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  Subjects -> TRANSPORTATION (Total: 164 journals)
    - AIR TRANSPORT (7 journals)
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    - TRANSPORTATION (95 journals)

TRANSPORTATION (95 journals)

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Journal Cover Transportation Research Part C: Emerging Technologies
  [SJR: 1.943]   [H-I: 55]   [21 followers]  Follow
    
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 0968-090X
   Published by Elsevier Homepage  [2969 journals]
  • Second order macroscopic traffic flow model validation using automatic
           differentiation with resilient backpropagation and particle swarm
           optimisation algorithms
    • Abstract: Publication date: October 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 71
      Author(s): Adam Poole, Apostolos Kotsialos
      The problem of validating the Modéle d’Écoulement de Trafic sur Autoroute NETworks (METANET) model of a motorway section is considered. Model calibration is formulated as a least squares error minimisation problem with explicit penalisation of fundamental diagram parameter variation. The Automatic Differentiation by Overloading in C++ (ADOL-C) library is incorporated into the METANET source code and is coupled with the Resilient Back Propagation (RPROP) heuristic for solving the minimisation problem. The result is a very efficient system which is able to be calibrate METANET by determining the density and speed equation parameters as well as the fundamental diagrams used. Information obtained from the system’s Jacobian provides extra insight into the dynamics showing how sensitivities propagate into the network. A 22km site near Sheffield, UK, using data from three different days is considered. In addition to the ADOL-C/RPROP system, three particle swarm optimisation algorithms are used for solving the calibration problem. In all cases, the optimal parameter sets found are verified on data not used during calibration. Although, all three sets of data display a similar congestion pattern, the verification process showed that only one of them is capable of leading to parameter sets that capture the underlying dynamics of the traffic flow process.


      PubDate: 2016-08-26T14:56:06Z
       
  • Heuristic search for the coupled runway sequencing and taxiway routing
           problem
    • Abstract: Publication date: October 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 71
      Author(s): Una Benlic, Alexander E.I. Brownlee, Edmund K. Burke
      This paper presents the first local search heuristic for the coupled runway sequencing (arrival & departure) and taxiway routing problems, based on the receding horizon (RH) scheme that takes into account the dynamic nature of the problem. As test case, we use Manchester Airport, the third busiest airport in the UK. From the ground movement perspective, the airport layout requires that departing aircraft taxi across the arrivals runway. This makes it impossible to separate arrival from departure sequencing in practice. Operationally, interactions between aircraft on the taxiways could prevent aircraft from taking off from, or landing on, runways during the slots assigned to them by an algorithm optimizing runway use alone. We thus consider the interactions between arrival and departure aircraft on the airport surface. Compared to sequentially optimized solutions, the results obtained with our approach indicate a significant decrease in the taxiway routing delay, with generally no loss in performance in terms of the sequencing delay for a regular day of operations. Another benefit of such a simultaneous optimization approach is the possibility of holding aircraft at the stands for longer, without the engines running. This significantly reduces the fuel burn, as well as bottlenecks and traffic congestion during peak hours that are often the cause of flight delays due to the limited amount of airport surface space available. Given that the maximum computing time per horizon is around 95s, real-time operation might be practical with increased computing power.


      PubDate: 2016-08-26T14:56:06Z
       
  • A simple reservation and allocation model of shared parking lots
    • Abstract: Publication date: October 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 71
      Author(s): Chaoyi Shao, Hai Yang, Yi Zhang, Jintao Ke
      With increasing auto demands, efficient parking management is by no means less important than road traffic congestion control. This is due to shortages of parking spaces within the limited land areas of the city centers in many metropolises. The parking problem becomes an integrated part of traffic planning and management. On the other hand, it is a fact that many private parking spots are available during daytime in nearby residential compound because those residents drive their cars out to work. These temporarily vacant parking lots can be efficiently utilized to meet the parking demand of other drivers who are working at nearby locations or drivers who come for shopping or other activities. This paper proposes a framework and a simple model for embracing shared use of residential parking spaces between residents and public users. The proposed shared use is a winning strategy because it maximizes the use of private resources to benefit the community as a whole. It also creates a new business model enabled by the fast-growing mobile apps in our daily lives.


      PubDate: 2016-08-26T14:56:06Z
       
  • Adaptive scheduling for real-time and temporal information services in
           vehicular networks
    • Abstract: Publication date: October 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 71
      Author(s): Penglin Dai, Kai Liu, Liang Feng, Qingfeng Zhuge, Victor C.S. Lee, Sang H. Son
      Vehicular networks represent a research area of significant importance in improving the safety, efficiency and sustainability of transportation systems. One of the key research problems in vehicular networks is real-time data dissemination, which is crucial to the satisfactory performance of many emergent applications providing real-time information services in vehicular networks. Specifically, the two issues need to be addressed in this problem are maintenance of temporal data freshness and timely dissemination of data. Most existing works only considered periodical data update via backbone wired networks in maintaining temporal data freshness. However, many applications rely on passing vehicles to upload their collected information via wireless network, which imposes new challenges as the uplink data update will have to compete with the downlink data dissemination for the limited wireless bandwidth. With such observations, we propose a temporal information service system, in which vehicles are able to collect up-to-date temporal information and upload them to the roadside units (RSU) along their trajectories. Meanwhile, RSU can disseminate its available data items to vehicles based on their specific requests. Particularly, in this paper, we first quantitatively analyze the freshness of temporal data and propose a mathematical model to evaluate the usefulness of the temporal data. Next, we give the formulation of the proposed real-time and temporal information service (RTIS) problem, and prove the NP-hardness of this problem by constructing a polynomial-time reduction from 0–1 knapsack problem. Subsequently, we establish a probabilistic model to theoretically analyze the tradeoff between timely temporal data update and requested data dissemination sharing a common communication resource, which provides a deeper insight of the proposed RTIS. Further, a heuristic algorithm, namely adaptive update request scheduling (AURS), is designed to enhance the efficacy of RTIS by synthesizing the broadcast effect, the real-time service requirement and the service quality in making scheduling decisions. The computational complexity and scalability analysis of AURS is also discussed. Last but not least, a simulation model is implemented and a comprehensive performance evaluation has been carried out to demonstrate the superiority of ARUS against several state-of-the-art approaches in a variety of application scenarios.


      PubDate: 2016-08-26T14:56:06Z
       
  • Spatial-temporal traffic flow pattern identification and anomaly detection
           with dictionary-based compression theory in a large-scale urban network
    • Abstract: Publication date: October 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 71
      Author(s): Zhenhua Zhang, Qing He, Hanghang Tong, Jizhan Gou, Xiaoling Li
      Traffic flow pattern identification, as well as anomaly detection, is an important component for traffic operations and control. To reveal the characteristics of regional traffic flow patterns in large road networks, this paper employs dictionary-based compression theory to identify the features of both spatial and temporal patterns by analyzing the multi-dimensional traffic-related data. An anomaly index is derived to quantify the network traffic in both spatial and temporal perspectives. Both pattern identifications are conducted in three different geographic levels: detector, intersection, and sub-region. From different geographic levels, this study finds several important features of traffic flow patterns, including the geographic distribution of traffic flow patterns, pattern shifts at different times-of-day, pattern fluctuations over different days, etc. Both spatial and temporal traffic flow patterns defined in this study can jointly characterize pattern changes and provide a good performance measure of traffic operations and management. The proposed method is further implemented in a case study for the impact of a newly constructed subway line. The before-and-after study identifies the major changes of surrounding road traffic near the subway stations. It is found that new metro stations attract more commute traffic in weekdays as well as entertaining traffic during weekends.


