverage rates ranged from 30% to 80%. The proposed method achieves approximately 55% improvement in link flow estimation and 67% improvement in path flow estimation compared with the original PFE without the microscopic level consideration. The accuracy of the vehicle path reconstruction exceeds 80% even when the AVI coverage is only 40% with an AVI detection error of 6%.


      PubDate: 2015-07-29T20:53:46Z
       
  • The train marshalling by a single shunting engine problem
    • Abstract: Publication date: September 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 58, Part A
      Author(s): Jan-Alexander Adlbrecht, Benno Hüttler, Jan Zazgornik, Manfred Gronalt
      We consider the problem of marshalling a train from a number of rail cars that are distributed throughout the classification bowl of a shunting yard. In contrast to most other contributions we do not consider marshalling based on repeated roll-ins, but marshalling by shunting engine. This is also a common process alternative at shunting yards that has not yet received much attention from the scientific community. The goal is to find the optimal route for this shunting engine that respects all constraints applicable to movements in a shunting yard. We propose a Mixed Integer Programme (MIP) under consideration of single-block trains. A block refers to rail cars that share the same destination. Then we conduct a series of numerical experiments and show that the solutions of the MIP improve by 10% on average when compared to those produced by a Real-World-Heuristic that is designed to approximate the current marshalling practice. Finally, we statistically derive relationships between selected problem instance characteristics and the expected marshalling effort that can be useful for practitioners and operators of shunting yards.


      PubDate: 2015-07-25T21:47:15Z
       
  • Stochastic optimal path problem with relays
    • Abstract: Publication date: Available online 22 July 2015
      Source:Transportation Research Part C: Emerging Technologies
      Author(s): Peng (Will) Chen, Yu (Marco) Nie
      This paper studies the optimal path problem for travelers driving with vehicles of a limited range, such as most battery electric vehicles currently available in the market. The optimal path in this problem often consists of several relay points, where the vehicles can be refueled to extend its range. We propose a stochastic optimal path problem with relays (SOPPR), which aims at minimizing a general expected cost while maintaining a reasonable arrival probability. To account for uncertainty in the road network, the travel speed on a road segment is treated as a discrete random variable, which determines the total energy required to traverse the segment. SOPPR is formulated in two stages in this paper. In the first stage, an optimal routing problem is solved repeatedly to obtain the expected costs and arrival probabilities from any node to all refueling nodes and the destination. With this information, the second stage constructs an auxiliary network, on which the sequence of refueling decisions can be obtained by solving another optimal path problem. Label-correcting algorithms are developed to solve the routing problems in both stages. Numerical experiments are conducted to compare the stochastic and deterministic models, to examine the impact of different parameters on the routing results, and to evaluate the computational performance of the proposed algorithms.


      PubDate: 2015-07-25T21:47:15Z
       
  • Modeling taxi services with smartphone-based e-hailing applications
    • Abstract: Publication date: September 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 58, Part A
      Author(s): Fang He, Zuo-Jun Max Shen
      Traditionally, customers always hail empty-cruising taxis on streets, which may offer low levels of comfort and efficiency especially during rush hours or rainy days. Thanks to the advance of smartphone technology, the e-hailing applications, which enable customers to hail taxis through their smartphones, become popular globally. To provide a systematic account of the impact of e-hailing applications’ wide adoption on the taxi system, we first propose a spatial equilibrium model that not only balances the supply and demand of taxi services but also captures both the taxi drivers’ and customers’ possible adoption of the newly-emerging e-hailing applications in a well-regulated taxi market. We then prove the existence of the proposed equilibrium, and further provide an algorithm to solve it. An extensive equilibrium model with elastic taxi-customer demands is also proposed. Lastly, a numerical example is presented to compare the taxi services with and without the e-hailing application and evaluate two types of e-hailing applications.


      PubDate: 2015-07-25T21:47:15Z
       
  • Game theoretic approach for predictive lane-changing and car-following
           control
    • Abstract: Publication date: September 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 58, Part A
      Author(s): Meng Wang, Serge P. Hoogendoorn, Winnie Daamen, Bart van Arem, Riender Happee
      This contribution puts forward a receding horizon control approach for automated driving systems, where tactical-level lane change decisions and control-level accelerations are jointly evaluated under a central mathematical framework. The key idea is that controlled vehicles predictively determine discrete desired lane sequences and continuous accelerations to minimise a cost function reflecting undesirable future situations. The interactions between controlled vehicles and surrounding vehicles are captured in the cost function. The approach is flexible in terms of application to controller design for both non-cooperative control systems where controlled vehicles only optimise their own cost and cooperative control systems where controlled vehicles coordinate their decisions to optimise the collective cost. To determine the controller behaviour, the problem is formulated as a differential game where controlled vehicles make decisions based on the expected behaviour of other vehicles. The control decisions are updated at regular frequency, using the newest information regarding the state of controlled vehicles and surrounding vehicles available. A problem decomposition technique is employed to reduce the dimensionality of the original problem by introducing a finite number of sub-problems and an iterative algorithm based on Pontryagin’s Principle is used to solve sub-problems efficiently. The proposed controller performance is demonstrated via numerical examples. The results show that the proposed approach can produce efficient lane-changing manoeuvres while obeying safety and comfort requirements. Particularly, the approach generates optimal lane change decisions in the predicted future, including strategic overtaking, cooperative merging and selecting a safe gap.


      PubDate: 2015-07-25T21:47:15Z
       
  • Deliveries to residential units: A rising form of freight transportation
           in the U.S.
    • Abstract: Publication date: September 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 58, Part A
      Author(s): Xiaokun (Cara) Wang, Yiwei Zhou
      As a result of the rapid growth of online shopping, more goods and services are delivered directly to residential units. The door-to-door deliveries improve residents’ accessibility to retail sector, and at the same time create truck delivery trips. However, partially due to the data limitation, most existing freight research focuses on freight trips generated by business establishments. Little is known about freight trips generated by residential units. As a growing number of urban areas are pushing for dense and mixed development, it is necessary to understand the pattern of truck freight trips directly generated by residential units. This paper uses the U.S. National Household Travel Survey (NHTS) data to investigate the freight trips generated by residential units. The 2009 NHTS provides accurate, comprehensive and timely information on trips, land use, household characteristics and social economic factors. It is the first time that the NHTS data is used to estimate freight trips. A binary choice model and a right-censored negative binomial model are used to identify the impacts of person-related, household-related, and regional-specific variables on home delivery frequency. A case study for the New York State Capital District is then presented. The estimated freight trips generated by residential units are also compared to the freight trips generated by business establishments. Results, although still preliminary and subject to uncertainty, indicate that freight trips generated by residential units have comparable magnitude as the freight trips generated by businesses. Such a study will supplement city logistics studies that traditionally focus on business behavior, helping reconstruct a complete picture of the freight activities in urban areas.


      PubDate: 2015-07-25T21:47:15Z
       
  • Real-time traffic state estimation in urban corridors from heterogeneous
           data
    • Abstract: Publication date: Available online 21 July 2015
      Source:Transportation Research Part C: Emerging Technologies
      Author(s): Alfredo Nantes, Dong Ngoduy, Ashish Bhaskar, Marc Miska, Edward Chung
      In recent years, rapid advances in information technology have led to various data collection systems which are enriching the sources of empirical data for use in transport systems. Currently, traffic data are collected through various sensors including loop detectors, probe vehicles, cell-phones, Bluetooth, video cameras, remote sensing and public transport smart cards. It has been argued that combining the complementary information from multiple sources will generally result in better accuracy, increased robustness and reduced ambiguity. Despite the fact that there have been substantial advances in data assimilation techniques to reconstruct and predict the traffic state from multiple data sources, such methods are generally data-driven and do not fully utilize the power of traffic models. Furthermore, the existing methods are still limited to freeway networks and are not yet applicable in the urban context due to the enhanced complexity of the flow behavior. The main traffic phenomena on urban links are generally caused by the boundary conditions at intersections, un-signalized or signalized, at which the switching of the traffic lights and the turning maneuvers of the road users lead to shock-wave phenomena that propagate upstream of the intersections. This paper develops a new model-based methodology to build up a real-time traffic prediction model for arterial corridors using data from multiple sources, particularly from loop detectors and partial observations from Bluetooth and GPS devices.