      PubDate: 2016-08-21T12:10:39Z
       
  • Traffic signal control with partial grade separation for oversaturated
           conditions
    • Abstract: Publication date: October 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 71
      Author(s): Qing He, Ramya Kamineni, Zhenhua Zhang
      Increasing individual vehicular traffic is a major concern all around the world. This leads to more and more oversaturated intersections. Traffic signal control under oversaturated condition is a long-lasting challenge. To address this challenge thoroughly, this paper introduces grade separation at signalized intersections. A lane-based optimization model is developed for the integrated design of grade-separated lanes (e.g. tunnels), lane markings (e.g. left turns, through traffic, right turns, etc.) and signal timing settings. We take into account two types of lane configurations. One is conventional surface lanes controlled by signals, and the other is grade-separated lanes. This problem is formulated as a Mixed Integer Linear Program (MILP), and this can be solved using the regular branch-and-bound methods. The integer decision variables help in finding if the movement is on grade-separated or surface lanes, and also the successor functions to govern the order of signal display. The continuous variables include the assigned lane flow, common flow multiplier, cycle length, and start and duration of green for traffic movements and lanes. The optimized signal time settings and lane configurations are then represented in Vissim simulation. Numerical examples, along with a benefit-cost analysis show the good savings of the proposed optimization model for oversaturated traffic conditions. The benefit-cost ratio for installing 4 grade-separated lanes (as a tunnel) at a heavily oversaturated intersection (intersection capacity utilization rate equal to 1.57) exceeds 5.4.
      Graphical abstract image

      PubDate: 2016-08-16T12:04:51Z
       
  • Economic analysis of ride-sourcing markets
    • Abstract: Publication date: October 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 71
      Author(s): Liteng Zha, Yafeng Yin, Hai Yang
      Ride-sourcing refers to an emerging urban mobility service that private car owners drive their own vehicles to provide for-hire rides. This paper analyzes the ride-sourcing market using an aggregate model where the matchings between customers and drivers are captured by an exogenous matching function. It is found that without any regulatory intervention a monopoly ride-sourcing platform will maximize the joint profit with its drivers. On the other hand, the first-best solution is not sustainable when the matching function exhibits increasing returns to scale and the cost function of the platform is subject to economies of scale. Regardless of the examined market scenarios, the average waiting time of customers is proportional to the average searching time of drivers. We establish conditions for regulators to solely regulate the commission charged by the platform to guarantee the second-best. We further investigate the competition of ride-sourcing platforms and find that competition does not necessarily lower the price level or improve social welfare. In the latter case, regulators may rather encourage the merger of the platforms and regulate them directly as a monopolist.


      PubDate: 2016-08-16T12:04:51Z
       
  • Capturing the conditions that introduce systematic variation in
           bike-sharing travel behavior using data mining techniques
    • Abstract: Publication date: October 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 71
      Author(s): Maria Bordagaray, Luigi dell’Olio, Achille Fonzone, Ángel Ibeas
      The potential of smart-card transactions within bike-sharing systems (BSS) is still to be explored. This research proposes an original offline data mining procedure that takes advantage of the quality of these data to analyze the bike usage casuistry within a sharing scheme. A difference is made between usage and travel behavior: the usage is described by the actual trip-chaining gathered with every smart-card transaction and is directly influenced by the limitations of the BSS as a public renting service, while the travel behavior relates to the spatio-temporal distribution, the travel time and trip purpose. The proposed approach is based on the hypothesis that there are systematic usage types which can be described through a set of conditions that permit to classify the rentals and reduce the heterogeneity in travel patterns. Hence, the proposed algorithm is a powerful tool to characterize the actual demand for bike-sharing systems. Furthermore, the results show that its potential goes well beyond that since service deficiencies rapidly arise and their impacts can be measured in terms of demand. Consequently, this research contributes to the state of knowledge on cycling behavior within public systems and it is also a key instrument beneficial to both decision makers and operators assisting the demand analysis, the service redesign and its optimization.


      PubDate: 2016-08-11T03:43:28Z
       
  • Signal coordination models for long arterials and grid networks
    • Abstract: Publication date: October 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 71
      Author(s): Lihui Zhang, Ziqi Song, Xiaojun Tang, Dianhai Wang
      This paper proposes two models to tackle traffic signal coordination problems for long arterials and grid networks. Both models, denoted as MaxBandLA and MaxBandGN, are built based on Little’s bandwidth maximization model, and the resulting formulations are both small-sized mixed-integer linear programs. Model MaxBandLA can optimize arterial partition plan and signal coordination plans of all the subsystems simultaneously. Model MaxBandGN directly optimizes the offsets for all the signals in a grid network, and as such, no ’cycle constraints’ need to be constructed. Numerical tests are presented to show that both models have the potential to produce coordination plans that are comparable to signal plans optimized by Synchro.


      PubDate: 2016-08-11T03:43:28Z
       
  • Understanding user acceptance factors of electric vehicle smart charging
    • Abstract: Publication date: October 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 71
      Author(s): Christian Will, Alexander Schuller
      Smart charging has been the focus of considerable research efforts but so far there is little notion of users’ acceptance of the concept. This work considers potentially influential factors for the acceptance of smart charging from the literature and tests their viability employing a structural equation model, following the partial least squares approach. For a sample of 237 early electric vehicle adopters from Germany our results show that contributing to grid stability and the integration of renewable energy sources are key motivational factors for acceptance of smart charging. In addition, the individual need for flexibility should not be impaired through charging control. Further well known influential factors like economic incentives do not seem to have a significant impact in the sample group under scrutiny. These and further findings should be taken into account by aggregators when designing attractive business models that incentivize the participation of early adopters and ease market rollout.


      PubDate: 2016-08-06T01:51:32Z
       
  • Modeling, calibrating, and validating car following and lane changing
           behavior
    • Abstract: Publication date: October 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 71
      Author(s): Zuduo Zheng, Majid Sarvi



      PubDate: 2016-08-06T01:51:32Z
       
  • Data fusion algorithm for macroscopic fundamental diagram estimation
    • Abstract: Publication date: October 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 71
      Author(s): Lukas Ambühl, Monica Menendez
      A promising framework that describes traffic conditions in urban networks is the macroscopic fundamental diagram (MFD), relating average flow and average density in a relatively homogeneous urban network. It has been shown that the MFD can be used, for example, for traffic access control. However, an implementation requires an accurate estimation of the MFD with the available data sources. Most scientific literature has considered the estimation of MFDs based on either loop detector data (LDD) or floating car data (FCD). In this paper, however, we propose a methodology for estimating the MFD based on both data sources simultaneously. To that end, we have defined a fusion algorithm that separates the urban network into two sub-networks, one with loop detectors and one without. The LDD and the FCD are then fused taking into account the accuracy and network coverage of each data type. Simulations of an abstract grid network and the network of the city of Zurich show that the fusion algorithm always reduces the estimation error significantly with respect to an estimation where only one data source is used. This holds true, even when we account for the fact that the probe penetration rate of FCD needs to be estimated with loop detectors, hence it might also include some errors depending on the number of loop detectors, especially when probe vehicles are not homogeneously distributed within the network.


      PubDate: 2016-08-06T01:51:32Z
       
  • A probabilistic model of pedestrian crossing behavior at signalized
           intersections for connected vehicles
    • Abstract: Publication date: October 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 71
      Author(s): Yoriyoshi Hashimoto, Yanlei Gu, Li-Ta Hsu, Miho Iryo-Asano, Shunsuke Kamijo
      Active safety systems which assess highly dynamic traffic situations including pedestrians are required with growing demands in autonomous driving and Connected Vehicles. In this paper, we focus on one of the most hazardous traffic situations: the possible collision between a pedestrian and a turning vehicle at signalized intersections. This paper presents a probabilistic model of pedestrian behavior to signalized crosswalks. In order to model the behavior of pedestrian, we take not only pedestrian physical states but also contextual information into account. We propose a model based on the Dynamic Bayesian Network which integrates relationships among the intersection context information and the pedestrian behavior in the same way as a human. The particle filter is used to estimate the pedestrian states, including position, crossing decision and motion type. Experimental evaluation using real traffic data shows that this model is able to recognize the pedestrian crossing decision in a few seconds from the traffic signal and pedestrian position information. This information is assumed to be obtained with the development of Connected Vehicle.