      PubDate: 2015-07-21T21:42:26Z
       
  • Editorial Board/Copyright Information
    • Abstract: Publication date: August 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 57




      PubDate: 2015-07-21T21:42:26Z
       
  • Traffic flow optimisation in presence of vehicle automation and
           communication systems – Part II: Optimal control for multi-lane
           motorways
    • Abstract: Publication date: August 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 57
      Author(s): Claudio Roncoli, Markos Papageorgiou, Ioannis Papamichail
      Integrated motorway traffic flow control considering the use of Vehicle Automation and Communication Systems (VACS) is considered in this paper. VACS may act both as sensors (providing information on traffic conditions) and as actuators, permitting the deployment of ramp metering, variable speed limits, and lane changing control. The integrated traffic control problem is addressed through the formulation of a linearly constrained optimal control problem based on the first-order multi-lane model for motorways introduced and validated in a companion paper (Part I). A case study illustrating the potential improvements achievable using this approach is presented.


      PubDate: 2015-07-21T21:42:26Z
       
  • Capacity drops at merges: New analytical investigations
    • Abstract: Publication date: Available online 16 July 2015
      Source:Transportation Research Part C: Emerging Technologies
      Author(s): Ludovic Leclercq, Victor L. Knoop, Florian Marczak, Serge P. Hoogendoorn
      This paper focuses on the derivation of analytical formulae to estimate the effective capacity at freeway merges. It extends previous works by proposing a generic framework able to account for (i) heterogeneous vehicle characteristics and (ii) refined description of the physical interactions between upstream waves and downstream voids created by inserting vehicles within the merge area. The provided analytical formulae permit to directly compute the capacity values when the merge is self-active, i.e. when both upstream roads are congested while downstream traffic conditions are free-flow. They show that accounting for vehicle heterogeneity is not necessary when only the mean capacity is targeted. Calculations with the proper mean value for all parameters provide almost the same results as calculations that consider the full distributions for all parameters. This means that calibrating all distributions is not necessary only the mean parameter values are important. Finally, this paper also shows that vehicle heterogeneity plays a major role in the flow dynamics just upstream of the merge.


      PubDate: 2015-07-17T21:31:55Z
       
  • Optimal location of wireless charging facilities for electric vehicles:
           Flow-capturing location model with stochastic user equilibrium
    • Abstract: Publication date: September 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 58, Part A
      Author(s): Raffaela Riemann, David Z.W. Wang, Fritz Busch
      In this study, the optimal locations of a specific type of charging facilities for electric vehicles (EVs), wireless power transfer facilities, are investigated. A mathematical model has been developed to address this problem. The objective of the model is to locate a given number of wireless charging facilities for EVs out of a set of candidate facility locations for capturing the maximum traffic flow on a network. The interaction between traffic flow patterns and the location of the charging facilities is incorporated explicitly by applying the stochastic user equilibrium principle to describe electric vehicle drivers’ routing choice behavior. Firstly, the problem is formulated into a mixed-integer nonlinear program, secondly a solution method is developed to obtain the global optimal solution of the linearized program. Numerical experiments are presented to demonstrate the model validity.


      PubDate: 2015-07-17T21:31:55Z
       
  • Development of a wireless inspection and notification system with minimum
           monitoring hardware for real-time vehicle engine health inspection
    • Abstract: Publication date: September 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 58, Part A
      Author(s): Pak Kin Wong, Chi Man Vong, Ka In Wong, Zi-Qian Ma
      While many standards have been stipulated to control vehicular emissions, current inspection program for examining the engine health of in-use vehicles is practically ineffective and time-consuming. In particular, in-use vehicles are only required for inspection yearly, but huge amount of emissions may have been produced from malfunctioned engines daily. A new wireless inspection and notification system (WINS) is therefore proposed to monitor the vehicle engine health on the street in situ. The principle of WINS is to wirelessly examine some of the engine parameters through radio frequency identification (RFID) and traffic lights. RFID tags are installed on vehicles to collect the engine health information, whereas RFID interrogators are installed on traffic lights for wireless data transmission. Experiments were carried out to evaluate the effectiveness of the proposed WINS, and the results show that the proposed WINS is more convenient and economical than traditional vehicle inspection system. Moreover, as there are more than hundreds of traffic lights in the traffic network of a city, a maximum spanning tree (MAXST) algorithm is proposed to determine the suitable number of RFID devices required in the network so that the implementation cost, system loading and missing rate can be optimized. Different from the typical spanning tree algorithm in operational research, the MAXST algorithm has a domain-specific rule and weight calculation method for this application. To verify the methodology, simulations on the traffic networks of Shenzhen, New York and London were conducted. Results show that only 25–40% of traffic lights of the traffic networks are necessary for installation of RFID interrogators, with a rate of 2–7% that the vehicle owners may be able to escape the location of RFID interrogators.


      PubDate: 2015-07-17T21:31:55Z
       
  • Traffic control for air quality management and congestion mitigation in
           complex urban vehicular tunnels
    • Abstract: Publication date: September 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 58, Part A
      Author(s): Zhen Tan, H. Oliver Gao
      Urban vehicular tunnels, generally connected to the ground road network via on- and off-ramps, are geometrically complex with multiple entrances and exits. They are designed with in-tunnel ventilation systems and multiple pollutant discharge points for air quality control. In addition to traditional mechanical ventilation tools, traffic control has been recognized as a useful approach for air quality management and congestion mitigation in tunnels. This study aims to develop quantitative system analytic models for optimal traffic control considering both traffic and air quality improvement goals for complex urban tunnels. Moving vehicles inside the tunnel are not only the emission source, but also a key factor affecting aerodynamics in the tunnel. For a control cycle, steady-state traffic flow, aerodynamics, and pollutant dispersion models are established by tunnel segment, in which the air flow speed under a given mechanical ventilation scheme is mainly affected by tunnel traffic. An optimal time-of-day ramp traffic metering and mainline inlet traffic control model is proposed using nonlinear programming (NP) techniques to meet multiple air quality/emission as well as traffic throughput requirements. In-tunnel air quality requirements and emission limits at discharge points are modeled as nonlinear constraints for traffic control decisions. For illustration, the model was applied to an urban tunnel in Hangzhou, China for optimal traffic control to (1) assist the tunnel ventilation to meet environmental requirements under varying traffic demand; (2) provide a mechanism for tunnel air pollution control when fan operation alone is not enough during peak traffic period; and (3) maintain traffic efficiency by preventing recurrent congestion in the tunnel. The proposed tunnel traffic control method proves a useful complementary strategy to traditional mechanical tunnel ventilation for the improvement of urban tunnel transportation environment.


      PubDate: 2015-07-17T21:31:55Z
       
  • A real-life Multi Depot Multi Period Vehicle Routing Problem with a
           Heterogeneous Fleet: Formulation and Adaptive Large Neighborhood Search
           based Matheuristic
    • Abstract: Publication date: Available online 7 July 2015
      Source:Transportation Research Part C: Emerging Technologies
      Author(s): Simona Mancini
      In this paper, a new rich Vehicle Routing Problem that could arise in a real life context is introduced and formalized: the Multi Depot Multi Period Vehicle Routing Problem with a Heterogeneous Fleet. The goal of the problem is to minimize the total delivery cost. A heterogeneous fleet composed of vehicles with different capacity, characteristics (i.e. refrigerated vehicles) and hourly costs is considered. A limit on the maximum route duration is imposed. Unlike what happens in classical multi-depot VRP, not every customer may/will be served by all the vehicles or from all the depots. The planning horizon, as in most real life applications, consists of multiple periods, and the period in which each route is performed is a variable of the problem. The set of periods, within the time horizon, in which the delivery may be carried out is known for each customer. A Mixed Integer Programming (MIP) formulation for MDMPVRPHF is presented in this paper, and an Adaptive Large Neighborhood Search (ALNS) based Matheuristic approach is proposed, in which different destroy operators are defined. Computational results, pertaining to realistic instances, which show the effectiveness of the proposed method, are provided.


      PubDate: 2015-07-14T12:16:25Z
       
  • Traffic zone division based on big data from mobile phone base stations
    • Abstract: Publication date: Available online 9 July 2015
      Source:Transportation Research Part C: Emerging Technologies
      Author(s): Honghui Dong , Mingchao Wu , Xiaoqing Ding , Lianyu Chu , Limin Jia , Yong Qin , Xuesong Zhou
      Call detail record (CDR) data from mobile communication carriers offer an emerging and promising source of information for analysis of traffic problems. To date, research on insights and information to be gleaned from CDR data for transportation analysis has been slow, and there has been little progress on development of specific applications. This paper proposes the traffic semantic concept to extract traffic commuters’ origins and destinations information from the mobile phone CDR data and then use the extracted data for traffic zone division. A K-means clustering method was used to classify a cell-area (the area covered by a base stations) and tag a certain land use category or traffic semantic attribute (such as working, residential, or urban road) based on four feature data (including real-time user volume, inflow, outflow, and incremental flow) extracted from the CDR data. By combining the geographic information of mobile phone base stations, the roadway network within Beijing’s Sixth Ring Road was divided into a total of 73 traffic zones using another K-means clustering algorithm. Additionally, we proposed a traffic zone attribute-index to measure tendency of traffic zones to be residential or working. The calculated attribute-index values of 73 traffic zones in Beijing were consistent with the actual traffic and land-use data. The case study demonstrates that effective traffic and travel data can be obtained from mobile phones as portable sensors and base stations as fixed sensors, providing an opportunity to improve the analysis of complex travel patterns and behaviors for travel demand modeling and transportation planning.


      PubDate: 2015-07-14T12:16:25Z
       
  • A practice-ready relocation model for free-floating carsharing systems
           with electric vehicles – Mesoscopic approach and field trial results
           
    • Abstract: Publication date: August 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 57
      Author(s): Simone Weikl , Klaus Bogenberger
      This paper introduces a relocation model for free-floating Carsharing (FFCS) systems with conventional and electric vehicles (EVs). In case of imbalances caused by one-way trips, the approach recommends profit maximizing vehicle relocations. Unlike existing approaches, two types of relocations are distinguished: inter zone relocations moving vehicles between defined macroscopic zones of the operating area and intra zone relocations moving vehicles within such zones. Relocations are combined with the unplugging and recharging of EVs and the refueling of conventional vehicles. In addition, remaining pure service trips are suggested. A historical data analysis and zone categorization module enables the calculation of target vehicle distributions. Unlike existing approaches, macroscopic optimization steps are supplemented by microscopic rule-based steps. This enables relocation recommendations on the individual vehicle level with the exact GPS coordinates of the relocation end positions. The approach is practice-ready with low computational times even for large-scale scenarios. To assess the impact of relocations on the system’s operation, the model is applied to a FFCS system in Munich, Germany within three real world field tests. Test three shows the highest degree of automation and represents the final version of the model. Its evaluation shows very promising results. Most importantly, the profit is increased by 5.8% and the sales per vehicle by up to 10%. The mean idle time per trip end is decreased by 4%.


      PubDate: 2015-07-14T12:16:25Z
       
  • An adaptive large neighborhood search heuristic for fleet deployment
           problems with voyage separation requirements
    • Abstract: Publication date: Available online 14 July 2015
      Source:Transportation Research Part C: Emerging Technologies
      Author(s): Rikard Bakkehaug , Jørgen G. Rakke , Kjetil Fagerholt , Gilbert Laporte
      In this paper we propose an adaptive large neighborhood search heuristic for a ship routing and scheduling problem with voyage separation requirements. The voyage separation requirement is modeled as the minimum time elapsed between two consecutive sailings on a trade, and yields solutions with voyages fairly evenly spread over the planning horizon. Voyage separation requires the schedule of each ship to be synchronized with those of the others, since the start of service of a voyage could affect the feasible start time of another voyage. The proposed heuristic is compared with an exact algorithm on several instances, and yields good quality solutions within relatively short computation times.


      PubDate: 2015-07-14T12:16:25Z
       
  • Quasi-optimal feedback control for a system of oversaturated intersections
    • Abstract: Publication date: August 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 57
      Author(s): Weili Sun , Yunpeng Wang , Guizhen Yu , Henry X. Liu
      Oversaturated intersection control is a long-standing problem in traffic science and engineering. The problem becomes even harder when we consider a system of oversaturated intersections. Most of the research works in this area are off-line studies that require fully knowledge of origin–destination demand, which would be difficult to obtain in reality. Although several on-line feedback control methods are proposed, they only aim at preventing queue spillover, not able to minimize vehicular delay time. Moreover, these on-line control strategies are not theoretically evaluated how optimal (or sub-optimal) they are. We propose in this paper a quasi-optimal decentralized QUEUE-based feedback (abbreviated as QUEUE) control strategy for a system of oversaturated intersections. The QUEUE strategy is applied cycle-by-cycle based on measurement of current queue sizes, but its overall result is able to approximate the optimal one derived from off-line studies. Details of the feedback control laws for upstream and downstream intersections, in the queueing period and the queue dissipation period, are discussed. Superior to the existing feedback control strategies, the upper bounds of sub-optimality of the QUEUE strategy generating from demand fluctuation and coupling of intersections are specified quantitatively. It is also theoretically proved that the queue measurement error or demand estimation error would not be amplified by the QUEUE strategy. Numerical examples show that the QUEUE strategy performs very well and is robust to errors.


      PubDate: 2015-07-14T12:16:25Z
       
  • Cost effective future derailment mitigation techniques for rail freight
           traffic management in Europe
    • Abstract: Publication date: Available online 4 July 2015
      Source:Transportation Research Part C: Emerging Technologies
      Author(s): Dewan Md Zahurul Islam , Konstantina Laparidou , Arnaud Burgess
      Safe and reliable traffic management is vital for uninterrupted and successful operation of the European rail network, where mixed traffic (i.e. freight and passenger) services are run. Although rail freight derailment is infrequent, its consequences can be severe and may result in different forms of costs, including infrastructure; rolling stock; traffic disruptions; injuries and fatalities. The objective of this research paper is to conduct a cost benefit analysis (CBA) to identify cost effective mitigation techniques for efficient rail freight traffic management in Europe, by 2050. Reviewing previous derailments and studies, eight sets of derailment causes are analysed and, for each of them, sets of mitigation techniques are aimed at for their alleviation. The study finds that the highest cumulative costs of derailment are associated with ‘wheel failure’, while the lowest cumulative cost is identified for ‘excessive track width’. Regarding mitigation techniques, the lowest cumulative benefits are demonstrated for ‘track height’ interventions, whereas ‘wheel failure’ alleviation demonstrates the highest benefits, in value terms (all by 2050). In most cases, the benefit to cost ratio did not exceed 2.6; in two cases (‘track height’ and ‘rail failures’) the ratio remained below 1 – a negative outcome where cost is higher than benefit. The study suggests that the most cost-efficient interventions are those applied to ‘hot axle box and axle rupture’ and ‘spring and suspension failure’.