      PubDate: 2016-08-02T00:51:22Z
       
  • Influence of connected and autonomous vehicles on traffic flow stability
           and throughput
    • Abstract: Publication date: October 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 71
      Author(s): Alireza Talebpour, Hani S. Mahmassani
      The introduction of connected and autonomous vehicles will bring changes to the highway driving environment. Connected vehicle technology provides real-time information about the surrounding traffic condition and the traffic management center’s decisions. Such information is expected to improve drivers’ efficiency, response, and comfort while enhancing safety and mobility. Connected vehicle technology can also further increase efficiency and reliability of autonomous vehicles, though these vehicles could be operated solely with their on-board sensors, without communication. While several studies have examined the possible effects of connected and autonomous vehicles on the driving environment, most of the modeling approaches in the literature do not distinguish between connectivity and automation, leaving many questions unanswered regarding the implications of different contemplated deployment scenarios. There is need for a comprehensive acceleration framework that distinguishes between these two technologies while modeling the new connected environment. This study presents a framework that utilizes different models with technology-appropriate assumptions to simulate different vehicle types with distinct communication capabilities. The stability analysis of the resulting traffic stream behavior using this framework is presented for different market penetration rates of connected and autonomous vehicles. The analysis reveals that connected and autonomous vehicles can improve string stability. Moreover, automation is found to be more effective in preventing shockwave formation and propagation under the model’s assumptions. In addition to stability, the effects of these technologies on throughput are explored, suggesting substantial potential throughput increases under certain penetration scenarios.


      PubDate: 2016-08-02T00:51:22Z
       
  • Multi-step prediction of experienced travel times using agent-based
           modeling
    • Abstract: Publication date: October 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 71
      Author(s): Hao Chen, Hesham A. Rakha
      This paper develops an agent-based modeling approach to predict multi-step ahead experienced travel times using real-time and historical spatiotemporal traffic data. At the microscopic level, each agent represents an expert in a decision-making system. Each expert predicts the travel time for each time interval according to experiences from a historical dataset. A set of agent interactions is developed to preserve agents that correspond to traffic patterns similar to the real-time measurements and replace invalid agents or agents associated with negligible weights with new agents. Consequently, the aggregation of each agent’s recommendation (predicted travel time with associated weight) provides a macroscopic level of output, namely the predicted travel time distribution. Probe vehicle data from a 95-mile freeway stretch along I-64 and I-264 are used to test different predictors. The results show that the agent-based modeling approach produces the least prediction error compared to other state-of-the-practice and state-of-the-art methods (instantaneous travel time, historical average and k-nearest neighbor), and maintains less than a 9% prediction error for trip departures up to 60min into the future for a two-hour trip. Moreover, the confidence boundaries of the predicted travel times demonstrate that the proposed approach also provides high accuracy in predicting travel time confidence intervals. Finally, the proposed approach does not require offline training thus making it easily transferable to other locations and the fast algorithm computation allows the proposed approach to be implemented in real-time applications in Traffic Management Centers.


      PubDate: 2016-07-27T13:10:39Z
       
  • A discrete dynamical system of formulating traffic assignment: Revisiting
           Smith’s model
    • Abstract: Publication date: October 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 71
      Author(s): Ren-Yong Guo, Hai-Jun Huang
      Through relaxing the behavior assumption adopted in Smith’s model (Smith, 1984), we propose a discrete dynamical system to formulate the day-to-day evolution process of traffic flows from a non-equilibrium state to an equilibrium state. Depending on certain preconditions, the equilibrium state can be equivalent to a Wardrop user equilibrium (UE), Logit-based stochastic user equilibrium (SUE), or boundedly rational user equilibrium (BRUE). These equivalence properties indicate that, to make day-to-day flows evolve to equilibrium flows, it is not necessary for travelers to choose their routes based on actual travel costs of the previous day. Day-to-day flows can still evolve to equilibrium flows provided that travelers choose their routes based on estimated travel costs which satisfy these preconditions. We also show that, under a more general assumption than the monotonicity of route cost function, the trajectory of the dynamical system converges to a set of equilibrium flows by reasonably setting these parameters in the dynamical system. Finally, numerical examples are presented to demonstrate the application and properties of the dynamical system. The study is helpful for understanding various processes of forming traffic jam and designing an algorithm for calculating equilibrium flows.


      PubDate: 2016-07-27T13:10:39Z
       
  • Editorial Board/Copyright Information
    • Abstract: Publication date: August 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 69




      PubDate: 2016-07-27T13:10:39Z
       
  • Non-recurrent congestion analysis using data-driven spatiotemporal
           approach for information construction
    • Abstract: Publication date: October 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 71
      Author(s): Zhuo Chen, Xiaoyue Cathy Liu, Guohui Zhang
      A systematic approach to quantify Incident-Induced Delay (IID) is proposed in this study. The paper complements existing literature by developing a data-driven method to dynamically determine the spatiotemporal extent of individual incidents. The information construction process can be further used to uncover a variety of features that are associated with any specific incidents for optimal freeway management. Additionally, this study contributes two particular highlights: secondary incident identification and K-Nearest Neighbor (KNN) pattern matching. Secondary incident identification, as a pre-processing for IID estimation, disentangles the convoluted influences of subsequent incidents. The proposed method uses KNN pattern matching, an essentially heuristic search process to separate the delay solely induced by incidents from the recurrent congestion. The proposed algorithm on IID quantification was implemented on Interstate 15 in the state of Utah using data obtained from 2013. Results and implications are presented. Hot spot analysis is conducted that can be potentially used for incident mitigation and to inform investment decisions. The proposed methodology is easily transferable to any traffic operation system that has access to sensor data at a corridor level.


      PubDate: 2016-07-19T13:06:25Z
       
  • Integrated traffic-transit stochastic equilibrium model with park-and-ride
           facilities
    • Abstract: Publication date: October 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 71
      Author(s): Cristobal Pineda, Cristián E. Cortés, Pedro Jara-Moroni, Eduardo Moreno
      We propose an Integrated Stochastic Equilibrium model that considers both private automobile traffic and transit networks to incorporate the interactions between these two modes in terms of travel time and generalized costs. In addition, in the general version of the model, travelers are allowed to switch from personal vehicles to mass transit at specific locations in a park-and-ride scheme. The assignment for traffic equilibrium is based on the Markovian Traffic Equilibrium model of Baillon and Cominetti (2008), whereas the equilibrium of the transit network is represented by the Stochastic Transit Equilibrium model of Cortés et al. (2013). Stochastic travel decisions are made at the node level, thereby avoiding the enumeration of routes or strategies and incorporating various perception and uncertainty issues. We propose a Method-of-Successive-Averages algorithm to calculate an Integrated Stochastic Equilibrium and conduct numerical experiments to highlight the effect of stochasticity on equilibrium flows and travel times. Our experiments show that higher stochasticity implies greater dispersion of equilibrium flows and longer expected travel times. Results on a real network with mode combination and park and ride facilities provide insights regarding the use of park and ride in terms of number and location, potential modal share of the combined mode option under different circumstances, and travel time impact due to the implementation of such park and ride facilities in a real setting.


      PubDate: 2016-07-19T13:06:25Z
       
  • The influence of attitude towards individuals’ choice for a remotely
           piloted commercial flight: A latent class logit approach
    • Abstract: Publication date: October 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 71
      Author(s): Brett R.C. Molesworth, Tay T.R. Koo
      The Remotely Piloted Commercial Passenger Aircraft Attitude Scale (RPCPAAS) was created to measure positive and negative attitudes towards a new and plausible form of air travel. This information was then used, in combination with a latent class logit model built on data generated from a stated choice experiment to gain insight into the choice behaviour between conventionally piloted aircraft (CPA) with a pilot on-board and remotely piloted aircraft (RPA) with a pilot on the ground. The results revealed that individuals, on-average, if presented a choice between a CPA and a RPA of equivalent attributes, would elect for the CPA option. However, there is variability in the passengers’ sensitivity to various flight attributes, and these sensitivities were influenced by individuals’ attitude towards the new technology (i.e., RPA). From an operational perspective, and assuming that one day passengers of commercial airlines are offered the choice between CPA and RPA, the strategies employed by airlines to encourage the use of the new technology need to be different, based on individuals’ attitude towards RPA.


      PubDate: 2016-07-19T13:06:25Z
       
  • Uni- and bi-directional pedestrian flow in the view-limited condition:
           Experiments and modeling
    • Abstract: Publication date: October 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 71
      Author(s): Ning Guo, Qing-Yi Hao, Rui Jiang, Mao-Bin Hu, Bin Jia
      In this paper, the impact of vision on the uni- and bi-directional flow has been investigated via experiment and modeling. In the experiments, pedestrians are asked to walk clockwise/anti-clockwise in a ring-shaped corridor under view-limited condition and normal view condition. As expected, the flow rate under the view-limited condition decreases comparing with that under the normal view condition, no matter in uni- or bi-directional flow. In bidirectional flow, pedestrians segregate into two opposite moving streams very quickly under the normal view condition, and clockwise/anti-clockwise walking pedestrians are always in the inner/outer ring due to right-walking preference. In the first set of experiment, spontaneous lane formation has not occurred under the view-limited condition. Pedestrian flow does not evolve into stationary state. Local congestion occurs and dissipates from time to time. However, in the later sets of experiments, spontaneous lane formation has re-occurred. This is because participants learned from the experience and adapted right-walking preference to avoid collision. To model the flow dynamics, an improved force-based model has been proposed. The driving force has been modified. The right-walking preference has been taken into account. The fact that pedestrians cannot judge the moving direction accurately under limited-view condition has been considered. Simulation results are in good agreement with the experimental ones.


      PubDate: 2016-07-19T13:06:25Z
       
  • A lane-level road network model with global continuity
    • Abstract: Publication date: October 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 71
      Author(s): Tao Zhang, Stefano Arrigoni, Marco Garozzo, Dian-ge Yang, Federico Cheli
      An increasing number of Intelligent Transportation System (ITS) applications require high accurate vehicle positioning, e.g., positioning at the lane-level. This requirement motives the development of modeling the road network at the lane-level. In this paper we propose a novel lane-level road network model. It can be considered an improvement to existing models in its capability of representing the road and intersection details at the lane-level in a uniform and precise way. As a result, the model can guarantee the global continuity for arbitrary map route, which better approximates the real vehicle trajectory. In addition, the map construction algorithms are also developed. Following the proposed methods, the lane parameters can be extracted efficiently under flexible precision requirement, and intersections with varying appearances can be precisely modeled with limited extra data. Experiments were performed to verify the proposed model in representing the lane-level geometrical and topological details of an urban area of Milan. The results also demonstrate the effectiveness of the map construction methods.


      PubDate: 2016-07-19T13:06:25Z
       
  • Optimization of traffic flow at freeway sags by controlling the
           acceleration of vehicles equipped with in-car systems
    • Abstract: Publication date: October 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 71
      Author(s): Bernat Goñi-Ros, Victor L. Knoop, Toshimichi Takahashi, Ichiro Sakata, Bart van Arem, Serge P. Hoogendoorn
      Sags are bottlenecks in freeway networks. According to previous research, the main cause is that most drivers do not accelerate enough at sags. Consequently, they keep longer headways than expected given their speed, which leads to congestion in high demand conditions. Nowadays, there is growing interest in the development of traffic control measures for sags based on the use of in-car systems. This paper aims to determine the optimal acceleration behavior of vehicles equipped with in-car systems at sags and the related effects on traffic flow, thereby laying the theoretical foundation for developing effective traffic management applications. We formulate an optimal control problem in which a centralized controller regulates the acceleration of some vehicles of a traffic stream moving along a single-lane freeway stretch with a sag. The control objective is to minimize total travel time. The problem is solved for scenarios with different numbers of controlled vehicles and positions in the stream, assuming low penetration rates. The results indicate that the optimal behavior involves performing a deceleration-acceleration-deceleration-acceleration (DADA) maneuver in the sag area. This maneuver induces the first vehicles located behind the controlled vehicle to accelerate fast along the vertical curve. As a result, traffic speed and flow at the end of the sag (bottleneck) increase for a time. The maneuver also triggers a stop-and-go wave that temporarily limits the inflow into the sag, slowing down the formation of congestion at the bottleneck. Moreover, in some cases controlled vehicles perform one or more deceleration-acceleration maneuvers upstream of the sag. This additional strategy is used to manage congestion so that inflow is regulated more effectively. Although we cannot guarantee global optimality, our findings reveal a potentially highly effective and innovative way to reduce congestion at sags, which could possibly be implemented using cooperative adaptive cruise control systems.


      PubDate: 2016-07-12T23:40:56Z
       
  • Optimal locations and travel time display for variable message signs
    • Abstract: Publication date: August 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 69
      Author(s): Meng Li, Xi Lin, Fang He, Han Jiang
      This paper first develops a network equilibrium model with the travel time information displayed via variable message signs (VMS). Specifically, the equilibrium considers the impact of the displayed travel time information on travelers’ route choices under the recurrent congestion, with the endogenous utilization rates of displayed information by travelers. The existence of the equilibrium is proved and an iterative solution procedure is provided. Then, we conduct the sensitivity analyses of the network equilibrium and further propose a paradox, i.e., providing travel time information via VMS to travelers may degrade the network performance under some poor designs. Therefore, we investigate the problem of designing the VMS locations and travel time display within a given budget, and formulate it as a mixed integer nonlinear program, solved by an active-set algorithm. Lastly, numerical examples are presented to offer insights on the equilibrium results and optimal designs of VMS.


      PubDate: 2016-07-09T06:12:04Z
       
  • Forecasting travel behavior using Markov Chains-based approaches
    • Abstract: Publication date: August 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 69
      Author(s): Ismaïl Saadi, Ahmed Mustafa, Jacques Teller, Mario Cools
      Recent advances in agent-based micro-simulation modeling have further highlighted the importance of a thorough full synthetic population procedure for guaranteeing the correct characterization of real-world populations and underlying travel demands. In this regard, we propose an integrated approach including Markov Chain Monte Carlo (MCMC) simulation and profiling-based methods to capture the behavioral complexity and the great heterogeneity of agents of the true population through representative micro-samples. The population synthesis method is capable of building the joint distribution of a given population with its corresponding marginal distributions using either full or partial conditional probabilities or both of them simultaneously. In particular, the estimation of socio-demographic or transport-related variables and the characterization of daily activity-travel patterns are included within the framework. The fully probabilistic structure based on Markov Chains characterizing this framework makes it innovative compared to standard activity-based models. Moreover, data stemming from the 2010 Belgian Household Daily Travel Survey (BELDAM) are used to calibrate the modeling framework. We illustrate that this framework effectively captures the behavioral heterogeneity of travelers. Furthermore, we demonstrate that the proposed framework is adequately adapted to meeting the demand for large-scale micro-simulation scenarios of transportation and urban systems.


      PubDate: 2016-07-09T06:12:04Z
       
  • Generation and recovery of airborne delays in air transport
    • Abstract: Publication date: August 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 69
      Author(s): Seddik Belkoura, José Maria Peña, Massimiliano Zanin
      The analysis of the causes behind the appearance and propagation of delays is one of the major topics inside Air Transport Management research. Existing research focuses by and large on Air Traffic Flow Management regulations and reactionary delays; less attention has been devoted to the study of the mechanisms governing the generation and absorption of delays while airborne, in spite of their important economical and environmental consequences. Here we present a methodology to detect delay-generating events, based on the comparison of planned and real trajectories; these events are then used to characterise several aspects of the dynamics of the system, e.g. its resilience. We apply this methodology to a historical data set of flights crossing the European airspace during 2011, and observe an overall resilient system, able to absorb as much delays as it generates; yet resilience is not constant, but strongly depends on the phase of the flight, and shows high spatial and temporal heterogeneities. We anticipate the proposed methodology to open new doors for the development of a better systemic performance, by enabling the characterisation and understanding of this fundamental type of delay.