      PubDate: 2015-07-08T01:46:09Z
       
  • Congestion mechanism and demand adjustment strategies for double-cell
           system with bottlenecks
    • Abstract: Publication date: August 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 57
      Author(s): Nan Geng , Xiaomei Zhao , Dongfan Xie , Xingang Li , Ziyou Gao
      In this paper, ramp systems on the Beijing 3rd ring road are described as double-cell ramp systems with a bottleneck. By analyzing empirical data for the Beijing 3rd ring road, we found that the initial states have an important impact on the final convergence states of the ramp systems. Then, we studied the dynamic process of the ramp systems, determined the congestion mechanism, and then designed a ramp control method based on the obtained mechanism. Under a feasible demand, double-cell ramp systems exhibit two typical cases, including an upstream-bottleneck system (in which the bottleneck cell is upstream) and a downstream-bottleneck system (in which the bottleneck cell is downstream). Then, a cell transmission model is used to analyze the dynamic evolution processes, starting from different initial states, and determine the congestion mechanism for each case. It is proven that the two systems have different possible equilibrium sets and congestion mechanisms. In an upstream-bottleneck system, the downstream always converges to the uncongested equilibrium, while the upstream bottleneck cell may experience congestion under certain initial states. In a downstream-bottleneck system, the congestion starts downstream, and then gradually propagates upstream. Furthermore, based on the different congestion mechanisms, two demand adjustment strategies are proposed, which redistribute the stationary feasible demand. The simulation results indicate that both systems can converge to uncongested equilibriums after demand adjustment. The ramp demand adjustment methods provide a scientific basis for urban traffic system management.


      PubDate: 2015-07-08T01:46:09Z
       
  • Traffic flow optimisation in presence of vehicle automation and
           communication systems – Part I: A first-order multi-lane model for
           motorway traffic
    • Abstract: Publication date: Available online 4 July 2015
      Source:Transportation Research Part C: Emerging Technologies
      Author(s): Claudio Roncoli , Markos Papageorgiou , Ioannis Papamichail
      Proposed or emerging vehicle automation and communication systems (VACS) may contribute to the mitigation of motorway traffic congestion on the basis of appropriate traffic control strategies. In this context, this paper presents a novel first-order multi-lane macroscopic traffic flow model for motorways which is mainly intended for use within a related optimal control problem formulation. The model’s starting point is close to the well-known CTM (cell-transmission model), which is modified and extended to consider additional aspects of the traffic dynamics, such as lane changing and the capacity drop, via appropriate procedures for computing lateral and longitudinal flows. The model has been derived with a view to combine realistic traffic flow description with a simple (linear or piecewise linear) mathematical form, which can be exploited for efficient optimal control problem formulations, as described in a companion (Part II) paper. Although the model has been primarily derived for use in future traffic conditions including VACS, it may also be used for conventional traffic flow representation. In fact, the accuracy of the proposed modelling approach is demonstrated through calibration and validation procedures using real data from an urban motorway located in Melbourne, Australia.


      PubDate: 2015-07-08T01:46:09Z
       
  • Routing and fleet deployment in liner shipping with spot voyages
    • Abstract: Publication date: August 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 57
      Author(s): Rodrigo Moretti Branchini , Vinícius Amaral Armentano , Reinaldo Morabito
      The routing, scheduling and fleet deployment is an important integrated planning problem faced by liner shipping companies which also lift load from the spot market. This paper is concerned with coordinating the decisions of the assignment of ships to contractual and spot voyages, and the determination of ship routes and schedules in order to maximize profit. We propose a new model for representing voyages as nodes of a directed graph which is used to build a mixed integer programming formulation. Besides contractual and spot nodes, another type of node is put forward to represent a combination of a contractual voyage with one or more spot voyages. In addition, the concept of dominated nodes is introduced in order to discard them and reduce the effort of the search for an optimal solution. A set of test problems has been generated taking into account real world assumptions. The test problems are solved by an optimization software and computational results are reported. The results show the potential of the approach to solve test problems of moderate size.


      PubDate: 2015-07-08T01:46:09Z
       
  • An RFID-based inventory management framework for emergency relief
           operations
    • Abstract: Publication date: August 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 57
      Author(s): Eren Erman Ozguven , Kaan Ozbay
      In the aftermath of super storm Sandy, a large region from North Carolina to Maine endured food shortages, power outages, and long lines at gas stations forced to ration fuel due to low supply and high demand. These issues were largely the result of the affected transportation network’s inability to effectively cope with random and highly dynamic changes, and a lack of available resources and suppliers who were capable of enacting adequate emergency response measures. These problems experienced during super storm Sandy further underscored the need for a robust emergency inventory management system, where planning policies can be integrated with real-time on-line inventory management strategies to keep track of fluctuations of vital commodities such as food, water, medicine, fuel and power supplies. Motivated by this important problem, this paper investigates a comprehensive feedback-based emergency management framework for disasters such as super storm Sandy that provides integration with an emerging intelligent transportation systems technology, namely Radio Frequency Identification Devices (RFID). Within this framework, the offline-planning problem is solved by the stochastic humanitarian inventory management approach; and the online modeling strategy includes the application of a continuous time model predictive control technique. After introducing the mathematical background, the proposed framework is discussed using case studies built based on super storm Sandy in order to understand the efficiency and practicality of this RFID-based methodology. Results suggest that the methodology can properly account for and react to the rapidly changing needs for vital supplies that occur during the emergency relief operations. Based on this approach, planners and decision makers can be aware of the time delay that can happen due to disaster-related disruptions and thus maintain a safe level of buffer for vital supplies.


      PubDate: 2015-07-08T01:46:09Z
       
  • Time-dependent fuzzy random location-scheduling programming for hazardous
           materials transportation
    • Abstract: Publication date: August 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 57
      Author(s): Wei Meiyi , Li Xiang , Yu Lean
      The tremendous use of hazardous materials has promoted the economic development, which also brings about a growing risk causing a widespread concern. In this work, we consider a location-scheduling problem on hazardous materials transportation under the assumption that transportation risks are time-dependent fuzzy random variables. First, we formulate a scheduling optimization model and design a fuzzy random simulation based genetic algorithm to optimize the departure time and dwell times for each depot–customer pair. Then we establish an expected value model and design a modified particle swarm optimization algorithm to minimize the en route risks and site risks. Finally, numerical examples are given to illustrate the effectiveness of the proposed models and algorithms.


      PubDate: 2015-07-08T01:46:09Z
       
  • Personalised feedback and eco-driving: An explorative study
    • Abstract: Publication date: Available online 2 July 2015
      Source:Transportation Research Part C: Emerging Technologies
      Author(s): R.F.T. Brouwer , A. Stuiver , T. Hof , L. Kroon , J. Pauwelussen , B. Holleman
      Conventional road transport has negative impact on the environment. Stimulating eco-driving through feedback to the driver about his/her energy conservation performance has the potential to reduce CO2 emissions and promote fuel cost savings. Not all drivers respond well to the same type of feedback. Research has shown that different drivers are attracted to different types of information and feedback. The goal of this paper is to explore which different driver segments with specific psychographic characteristics can be distinguished, how these characteristics can be used in the development of an ecodriving support system and whether tailoring eco-driving feedback technology to these different driver segments will lead to increased acceptance and thus effectiveness of the eco feedback technology. The driver segments are based on the value orientation theory and learning orientation theory. Different possibilities for feedback were tested in an exploratory study in a driving simulator. An explorative study was selected since the choice of the display (how and when the information is presented) may have a strong impact on the results. This makes testing of the selected driver segments very difficult. The results of the study nevertheless suggest that adapting the display to a driver segment showed an increase in acceptance in certain cases. The results showed small differences for ratings on acceptation, ease of use, favouritism and a lower general rating between matched (e.g., learning display with learning oriented drivers) and mismatched displays (e.g., learning display with performance oriented drivers). Using a display that gives historical feedback and incorporates learning elements suggested a non-verifiable increase in acceptance for learning oriented drivers. However historical feedback and learning elements may be less effective for performance oriented drivers, who may need comparative feedback and game elements to improve energy conserving driving behaviour.


      PubDate: 2015-07-03T13:00:04Z
       
  • Bus service time estimation model for a curbside bus stop
    • Abstract: Publication date: August 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 57
      Author(s): Bomin Bian , Ning Zhu , Shuai Ling , Shoufeng Ma
      The bus service time at bus stop areas occupies a large proportion of the total on-road bus operational time. Curbside bus stops are very common in urban transit systems, and the occurrence of bus queues forming at the entry and departure area of bus stop is quite frequent. To estimate the service time at a curbside bus stop, a compound Poisson service time estimation model (CPSTM) is proposed. The CPSTM considers the interactions among arriving buses and number of boarding and alighting passengers. Realistic observational data are acquired for a representative bus stop. Four different scenarios are presented to estimate the total expected service time. The service time estimation of each bus line is obtained via the CPSTM, and the effectiveness of the proposed CPSTM is demonstrated. The results show that the employment of real-time data is not required for accurate service time estimation.


      PubDate: 2015-07-03T13:00:04Z
       
  • Location privacy preferences: A survey-based analysis of consumer
           awareness, trade-off and decision-making
    • Abstract: Publication date: July 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 56
      Author(s): Caitlin D. Cottrill , Piyushimita “Vonu” Thakuriah
      With the advent and rapid dissemination of location-sensing information technology, the issue of location information privacy is receiving growing attention. Perhaps of greatest concern is ensuring that potential users of mobile Information and Communications Technologies (e.g., Location-Based Services and Intelligent Transportation Systems) are comfortable with the levels of privacy protection afforded them, as well as with the benefits they will receive in return for providing private location information. This paper explores the concepts of privacy risks, benefits, willingness to trade, and compensation in relationship to mobile and locational technologies using a stated preference survey to ascertain areas of interest in determining the trade-offs that consumers will be willing to make in return for mobility enhancements. Analysis of the survey leads to findings that while respondents believe that sharing data in the mobile environment may pose privacy risks, they do not generally take steps necessary to address these risks; that privacy preferences are impacted by a range of factors, including both personal and contextual considerations (such as factors arising from their specific situation at the time of information seeking); and that willingness to trade private location data is dependent upon a number of factors related to context, personal characteristics, expected benefits and degree of trust in the collecting organization.


      PubDate: 2015-06-24T12:55:31Z
       
  • Orchestration of driving simulator scenarios based on dynamic actor
           preparation and automated action planning
    • Abstract: Publication date: July 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 56
      Author(s): Zhitao Xiong , Johan Olstam
      In driving simulation, a scenario includes definitions of the road environment, the traffic situation, simulated vehicles’ interactions with the participant’s vehicle and measurements that need to be collected. The scenarios need to be designed in such a way that the research questions to be studied can be answered, which commonly imply exposing the participant for a couple of predefined specific situations that has to be both realistic and repeatable. This article presents an integrated algorithm based on Dynamic Actor Preparation and Automated Action Planning to control autonomous simulated vehicles in the simulation in order to generate predefined situations. This algorithm is thus able to plan driving actions for autonomous vehicles based on specific tasks with relevant contextual information as well as handling longitudinal transportation of simulated vehicles based on the contextual information in an automated manner. The conducted experiment shows that the algorithm is able to guarantee repeatability under autonomous traffic flow. The presented algorithm can benefit not only the driving simulation community, but also relevant areas, such as autonomous vehicle and in-vehicle device design by providing them with an algorithm for target pursue and driving task accomplishment, which can be used to design a human-vehicle cooperation system in the coming era of autonomous driving.


      PubDate: 2015-06-24T12:55:31Z
       
  • Effect of speed limits in degradable transport networks
    • Abstract: Publication date: July 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 56
      Author(s): Chen-Yang Yan , Rui Jiang , Zi-You Gao , Hu Shao
      This paper studies how link-specific speed limits influence the performance of degradable transport networks, in which the capacity of each link is a degradable random variable. The distribution and cumulative distribution of link travel time have been presented with the effect of speed limits taken into account. The mean and variance of link and route travel time are formulated. Three link states have been classified, and their physical meanings have been discussed. The relationship between critical capacity, travel time and speed limit has been elaborated. We have proposed a Speed Limit- and Reliability-based User Equilibrium (SLRUE), adopting travel time budget as the principle of travelers’ route choice. A heuristic method employing the method of successive averages is developed to solve the SLRUE in degradable networks. Through numerical studies, we find that for some networks both the mean and standard deviation of the total travel time could be reduced simultaneously by imposing some speed limits. The speed limit design problem has been studied, and it is found that imposing speed limits cannot always reduce the total travel time budget of a network.


      PubDate: 2015-06-24T12:55:31Z
       
  • Vehicle detection grammars with partial occlusion handling for traffic
           surveillance
    • Abstract: Publication date: July 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 56
      Author(s): Bin Tian , Ming Tang , Fei-Yue Wang
      Traffic surveillance is an important topic in intelligent transportation systems (ITS). Robust vehicle detection is one challenging problem for complex traffic surveillance. In this paper, we propose an efficient vehicle detection method by designing vehicle detection grammars and handling partial occlusion. The grammar model is implemented by novel detection grammars, including structure, deformation and pairwise SVM grammars. First, the vehicle is divided into its constitute parts, called semantic parts, which can represent the vehicle effectively. To increase the robustness of part detection, the semantic parts are represented by their detection score maps. The semantic parts are further divided into sub-parts automatically. The two-layer division of the vehicle is modeled into a grammar model. Then, the grammar model is trained by a designed training procedure to get ideal grammar parameters, including appearance models and grammar productions. After that, vehicle detection is executed by a designed detection procedure with respect to the grammar model. Finally, the issue of vehicle occlusion is handled by designing and training specific grammars. The strategy adopted by our method is first to divide the vehicle into the semantic parts and sub-parts, then to train the grammar productions for semantic parts and sub-parts by introducing novel pairwise SVM grammars and finally to detect the vehicle by applying the trained grammars. Experiments in practical urban scenarios are carried out for complex traffic surveillance. It can be shown that our method adapts to partial occlusion and various challenging cases.