      PubDate: 2016-07-09T06:12:04Z
       
  • Density/Flow reconstruction via heterogeneous sources and Optimal Sensor
           Placement in road networks
    • Abstract: Publication date: August 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 69
      Author(s): E. Lovisari, C. Canudas de Wit, A.Y. Kibangou
      This paper addresses the two problems of flow and density reconstruction in Road Transportation Networks with heterogeneous information sources and cost effective sensor placement. Following a standard modeling approach, the network is partitioned in cells, whose vehicle densities change dynamically in time according to first order conservation laws. The first problem is to estimate flow and the density of vehicles using as sources of information standard fixed sensors, precise but expensive, and Floating Car Data, less precise due to low penetration rates, but already available on most of main roads. A data fusion algorithm is proposed to merge the two sources of information to estimate the network state. The second problem is to place sensors by trading off between cost and performance. A relaxation of the problem, based on the concept of Virtual Variances, is proposed and solved using convex optimization tools. The efficiency of the designed strategies is shown on a regular grid and in the real world scenario of Rocade Sud in Grenoble, France, a ring road 10.5km long.


      PubDate: 2016-07-09T06:12:04Z
       
  • The impact of car specifications, prices and incentives for battery
           electric vehicles in Norway: Choices of heterogeneous consumers
    • Abstract: Publication date: August 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 69
      Author(s): Yingjie Zhang, Zhen (Sean) Qian, Frances Sprei, Beibei Li
      Electric vehicles (EVs), specifically Battery EVs (BEVs), can offer significant energy and emission savings over internal combustion engine vehicles. Norway has a long history of research and government incentives for BEVs. The BEV market in Norway allows us to fully examine consumers’ BEV choices influenced by car specifications, prices and government incentives (public bus lanes access, toll waiver and charging stations). The Random-Coefficient Discrete Choice Model (referred to as the BLP model) is applied to understand the choices of heterogeneous personal consumers and business buyers. Our study is instantiated on the entire EV sales data in Norway from 2011 to 2013, as well as a set of demographics at the municipality level. The results suggest significant positive effects of BEV technology improvement, space, toll waiver and charging station density on EV demand for both personal consumers and business buyers. However, the effects on business buyers may be generally less pronounced than on personal consumers. Interestingly, bus lanes access demonstrates a negative impact for personal consumers, possibly due to consumers’ concern regarding bus lane congestion. In addition, preferences on the BEV price can vary statistically among consumers with different income levels. Compared to the BEV technology development, demographical features and municipal incentives may have generally less impacts on market shares within the BEV market.


      PubDate: 2016-07-04T06:02:27Z
       
  • Preferences for shared autonomous vehicles
    • Abstract: Publication date: August 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 69
      Author(s): Rico Krueger, Taha H. Rashidi, John M. Rose
      Shared autonomous vehicles (SAVs) could provide inexpensive mobility on-demand services. In addition, the autonomous vehicle technology could facilitate the implementation of dynamic ride-sharing (DRS). The widespread adoption of SAVs could provide benefits to society, but also entail risks. For the design of effective policies aiming to realize the advantages of SAVs, a better understanding of how SAVs may be adopted is necessary. This article intends to advance future research about the travel behavior impacts of SAVs, by identifying the characteristics of users who are likely to adopt SAV services and by eliciting willingness to pay measures for service attributes. For this purpose, a stated choice survey was conducted and analyzed, using a mixed logit model. The results show that service attributes including travel cost, travel time and waiting time may be critical determinants of the use of SAVs and the acceptance of DRS. Differences in willingness to pay for service attributes indicate that SAVs with DRS and SAVs without DRS are perceived as two distinct mobility options. The results imply that the adoption of SAVs may differ across cohorts, whereby young individuals and individuals with multimodal travel patterns may be more likely to adopt SAVs. The methodological limitations of the study are also acknowledged. Despite a potential hypothetical bias, the results capture the directionality and relative importance of the attributes of interest.


      PubDate: 2016-06-29T22:58:25Z
       
  • A mathematical programming technique for matching time-stamped records in
           logistics and transportation systems
    • Abstract: Publication date: August 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 69
      Author(s): L. Douglas Smith, Jan Fabian Ehmke
      Time-stamped data for transportation and logistics are essential for estimating times on transportation legs and times between successive stages in logistic processes. Often these data are subject to recording errors and omissions. Matches must then be inferred from the time stamps alone because identifying keys are unavailable, suppressed to preserve confidentiality, or ambiguous because of missing observations. We present an integer programming (IP) model developed for matching successive events in such situations and illustrate its application in three problem settings involving (a) airline operations at an airport, (b) taxi service between an airport and a train station, and (c) taxi services from an airport. With data from the third setting (where a matching key was available), we illustrate the robustness of estimates for median and mean times between events under different random rates for “failure to record”, different screening criteria for outliers, and different target times used in the IP objective. The IP model proves to be a tractable and informative tool for data matching and data cleaning, with a wide range of potential applications.


      PubDate: 2016-06-29T22:58:25Z
       
  • A distributed framework for network-wide traffic monitoring and platoon
           information aggregation using V2V communications
    • Abstract: Publication date: August 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 69
      Author(s): Yingyan Lou, Peiheng Li, Xiaoyan Hong
      This study explores an innovative framework for distributed traffic monitoring and information aggregation using vehicle-to-vehicle (V2V) communications alone. We envision the proposed framework as the foundation to an alternative or supplemental traffic operation and management system, which could be particularly helpful under abnormal traffic conditions caused by unforeseen disasters and special events. Each equipped vehicle, through the distributed protocols developed, keeps track of the average traffic density and speed within a certain range, flags itself as micro-discontinuity in traffic if appropriate, and cross-checks its flag status with its immediate up- and down-stream vehicles. The micro-discontinuity flags define vehicle groups with similar traffic states, for initiating and terminating traffic information aggregation. The framework is validated using a microscopic traffic simulation platform VISSIM and its built-in component object model. Vehicle groups are successfully identified and their average speed and density effectively estimated. The impact of market penetration rate (MPR) is also investigated with a new methodology for performance evaluation under multiple traffic scenarios. Our simulation results show that the proposed framework lends itself better to more congested traffic conditions for any given MPR. With 50% MPR, the framework is able to provide information coverage for at least 37.76% of the simulated roadway facility under various traffic scenarios. This indicates that proposed framework could be useful with an MPR as low as 50%. Even with an MRP of 20%, the coverage ratio, under relatively congested traffic, can still reach around 58.82%. The framework is able to provide accurate speed estimation at high spatial resolution for the simulated roadway facility. The maximum relative error is under 10% for relatively congested traffic even with MPR as low as 20%. When there is a wider range of speed distribution (less congested traffic), the worst-case maximum relative error is still under 15% when MPR= 20 % . The density estimation is more sensitive to MPR, and is more accurate under low demand and high MPR scenarios. As expected, the accuracy of both speed and density estimation increases with MPR for any given traffic scenario.


      PubDate: 2016-06-29T22:58:25Z
       
  • An inference engine for smartphones to preprocess data and detect
           stationary and transportation modes
    • Abstract: Publication date: August 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 69
      Author(s): Hamid Reza Eftekhari, Mehdi Ghatee
      A smartphone can be utilized as a cost-effective device for the purposes of intelligent transportation system. To detect the movement and the stationary statuses in the motorized and non-motorized modes, this study develops a new inference engine, including two sets of rules. The first sets of rules are defined by the related thresholds on the features of smartphone sensors while the second sets are extracted from the human knowledge to improve the results of the first rules. The experimental results reveal that by utilizing Inertial Measurement Unit (IMU) sensors in the proposed inference engine, it is possible to save 40% energy in comparison with the previous research. Moreover, this engine increases the accuracy of the motorized mode detection to 95.2% and determines the stationary states in motorized mode with 97.1% accuracy.