      PubDate: 2015-06-24T12:55:31Z
       
  • Electric vehicles in multi-vehicle households
    • Abstract: Publication date: July 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 56
      Author(s): Michael A. Tamor , Miloš Milačić
      The suitability of an electric vehicle of a given range to serve in place of a given conventional vehicle is not limited by the daily travel over distances within that that range, but rather by the occasional inconvenience of finding alternative transport for longer trips. While the frequency of this inconvenience can be computed from usage data, the willingness of individual users to accept that replacement depends on details of available transportation alternatives and their willingness to use them. The latter can be difficult to assess. Fortunately, 65% of US households have access to the most convenient alternative possible: a second car. In this paper we describe an analysis of prospective EV acceptance and travel electrification in two-car households in the Puget Sound region. We find that EVs with 60miles of useful range could be acceptable (i.e. incur inconvenience no more than three days each year) to nearly 90% of two-car households and electrify nearly 55% of travel in those households (32% of all travel). This compares to 120miles range required to achieve the same fraction of electrified travel via one-for-one replacement of individual vehicles. Even though only one third of personal vehicles in the US may be replaced in this paradigm, the ‘EV as a second-car’ concept is attractive in that a significant fraction of travel can be electrified by vehicles with modest electric range and virtually no dependence on public charging infrastructure.


      PubDate: 2015-06-24T12:55:31Z
       
  • An integrated solution for lane level irregular driving detection on
           highways
    • Abstract: Publication date: July 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 56
      Author(s): Rui Sun , Washington Yotto Ochieng , Shaojun Feng
      Global Navigation Satellite Systems (GNSS) has been widely used in the provision of Intelligent Transportation System (ITS) services. Current meter level system availability can fulfill the road level applications, such as route guide, fleet management and traffic control. However, meter level of system performance is not sufficient for the advanced safety applications. These lane level safety applications requires centimeter/decimeter positioning accuracy, with high integrity, continuity and availability include lane control, collision avoidance and intelligent speed assistance, etc. Detecting lane level irregular driving behavior is the basic requirement for these safety related ITS applications. The two major issues involved in the lane level irregular driving identification are accessing to high accuracy positioning and vehicle dynamic parameters and extraction of erratic driving behaviour from this and other related information. This paper proposes an integrated solution for the lane level irregular driving detection. Access to high accuracy positioning is enabled by GNSS and Inertial Navigation System (INS) integration using filtering with precise vehicle motion models and lane information. The detection of different types of irregular driving behaviour is based on the application of a Fuzzy Inference System (FIS). The evaluation of the designed integrated systems in the field test shows that 0.5m accuracy positioning source is required for lane level irregular driving detection algorithm and the designed system can detect irregular driving styles.


      PubDate: 2015-06-24T12:55:31Z
       
  • Empirical analysis of free-floating carsharing usage: The Munich and
           Berlin case
    • Abstract: Publication date: July 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 56
      Author(s): Stefan Schmöller , Simone Weikl , Johannes Müller , Klaus Bogenberger
      Carsharing has become an important addition to existing mobility services over the last years. Today, several different systems are operating in many big cities. For an efficient and economic operation of any carsharing system, the identification of customer demand is essential. This demand is investigated within the presented research by analyzing booking data of a German free-floating carsharing system. The objectives of this paper are to describe carsharing usage and to identify factors that have an influence on the demand for carsharing. Therefore, the booking data are analyzed for temporal aspects, showing recurring patterns of varying lengths. The spatial distribution of bookings is investigated using a geographic information system and indicates a relationship between city structure and areas with high demand for carsharing. The temporal and spatial facets are then combined by applying a cluster analysis to identify groups of days with similar spatial booking patterns and show asymmetries in the spatiotemporal distribution of vehicle supply and demand. Influences on demand can be either short-term or long-term. The paper shows that changes in the weather conditions are a short-term influence as users of free-floating carsharing react to those. Furthermore, the application of a linear regression analysis reveals that socio-demographic data are suitable for making long-term demand predictions since booking numbers show quite a strong correlation with socio-demography, even in a simple model.


      PubDate: 2015-06-24T12:55:31Z
       
  • A continuous-flow-intersection-lite design and traffic control for
           oversaturated bottleneck intersections
    • Abstract: Publication date: July 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 56
      Author(s): Weili Sun , Xinkai Wu , Yunpeng Wang , Guizhen Yu
      Oversaturation has become a severe problem for urban intersections, especially the bottleneck intersections that cause queue spillover and network gridlock. Further improvement of oversaturated arterial traffic using traditional mitigation strategies, which aim to improve intersection capacity by merely adjusting signal control parameters, becomes challenging since exiting strategies may (or already) have reached their “theoretical” limits of optimum. Under such circumstance, several novel unconventional intersection designs, including the well-recognized continuous flow intersection (CFI) design, are originated to improve the capacity at bottleneck intersections. However, the requirement of installing extra sub-intersections in a CFI design would increase vehicular stops and, more critically, is unacceptable in tight urban areas with closed spaced intersections. To address these issues, this research proposes a simplified continuous flow intersection (called CFI-Lite) design that is ideal for arterials with short links. It benefits from the CFI concept to enable simultaneous move of left-turn and through traffic at bottleneck intersections, but does not need installation of sub-intersections. Instead, the upstream intersection is utilized to allocate left-turn traffic to the displaced left-turn lane. It is found that the CFI-Lite design performs superiorly to the conventional design and regular CFI design in terms of bottleneck capacity. Pareto capacity improvement for every traffic stream in an arterial system can be achieved under effortless conditions. Case study using data collected at Foothill Blvd in Los Angeles, CA, shows that the new design is beneficial in more than 90% of the 408 studied cycles. The testing also shows that the average improvements of green bandwidths for the synchronized phases are significant.


      PubDate: 2015-06-24T12:55:31Z
       
  • Editorial Board/Copyright Information
    • Abstract: Publication date: July 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 56




      PubDate: 2015-06-24T12:55:31Z
       
  • Real-time estimation of lane-based queue lengths at isolated signalized
           junctions
    • Abstract: Publication date: July 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 56
      Author(s): Seunghyeon Lee , S.C. Wong , Y.C. Li
      In this study, we develop a real-time estimation approach for lane-based queue lengths. Our aim is to determine the numbers of queued vehicles in each lane, based on detector information at isolated signalized junctions. The challenges involved in this task are to identify whether there is a residual queue at the start time of each cycle and to determine the proportions of lane-to-lane traffic volumes in each lane. Discriminant models are developed based on time occupancy rates and impulse memories, as calculated by the detector and signal information from a set of upstream and downstream detectors. To determine the proportions of total traffic volume in each lane, the downstream arrivals for each cycle are estimated by using the Kalman filter, which is based on upstream arrivals and downstream discharges collected during the previous cycle. Both the computer simulations and the case study of real-world traffic show that the proposed method is robust and accurate for the estimation of lane-based queue lengths in real time under a wide range of traffic conditions. Calibrated discriminant models play a significant role in determining whether there are residual queued vehicles in each lane at the start time of each cycle. In addition, downstream arrivals estimated by the Kalman filter enhance the accuracy of the estimates by minimizing any error terms caused by lane-changing behavior.


      PubDate: 2015-06-24T12:55:31Z
       
  • Lane-based real-time queue length estimation using license plate
           recognition data
    • Abstract: Publication date: August 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 57
      Author(s): Xianyuan Zhan , Ruimin Li , Satish V. Ukkusuri
      License plate recognition (LPR) data are emerging data sources that provide rich information in estimating the traffic conditions of urban arterials. While large-scale LPR system is not common in US, last few years have seen rapid developments and implementations in many other parts of world (e.g. China, Thailand and Middle East). Due to privacy issues, LPR data are seldom available to research communities. However, when available, this data source can be valuable in estimating real-time operational metrics in transportation systems. This paper proposes a lane-based real-time queue length estimation model using the license plate recognition (LPR) data. In the model, an interpolation method based on Gaussian process is developed to reconstruct the equivalent cumulative arrival–departure curve for each lane. The missing information for unrecognized or unmatched vehicles is obtained from the reconstructed arrival curve. With the complete arrival and departure information, a car-following based simulation scheme is applied to estimate the real-time queue length for each lane. The proposed model is validated using ground truth information of the maximum queue lengths from the city of Langfang in China. The results show that the model can capture the variations in queue lengths in the ground truth data, and the maximum queue length for each signal cycle can be estimated with a reasonable accuracy. The estimated queue length information using the proposed model can serve as a useful performance metric for various real-time traffic control applications.