      PubDate: 2016-06-24T22:44:36Z
       
  • Calibration of nonlinear car-following laws for traffic oscillation
           prediction
    • Abstract: Publication date: August 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 69
      Author(s): Christine Rhoades, Xin Wang, Yanfeng Ouyang
      Frequency-domain analysis has been successfully used to (i) predict the amplification of traffic oscillations along a platoon of vehicles with nonlinear car-following laws and (ii) measure traffic oscillation properties (e.g., periodicity, magnitude) from field data. This paper proposes a new method to calibrate nonlinear car-following laws based on real-world vehicle trajectories, such that oscillation prediction (based on the calibrated car-following laws) and measurement from the same data can be compared and validated. This calibration method, for the first time, takes into account not only the driver’s car-following behavior but also the vehicle trajectory’s time-domain (e.g., location, speed) and frequency-domain properties (e.g., peak oscillation amplitude). We use Newell’s car-following model (1961) as an example and calibrate its parameters based on a penalty-based maximum likelihood estimation procedure. A series of experiments using Next Generation Simulation (NGSIM) data are conducted to illustrate the applicability and performance of the proposed approach. Results show that the calibrated car-following models are able to simultaneously reproduce observed driver behavior, time-domain trajectories, and oscillation propagation along the platoon with reasonable accuracy.


      PubDate: 2016-06-24T22:44:36Z
       
  • Optimal recharging strategies for electric vehicle fleets with duration
           constraints
    • Abstract: Publication date: August 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 69
      Author(s): I-Lin Wang, Yiqi Wang, Ping-Cheng Lin
      Electrical vehicles (EVs) have become a popular green transportation means recently because they have lower energy consumption costs and produce less pollution. The success of EVs relies on technologies to extend their driving range, which can be achieved by the good deployment of EV recharging stations. This paper considers a special EV network composed of fixed routes for an EV fleet, where each EV moves along its own cyclic tour of depots. By setting up a recharging station on a depot, an EV can recharge its battery for no longer than a pre-specified duration constraint. We seek an optimal deployment of recharging stations and an optimal recharging schedule for each EV such that all EVs can continue their tours in the planning horizon with minimum total costs. To solve this difficult location problem, we first propose a mixed integer program (MIP) formulation and then derive four new valid inequalities to shorten the solution time. Eight MIP models, which were created by adding different combinations of the four valid inequalities to the basic model, have been implemented to test their individual effectiveness and synergy over twelve randomly generated EV networks. Valuable managerial insights into the usage of valid inequalities and the relations between the battery capacity and the total costs, number of recharging facilities to be installed, and running time are analyzed.


      PubDate: 2016-06-20T22:38:39Z
       
  • Operational analysis of the contraflow left-turn lane design at signalized
           intersections in China
    • Abstract: Publication date: August 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 69
      Author(s): Jiaming Wu, Pan Liu, Zong Z. Tian, Chengcheng Xu
      The primary objective of the study was to evaluate the impacts of an unconventional left-turn treatment called contraflow left-turn lane (CLL) on the operational performance of left-turn movement at signalized intersections. An analytical model was developed for estimating the capacity of left-turn movement at signalized intersections with the CLL design. The capacity model was calibrated and validated using field data collected at six approaches at five signalized intersections in the city of Handan, China. The results of field data analyses showed that the use of CLL design improved the capacity of left-turn movements. However, the capacity gains with the CLL design were quite stochastic considering the randomness in the arrivals of left-turning vehicles. Analytical delay models were proposed for estimating the delay to left-turning vehicles at intersections with the CLL design. A procedure was also proposed for optimizing the location of the upstream median opening and the green interval of the pre-signal. Simulation analyses were conducted to compare the delay experienced by the left-turning and through vehicles at signalized intersections with the conventional left-turn lane, the CLL and another unconventional left-turn treatment entitled “tandem design”. The results showed that both CLL and tandem designs outperformed conventional left-turn lane design; and the CLL design generated less delay to both the left-turning and through vehicles as compared with the tandem design.


      PubDate: 2016-06-20T22:38:39Z
       
  • Updating origin–destination matrices with aggregated data of GPS
           traces
    • Abstract: Publication date: August 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 69
      Author(s): Qian Ge, Daisuke Fukuda
      The practice of estimating origin–destination (OD) demand usually requires large-scale travel surveys. To reduce the cost and time spent on surveys, individual trajectory data obtained from mobile devices has been used as an alternative dataset since the last two decades for OD estimation but also constrained in practice in some countries. To estimate OD matrices while protecting privacy, this study uses aggregated data of mobile phone traces to estimate work-related trips. The proposed approach is a sequential updater based on the maximum entropy principle. Trip production and attraction are firstly calculated by a non-linear programming problem followed by a matrix fitting problem to distribute trips to each OD pair. Numerical study shows that updated values are much closer to the synthesize real values than the referred ones. The case study in Tokyo further demonstrates that the proposed updating approach can track the change of travel pattern.


      PubDate: 2016-06-20T22:38:39Z
       
  • Global convergence of the trial-and-error method for the traffic-restraint
           congestion-pricing scheme with day-to-day flow dynamics
    • Abstract: Publication date: August 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 69
      Author(s): Min Xu, Qiang Meng, Zhongxiang Huang
      The traffic-restraint congestion-pricing scheme (TRCPS) aims to maintain traffic flow within a desirable threshold for some target links by levying the appropriate link tolls. In this study, we propose a trial-and-error method using observed link flows to implement the TRCPS with the day-to-day flow dynamics. Without resorting to the origin–destination (O–D) demand functions, link travel time functions and value of time (VOT), the proposed trial-and-error method works as follows: tolls for the traffic-restraint links are first implemented each time (trial) and they are subsequently updated using observed link flows in a disequilibrium state at any arbitrary time interval. The trial-and-error method has the practical significance because it is necessary only to observe traffic flows on those tolled links and it does not require to wait for the network flow pattern achieving the user equilibrium (UE) state. The global convergence of the trial-and-error method is rigorously demonstrated under mild conditions. We theoretically show the viability of the proposed trial-and-error method, and numerical experiments are conducted to evaluate its performance. The result of this study, without doubt, enhances the confidence of practitioners to adopt this method.


      PubDate: 2016-06-20T22:38:39Z
       
  • Multiple-phase train trajectory optimization with signalling and
           operational constraints
    • Abstract: Publication date: August 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 69
      Author(s): Pengling Wang, Rob M.P. Goverde
      The train trajectory optimization problem aims at finding the optimal speed profiles and control regimes for a safe, punctual, comfortable, and energy-efficient train operation. This paper studies the train trajectory optimization problem with consideration of general operational constraints as well as signalling constraints. Operational constraints refer to time and speed restrictions from the actual timetable, while signalling constraints refer to the influences of signal aspects and automatic train protection on train operation. A railway timetable provides each train with a train path envelope, which consists of a set of positions on the route with a specified target time and speed point or window. The train trajectory optimization problem is formulated as a multiple-phase optimal control model and solved by a pseudospectral method. This model is able to capture varying gradients and speed limits, as well as time and speed constraints from the train path envelope. Train trajectory calculation methods under delay and no-delay situations are discussed. When the train follows the planned timetable, the train trajectory calculation aims at minimizing energy consumption, whereas in the case of delays the train trajectory is re-calculated to track the possibly adjusted timetable with the aim of minimizing delays as well as energy consumption. Moreover, the train operation could be affected by yellow or red signals, which is taken into account in the train speed regulation. For this purpose, two optimization policies are developed with either limited or full information of the train ahead. A local signal response policy ensures that the train makes correct and quick responses to different signalling aspects, while a global green wave policy aims at avoiding yellow signals and thus proceed with all green signals. The method is applied in a case study of two successive trains running on a corridor with various delays showing the benefit of accurate predictive information of the leading train on energy consumption and train delay of the following train.