      PubDate: 2015-06-24T12:55:31Z
       
  • Standardization of capacity unit for headway-based rail capacity analysis
    • Abstract: Publication date: August 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 57
      Author(s): Yung-Cheng Lai , Yun-Hsuan Liu , Yi-Ju Lin
      Determining the required capacity upgrades to accommodate future demand is a critical process in assisting public and private financing of capacity investments. Conventional railway systems usually operate multiple types of trains on the same track. These different types of trains can exert substantially different capacity impact, and can cause serious operational conflicts. In the past, rail line capacity is commonly defined as the maximum number of trains that can be operated on a section of track within a given time period. However, a specific unit (trains/hr or trains/day) does not reflect the heterogeneity of train types. According to the concept of base train equivalents (BTE) and base train unit (BTU), this study developed headway-based models to determine BTE for transforming different train types into a standard unit (i.e., BTU). An approximate method for lines with three and more types of trains was also proposed to compute BTEs for non-base trains. Results from the case studies demonstrate that this method enables the standardization of rail capacity unit, facilitates assessment of the impact from heterogeneous trains, and allows comparison and evaluation of the capacity measurements from different lines and systems.


      PubDate: 2015-06-24T12:55:31Z
       
  • Real-time identification of probe vehicle trajectories in the mixed
           traffic corridor
    • Abstract: Publication date: August 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 57
      Author(s): Yu Mei , Keshuang Tang , Keping Li
      This paper proposes three enhanced semi-supervised clustering algorithms, namely the Constrained-K-Means (CKM), the Seeded-K-Means (SKM), and the Semi-Supervised Fuzzy c-Means (SFCM), to identify probe vehicle trajectories in the mixed traffic corridor. The proposed algorithms are able to take advantage of the strengthens of topological relation judgment and the semi-supervised learning technique by optimizing the selection of pre-labeling samples and initial clustering centers of the original semi-supervised learning technique based on horizontal Global Positioning System data. The proposed algorithms were validated and evaluated based on the probe vehicle data collected at two mixed corridors on Shanghai’s urban expressways. Results indicate that the enhanced SFCM algorithm could achieve the best performance in terms of clustering purity and Normalized Mutual Information, followed by the CKM algorithm and the SKM algorithm. It may reach a nearly 100% clustering purity for the uncongested conditions and a clustering purity greater than 80% for the congested conditions. Meanwhile, it could improve clustering purity averagely by 21% and 14% for the congested conditions and 6.5% and 6% for the uncongested conditions, as compared with the traditional K-Means algorithm and the basic SFCM. The proposed algorithms can be applied for both on-line and off-line purposes, without the need of historical data. Clustering accuracies under different traffic conditions and possible improvements with the use of historical data are also discussed.


      PubDate: 2015-06-24T12:55:31Z
       
  • Modeling route choice inertia in network equilibrium with heterogeneous
           prevailing choice sets
    • Abstract: Publication date: August 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 57
      Author(s): Junlin Zhang , Hai Yang
      The notion of inertia is originally a term in physics that describes the tendency of an object sustaining the same mode and its resistance of change in the state of motion. In the context of social and behavioral sciences, inertia is often understood as the endurance of stable relationships or reluctance in adjustment of status quo. In this paper, a precise definition of inertia under the criteria of route choice in the transportation network is presented. We then incorporate the concept of route choice inertia into the traffic assignment problem and propose a model of inertial user equilibrium (IUE). The inertial user equilibrium is compatible with the standard user equilibrium and extends UE with heterogeneous route choice inertia patterns. The variational inequality formulation is established. We show how travelers’ heterogeneous inertia patterns may redistribute traffic flow and affect the original network equilibrium. Useful equivalent conditions for equilibrium preservation are obtained. The impact of traffic information provision to alleviate inertia is analyzed. The relationship between IUE and ε-BRUE is briefly discussed. And a number of numerical examples are conducted.


      PubDate: 2015-06-24T12:55:31Z
       
  • Development of a maximum likelihood regression tree-based model for
           predicting subway incident delay
    • Abstract: Publication date: August 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 57
      Author(s): Jinxian Weng , Yang Zheng , Xiaobo Qu , Xuedong Yan
      This study aims to develop a maximum likelihood regression tree-based model to predict subway incident delays, which are major negative impacts caused by subway incidents from the commuter’s perspective. Using the Hong Kong subway incident data from 2005 and 2009, a tree comprising 10 terminal nodes is selected to predict subway incident delays in a case study. An accelerated failure time (AFT) analysis is conducted separately for each terminal node. The goodness-of-fit results show that our developed model outperforms the traditional AFT models with fixed and random effects because it can overcome the heterogeneity problem and over-fitting effects. The developed model is beneficial for subway engineers looking to propose effective strategies for reducing subway incident delays, especially in super-large-sized cities with huge public travel demand.


      PubDate: 2015-06-24T12:55:31Z
       
  • An energy-efficient scheduling approach to improve the utilization of
           regenerative energy for metro systems
    • Abstract: Publication date: August 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 57
      Author(s): Xin Yang , Anthony Chen , Xiang Li , Bin Ning , Tao Tang
      Regenerative braking is an energy recovery mechanism that converts the kinetic energy during braking into electricity, also known as regenerative energy. In general, most of the regenerative energy is transmitted backward along the pantograph and fed back into the overhead contact line. To reduce the trains’ energy consumption, this paper develops a scheduling approach to coordinate the arrivals and departures of all trains located in the same electricity supply interval so that the energy regenerated from braking trains can be more effectively utilized to accelerate trains. Firstly, we formulate an integer programming model with real-world speed profiles to minimize the trains’ energy consumption with dwell time control. Secondly, we design a genetic algorithm and an allocation algorithm to find a good solution. Finally, we present numerical examples based on the real-life operation data from the Beijing Metro Yizhuang Line in Beijing, China. The results show that the proposed scheduling approach can reduce energy consumption by 6.97% and save about 1,054,388 CNY (or 169,223 USD) each year in comparison with the current timetable. Compared to the cooperative scheduling (CS) approach, the proposed scheduling approach can improve the utilization of regenerative energy by 36.16% and reduce the total energy consumption by 4.28%.


      PubDate: 2015-06-24T12:55:31Z
       
  • Analysis of plug-in hybrid electric vehicles’ utility factors using
           GPS-based longitudinal travel data
    • Abstract: Publication date: August 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 57
      Author(s): Xing Wu , Md. Aviquzzaman , Zhenhong Lin
      The benefit of using a PHEV comes from its ability to substitute gasoline with electricity in operation. Defined as the proportion of distance traveled in the electric mode, the utility factor (UF) depends mostly on the battery capacity, but also on many other factors, such as travel pattern and recharging pattern. Conventionally, the UFs are calculated based on the daily vehicle miles traveled (DVMT) by assuming motorists leave home in the morning with a full battery, and no charge occurs before returning home in the evening. Such an assumption, however, ignores the impact of the heterogeneity in both travel and charging behavior, such as going back home more than once in a day, the impact of available charging time, and the price of gasoline and electricity. Moreover, the conventional UFs are based on the National Household Travel Survey (NHTS) data, which are one-day travel data of each sample vehicle. A motorist’s daily travel distance variation is ignored. This paper employs the GPS-based longitudinal travel data (covering 3–18months) collected from 403 vehicles in the Seattle metropolitan area to investigate how such travel and charging behavior affects UFs. To do this, for each vehicle, we organized trips to a series of home and work related tours. The UFs based on the DVMT are found close to those based on home-to-home tours. On the other hand, it is seen that the workplace charge opportunities significantly increase UFs if the CD range is no more than 40miles.
      Graphical abstract image