      PubDate: 2016-06-20T22:38:39Z
       
  • A methodology for identifying similar days in air traffic flow management
           initiative planning
    • Abstract: Publication date: August 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 69
      Author(s): Kenneth D. Kuhn
      This article describes a methodology for selecting days that are comparable in terms of the conditions faced during air traffic flow management initiative planning. This methodology includes the use of specific data sources, specific features of calendar days defined using these data sources, and the application of a specific form of classification and then cluster analysis. The application of this methodology will produce results that enable historical analysis of the use of initiatives and evaluation of the relative success of different courses of action. Several challenges are overcome here including the need to identify the appropriate machine learning algorithms to apply, to quantify the differences between calendar days, to select features describing days, to obtain appropriate raw data, and to evaluate results in a meaningful way. These challenges are overcome via a review of relevant literature, the identification and trial of several useful models and data sets, and careful application of methods. For example, the cluster analysis that ultimately selects sets of similar days uses a distance metric based on variable importance measures from a separate classification model of observed initiatives. The methodology defined here is applied to the New York area, although it could be applied by other researchers to other areas.
      Graphical abstract image

      PubDate: 2016-06-15T13:10:40Z
       
  • Sequencing twin automated stacking cranes in a block at automated
           container terminal
    • Abstract: Publication date: August 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 69
      Author(s): Zhi-Hua Hu, Jiuh-Biing Sheu, Jack Xunjie Luo
      In the considered automated container terminal (ACT) that is designed for Shanghai Yangsha Terminal, two automated stacking cranes (ASCs) are configured for each block and they interact with automated lifting vehicles (ALVs) at the two ends of a block individually. To increase the capacity, container yards with multiple rows of blocks perpendicular to the terminal’s shoreline are considered. To utilize the yard spaces, the twin ASCs are devised to share the same tracks installed at the two sides of a block, while interferences between the ASCs challenge the routing and sequencing operations. To isolate the control and simplify the coordination of the two ASCs, the interference between ASCs is formulated by analyzing the minimal temporal intervals between any two tasks. Three models are then established to sequence the container handling tasks under the minimization of the makespan. An exact algorithm and a genetic algorithm are designed to solve the problem. Numerical experiments show that the algorithms are competitive comparing to on-the-shelf solvers. Practical implications are investigated based on the formulations and experimental results. The managerial implications and technological aspects of applying the formulations and algorithms to practical situations to real-world ACTs are discussed.


      PubDate: 2016-06-15T13:10:40Z
       
  • Integrated solution for anomalous driving detection based on
           BeiDou/GPS/IMU measurements
    • Abstract: Publication date: August 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 69
      Author(s): Rui Sun, Ke Han, Jun Hu, Yanjun Wang, Minghua Hu, Washington Yotto Ochieng
      There has been an increasing role played by Global Navigation Satellite Systems (GNSS) in Intelligent Transportation System (ITS) applications in recent decades. In particular, centimeter/decimetre positioning accuracy is required for some safety related applications, such as lane control, collision avoidance, and intelligent speed assistance. Lane-level Anomalous driving detection underpins these safety-related ITS applications. The two major issues associated with such detection are (1) accessing high accuracy vehicle positioning and dynamic parameters; and (2) extraction of irregular driving patterns from such information. This paper introduces a new integrated framework for detecting lane-level anomalous driving, by combining Global Positioning Systems (GPS), BeiDou, and Inertial Measurement Unit (IMU) with advanced algorithms. Specifically, we use Unscented Particle Filter (UPF) to perform data fusion with different positioning sources. The detection of different types of Anomalous driving is achieved based on the application of a Fuzzy Inference System (FIS) with a newly introduced velocity-based indicator. The framework proposed in this paper yield significantly improved accuracy in terms of positioning and Anomalous driving detection compared to state-of-the-art, while offering an economically viable solution for performing these tasks.


      PubDate: 2016-06-15T13:10:40Z
       
  • Transit signal priority accommodating conflicting requests under Connected
           Vehicles technology
    • Abstract: Publication date: August 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 69
      Author(s): Jia Hu, Byungkyu Brian Park, Young-Jae Lee
      In this research, a person-delay-based optimization method is proposed for an intelligent Transit Signal Priority (TSP) logic that resolves multiple conflicting TSP requests at an isolated intersection. This TSP with Connected Vehicles accommodating Conflicting Requests (TSPCV-CR) overcomes the challenge bore by the conventional “first come first serve” strategy and presents significant improvement on bus service performance. The feature of TSPCV-CR includes green time re-allocation, simultaneous multiple buses accommodation, and signal-transit coordination. These features help maximize the transit TSP service rate and minimize adverse effect on competing travel directions. The TSPCV-CR is also designed to be conditional. That is, TSP is granted only when the bus is behind schedule and the grant of TSP causes no extra total person delay. The optimization is formulated as a Binary Mixed Integer Linear Program (BMILP) which is solved by standard branch-and-bound routine. Minimizing per person delay is the objective of the optimization model. The logic developed in this research is evaluated using both analytical and microscopic traffic simulation approaches. Both analytical tests and simulation evaluations compared three scenarios: without TSP (NTSP), conventional TSP (CTSP), and TSP with Connected Vehicles that resolves Conflicting Requests (TSPCV-CR). The measures of effectiveness used include bus delay and total travel time of all travelers. The performance of TSPCV-CR is compared against conventional TSP (CTSP) under four congestion levels and three different conflicting scenarios. The results show that the TSPCV-CR greatly reduces bus delay at signalized intersection for all congestion levels and conflicting scenarios considered. Simulation based evaluation results show that the TSPCV-CR logic reduces average bus delay between 5% and 48% compared to the conventional TSP. The range of improvement corresponding to the four different v/c ratios tested, which are 0.5, 0.7, 0.9 and 1.0, respectively. No statistically significant negative effects are observed.


      PubDate: 2016-06-15T13:10:40Z
       
  • Evacuation planning for disaster responses: A stochastic programming
           framework
    • Abstract: Publication date: August 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 69
      Author(s): Li Wang, Lixing Yang, Ziyou Gao, Shukai Li, Xuesong Zhou
      Some disasters such as earthquakes, floods and hurricanes may result in evacuation for people in an affected area. This paper focuses on finding the a priori evacuation plans by considering side constraints and scenario-based stochastic link travel times and capacities. Hence a stochastic programming framework is developed so as to provide a reorganization of the traffic routing for a disaster response. Considering the different preferences of decision-makers, three evaluation criteria are introduced to formulate the objective function. Crisp linear equivalents for different evacuation strategies are further deduced to simplify solution methodologies. A heuristic algorithm combining the Lagrangian relaxation-based approach with K-shortest path techniques is designed to solve the expected disutility model. The experimental results indicate that the algorithm can solve large-scale instances for the problem of interest efficiently and effectively.


      PubDate: 2016-06-15T13:10:40Z
       
  • Influence of priority taking and abstaining at single-lane roundabouts
           using cellular automata
    • Abstract: Publication date: August 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 69
      Author(s): Nathan P. Belz, Lisa Aultman-Hall, James Montague
      Existing roundabout simulation models fail to consider all types of driver behavior which compromises their accuracy and ability to accurately evaluate roundabout performance. Further, these non-compliant driver behaviors, including priority taking and priority abstaining, are inconsistent with existing traffic flow theories. In this paper, a new cellular automata model, C.A.Rsim, is developed and calibrated with field data from five single-lane roundabouts in four northeastern states. Model results indicate that approximately 20% of the individuals in the driver population are inclined to priority taking and approximately 20% are inclined to priority abstaining behavior, though the observed levels of these types of behavior are naturally lower and vary with traffic volume. The model results also corroborate other research indicating that current models can overestimate capacity at higher circulating volumes, possibly a result of the jamming effect produced by priority taking behavior. The reduction in priority abstaining behavior, which is observed at older roundabouts, significantly reduces delay and queue length in certain traffic volumes. C.A.Rsim is also more parsimonious than many existing microsimulation models. These results provide insight on how variations in conflicting flow (i.e., traffic volume and turning movement balance) impact the amount of observed non-compliant behavior.