      PubDate: 2015-06-24T12:55:31Z
       
  • Highway voting system: Embracing a possible paradigm shift in traffic data
           acquisition
    • Abstract: Publication date: July 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 56
      Author(s): Wei-Hua Lin , Hong K. Lo
      The integration of internet and mobile phones has opened the door to a new wave of utilizing private vehicles as probes not only for performance evaluation but for traffic control as well, gradually replacing the role of traffic surveillance systems as the dominant source of traffic data. To prepare for such a paradigm shift, one needs to overcome some key institutional barriers, in particular, the privacy issue. A Highway Voting System (HVS) is proposed to address this issue in which drivers provide link- and/or path-based vehicle data to the traffic management system in the form of “votes” in order to receive favorable service from traffic control. The proposed HVS offers a platform that links data from individual vehicles directly with traffic control. In the system, traffic control responds to voting vehicles in a way similar to the current system responding to prioritized vehicles and providing the requested services accordingly. We show in the paper that the proposed “voting” system can effectively resolve the privacy issue which often hampers traffic engineers from getting detailed data from drivers. Strategies to entice drivers into “voting” so as to increase the market penetration level under all traffic conditions are discussed. Though the focus of the paper is on addressing the institutional issues associated with data acquisition from individual vehicles, other research topics associated with the proposed system are identified. Two examples are given to demonstrate the impact of the proposed system on algorithm development and traffic control.


      PubDate: 2015-06-24T12:55:31Z
       
  • Automated classification based on video data at intersections with heavy
           pedestrian and bicycle traffic: Methodology and application
    • Abstract: Publication date: July 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 56
      Author(s): Sohail Zangenehpour , Luis F. Miranda-Moreno , Nicolas Saunier
      Pedestrians and cyclists are amongst the most vulnerable road users. Pedestrian and cyclist collisions involving motor-vehicles result in high injury and fatality rates for these two modes. Data for pedestrian and cyclist activity at intersections such as volumes, speeds, and space–time trajectories are essential in the field of transportation in general, and road safety in particular. However, automated data collection for these two road user types remains a challenge. Due to the constant change of orientation and appearance of pedestrians and cyclists, detecting and tracking them using video sensors is a difficult task. This is perhaps one of the main reasons why automated data collection methods are more advanced for motorized traffic. This paper presents a method based on Histogram of Oriented Gradients to extract features of an image box containing the tracked object and Support Vector Machine to classify moving objects in crowded traffic scenes. Moving objects are classified into three categories: pedestrians, cyclists, and motor vehicles. The proposed methodology is composed of three steps: (i) detecting and tracking each moving object in video data, (ii) classifying each object according to its appearance in each frame, and (iii) computing the probability of belonging to each class based on both object appearance and speed. For the last step, Bayes’ rule is used to fuse appearance and speed in order to predict the object class. Using video datasets collected in different intersections, the methodology was built and tested. The developed methodology achieved an overall classification accuracy of greater than 88%. However, the classification accuracy varies across modes and is highest for vehicles and lower for pedestrians and cyclists. The applicability of the proposed methodology is illustrated using a simple case study to analyze cyclist–vehicle conflicts at intersections with and without bicycle facilities.


      PubDate: 2015-06-24T12:55:31Z
       
  • Vehicular Ad-Hoc Networks sampling protocols for traffic monitoring and
           incident detection in Intelligent Transportation Systems
    • Abstract: Publication date: July 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 56
      Author(s): Andrea Baiocchi , Francesca Cuomo , Mario De Felice , Gaetano Fusco
      Vehicular Ad-Hoc Networks (VANETs) are an emerging technology soon to be brought to everyday life. Many Intelligent Transport Systems (ITS) services that are nowadays performed with expensive infrastructure, like reliable traffic monitoring and car accident detection, can be enhanced and even entirely provided through this technology. In this paper, we propose and assess how to use VANETs for collecting vehicular traffic measurements. We provide two VANET sampling protocols, named SAME and TOME, and we design and implement an application for one of them, to perform real time incident detection. The proposed framework is validated through simulations of both vehicular micro-mobility and communications on the 68km highway that surrounds Rome, Italy. Vehicular traffic is generated based on a large real GPS traces set measured on the same highway, involving about ten thousand vehicles over many days. We show that the sampling monitoring protocol, SAME, collects data in few seconds with relative errors less than 10%, whereas the exhaustive protocol TOME allows almost fully accurate estimates within few tens of seconds. We also investigate the effect of a limited deployment of the VANET technology on board of vehicles. Both traffic monitoring and incident detection are shown to still be feasible with just 50% of equipped vehicles.


      PubDate: 2015-06-24T12:55:31Z
       
  • Does it pay to reveal safety information? The effect of safety
           information on flight choice
    • Abstract: Publication date: July 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 56
      Author(s): Aliza Fleischer , Anat Tchetchik , Tomer Toledo
      The case of flights safety lends itself as a natural case study for choice under of information asymmetry that involves dread risk and emotional factors. Specifically it allows one to experiment how the releasing of information will affect consumer choice. Previous studies, which followed the deregulation of commercial aviation, raised concerns about the corresponding potential for a marked deterioration in airline safety. Measures to prevent that decline were subsequently proposed. Specifically, it was argued that the public sector should establish and release flight safety indicators in addition to accidents’ statistics, which are currently available. It was argued that such safety indicators will also enable airlines to diversify their safety offerings. Underlying this argument are the assumptions that consumers’ flight safety preferences vary and that, provided with safety information, consumers will use it when making decisions. The present work, however, refutes the first assumption and sheds light on the second. It further investigates whether and how consumers react to and interpret safety information when choosing a flight, while accounting explicitly for a psychological trait. Employing an advanced experimental design and econometric approach, we find that: 1. When formal flight safety ratings are supplied, individuals abandoned their priors and rely on the information provided. 2. When it comes to “bad death” probabilities, people are not sensitive to the different shades of safety, and instead, they simply discern flights as either safe or unsafe. 3. Under a certain conditions disclosed information can alleviated fear and change the decision making of airline passengers.


      PubDate: 2015-06-24T12:55:31Z
       
  • A heuristic model of bounded route choice in urban areas
    • Abstract: Publication date: July 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 56
      Author(s): E.J. Manley , S.W. Orr , T. Cheng
      There is substantial evidence to indicate that route choice in urban areas is complex cognitive process, conducted under uncertainty and formed on partial perspectives. Yet, conventional route choice models continue make simplistic assumptions around the nature of human cognitive ability, memory and preference. In this paper, a novel framework for route choice in urban areas is introduced, aiming to more accurately reflect the uncertain, bounded nature of route choice decision making. Two main advances are introduced. The first involves the definition of a hierarchical model of space representing the relationship between urban features and human cognition, combining findings from both the extensive previous literature on spatial cognition and a large route choice dataset. The second advance involves the development of heuristic rules for route choice decisions, building upon the hierarchical model of urban space. The heuristics describe the process by which quick, ‘good enough’ decisions are made when individuals are faced with uncertainty. This element of the model is once more constructed and parameterised according to findings from prior research and the trends identified within a large routing dataset. The paper outlines the implementation of the framework within a real-world context, validating the results against observed behaviours. Conclusions are offered as to the extension and improvement of this approach, outlining its potential as an alternative to other route choice modelling frameworks.


      PubDate: 2015-04-19T12:07:04Z
       
 
 
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