      PubDate: 2016-06-15T13:10:40Z
       
  • A double standard model for allocating limited emergency medical service
           vehicle resources ensuring service reliability
    • Abstract: Publication date: August 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 69
      Author(s): Yi Liu, Zongzhi Li, Jingxian Liu, Harshingar Patel
      This paper introduces a new double standard model (DSM), along with a genetic algorithm (GA), for solving the emergency medical service (EMS) vehicle allocation problem that ensures acceptable service reliability with limited vehicle resources. Without loss of generality, the model is formulated to address emergency services to human injuries caused by vehicle crashes at intersections within an urban street network. The EMS fleet consists of basic life support (BLS) and advanced life support (ALS) vehicles suited for treating crashes with different severity levels within primary and secondary service coverage standards corresponding to extended response times. The model ensures that all demand sites are covered by at least one EMS vehicle within the secondary standard and a portion of which also meets the service reliability requirement. In addition, a portion of demand sites can be covered by at least one of each type of EMS vehicles within the primary standard. Meanwhile, it aims to achieve maximized coverage of demand sites within the primary standard that complies with the required service reliability. A computational experiment is conducted using 2004–2010 data on top two hundred high crash intersections in the city of Chicago as demand sites for model application. With an EMS fleet size of 15 BLS and 60 ALS ambulances maintained by the Chicago Fire Department, at best 92.4–95.5% of demand could be covered within the secondary standard at 90% of service reliability; and 65.5–68.4% of high severity demand and 50.2–54.5 low severity demand could be covered within the primary standard at 90% of service reliability. The model can help optimize EMS vehicle allocation in urban areas.


      PubDate: 2016-06-15T13:10:40Z
       
  • Integrated multi-track station layout design and train scheduling models
           on railway corridors
    • Abstract: Publication date: August 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 69
      Author(s): Jianguo Qi, Lixing Yang, Yuan Gao, Shukai Li, Ziyou Gao
      The dwelling capacity of the station (mainly determined by its multi-track layout) is a practically significant factor to influence the quality of the train schedules, especially in a busy railway corridor with heterogeneous trains and complex operations. To improve the passing capacity and transportation efficiency, this paper focuses on a network design problem over a railway corridor, in which some critical stations are considered to enlarge the number of siding tracks or platforms within the budget constraints. To evaluate the quality of design strategies, the construction cost and total travel time in the corresponding optimal train schedule are adopted as evaluation indexes. Based on two specific modeling methodologies, two types of optimization models are particularly formulated with different considerations. One is a single-level linear mixed-integer programming (S-LMIP) model based on the space–time network representation method; the other is a bi-level programming model associated with the platform choice-based method, where the upper level of the proposed model aims to design new siding tracks/platforms in the candidate stations, and the lower level is a train scheduling model with assigning the tracks for each train at each station. The commercial software GAMS with CPLEX solver and local searching based heuristic with integrated CPLEX solver are respectively employed to solve the near-optimal solutions for these two types of models. Finally, two sets of examples, in which a sample railway corridor and the Wuhan–Guangzhou high-speed railway corridor are adopted as the experimental environments, are implemented to illustrate the performance and effectiveness of the proposed approaches.


      PubDate: 2016-06-15T13:10:40Z
       
  • Optimal planning of liquefied natural gas deliveries
    • Abstract: Publication date: August 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 69
      Author(s): Sara Al-Haidous, Mohamed Kais Msakni, Mohamed Haouari
      We investigate the problem of designing an optimal annual delivery plan for Liquefied Natural Gas (LNG). This problem requires determining the long-term cargo delivery dates and the assignment of vessels to the cargoes while accommodating several constraints, including berth availability, liquefaction terminal inventory, planned maintenance, and bunkering requirements. We describe a novel mixed-integer programming formulation that captures important industry requirements and constraints with the objective of minimizing the vessel fleet size. A peculiar property of the proposed formulation is that it includes a polynomial number of variables and constraints and is, in our experience, computationally tractable for large problem instances using a commercial solver. Extensive computational runs demonstrate the efficacy of the proposed model for real instances provided by a major energy company that involve up to 118 cargoes and a 373-day planning horizon.


      PubDate: 2016-06-15T13:10:40Z
       
  • Modeling chain collisions in vehicular networks with variable penetration
           rates
    • Abstract: Publication date: August 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 69
      Author(s): Daxin Tian, Jianshan Zhou, Yunpeng Wang, Zhengguo Sheng, Haiying Xia, Zhenguo Yi
      The vehicular ad hoc network has great potential in improving traffic safety. One of the most important and interesting issues in the research community is the safety evaluation with limited penetration rates of vehicles equipped with inter-vehicular communications. In this paper, a stochastic model is proposed for analyzing the vehicle chain collisions. It takes into account the influences of different penetration rates, the stochastic nature of inter-vehicular distance distribution, and the different kinematic parameters related to driver and vehicle. The usability and accuracy of this model is tested and proved by comparative experiments with Monte Carlo simulations. The collision outcomes of a platoon in different penetration rates and traffic scenarios are also analyzed based on this model. These results are useful to provide theoretical insights into the safety control of a heterogeneous platoon.


      PubDate: 2016-06-15T13:10:40Z
       
  • Online distributed cooperative model predictive control of energy-saving
           trajectory planning for multiple high-speed train movements
    • Abstract: Publication date: August 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 69
      Author(s): Xihui Yan, Baigen Cai, Bin Ning, Wei ShangGuan
      The cooperative energy-efficient trajectory planning for multiple high-speed train movements is considered in this paper. We model all the high-speed trains as the agents that can communicate with others and propose a local trajectory planning control model using the Model Predictive Control (MPC) theory. After that we design an online distributed cooperative optimization algorithm for multiple train trajectories planning, under which each train agent can regulate the trajectory planning procedure to save energy using redundancy trip time through tuning ACO’s heuristic information parameter. Compared to the existing literature, the vital distinctions of our work lies not only on the online cooperative trajectory planning but also on the distributed mechanism for multiple high-speed trains. Experimental studies are given to illustrate the effectiveness of the proposed methods with the practical operational data of Wuhan-Guangzhou High-speed Railway in China.


      PubDate: 2016-06-15T13:10:40Z
       
  • Modeling duration choice in space–time multi-state supernetworks for
           individual activity-travel scheduling
    • Abstract: Publication date: August 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 69
      Author(s): Feixiong Liao
      Multi-state supernetworks have been advanced recently for modeling individual activity-travel scheduling decisions. The main advantage is that multi-dimensional choice facets are modeled simultaneously within an integral framework, supporting systematic assessments of a large spectrum of policies and emerging modalities. However, duration choice of activities and home-stay has not been incorporated in this formalism yet. This study models duration choice in the state-of-the-art multi-state supernetworks. An activity link with flexible duration is transformed into a time-expanded bipartite network; a home location is transformed into multiple time-expanded locations. Along with these extensions, multi-state supernetworks can also be coherently expanded in space–time. The derived properties are that any path through a space–time supernetwork still represents a consistent activity-travel pattern, duration choice are explicitly associated with activity timing, duration and chain, and home-based tours are generated endogenously. A forward recursive formulation is proposed to find the optimal patterns with the optimal worst-case run-time complexity. Consequently, the trade-off between travel and time allocation to activities and home-stay can be systematically captured.


      PubDate: 2016-06-15T13:10:40Z
       
 
 
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