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TRANSPORTATION (99 journals)

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Journal Cover   Transportation Research Part C: Emerging Technologies
  [SJR: 1.943]   [H-I: 55]   [16 followers]  Follow
    
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 0968-090X
   Published by Elsevier Homepage  [2812 journals]
  • Traffic flow optimisation in presence of vehicle automation and
           communication systems – Part II: Optimal control for multi-lane
           motorways
    • Abstract: Publication date: Available online 29 June 2015
      Source:Transportation Research Part C: Emerging Technologies
      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: 2015-07-03T13:00:04Z
       
  • An agent-based choice model for travel mode and departure time and its
           case study in Beijing
    • Abstract: Publication date: Available online 27 June 2015
      Source:Transportation Research Part C: Emerging Technologies
      Author(s): Mingqiao Zou , Meng Li , Xi Lin , Chenfeng Xiong , Chao Mao , Cheng Wan , Ke Zhang , Jiaying Yu
      Aiming to alleviate traffic jams, many traffic management strategies/policies are adopted to nudge travelers to re-arrange their departure time or switch from driving to public transit or non-motorized mode. Analytical travel behavior model is needed to predict travelers’ departure time choice and mode switch under such strategies. In this paper, we developed an agent-based model for travellers’ choices of mode and departure time. Departing from the traditional utility maximization theory, this model focuses on the decision-making process based on imperfect information, bounded and distinctive rationalities. In the modeling framework, travelers accumulate experiences and update their spatial and temporal knowledge through a Bayesian learning process. Before making a trip, travelers decide whether to search for alternative departure time and/or travel mode according to their expected search gain and cost. When an additional search happens, travelers decide whether or not to switch to the new departure time and travel mode according to a series of decision conditions. Both the search and decision processes are represented by production (if–then) rules derived from a joint revealed/stated-preference survey data collected in Beijing. Then the agent-based model is applied to evaluate congestion charge policies with various demand scenarios in the 2nd ring road of Beijing. Results suggest that the model can display the peak spreading and mode switch process practically.


      PubDate: 2015-07-03T13:00:04Z
       
  • Supporting eco-driving
    • Abstract: Publication date: Available online 29 June 2015
      Source:Transportation Research Part C: Emerging Technologies
      Author(s): Samantha L. Jamson , Rino Brouwer , Philipp Seewald



      PubDate: 2015-07-03T13:00:04Z
       
  • W-SPSA in practice: Approximation of weight matrices and calibration of
           traffic simulation models
    • Abstract: Publication date: Available online 30 June 2015
      Source:Transportation Research Part C: Emerging Technologies
      Author(s): Constantinos Antoniou , Carlos Lima Azevedo , Lu Lu , Francisco Pereira , Moshe Ben-Akiva
      The development and calibration of complex traffic models demands parsimonious techniques, because such models often involve hundreds of thousands of unknown parameters. The Weighted Simultaneous Perturbation Stochastic Approximation (W-SPSA) algorithm has been proven more efficient than its predecessor SPSA (Spall, 1998), particularly in situations where the correlation structure of the variables is not homogeneous. This is crucial in traffic simulation models where effectively some variables (e.g. readings from certain sensors) are strongly correlated, both in time and space, with some other variables (e.g. certain OD flows). In situations with reasonably sized traffic networks, the difference is relevant considering computational constraints. However, W-SPSA relies on determining a proper weight matrix (W) that represents those correlations, and such a process has been so far an open problem, and only heuristic approaches to obtain it have been considered. This paper presents W-SPSA in a formally comprehensive way, where effectively SPSA becomes an instance of W-SPSA, and explores alternative approaches for determining the matrix W. We demonstrate that, relying on a few simplifications that marginally affect the final solution, we can obtain W matrices that considerably outperform SPSA. We analyse the performance of our proposed algorithm in two applications in motorway networks in Singapore and Portugal, using a dynamic traffic assignment model and a microscopic traffic simulator, respectively.


      PubDate: 2015-07-03T13:00:04Z
       
  • 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
       
  • Stochastic eco-routing in a signalized traffic network
    • Abstract: Publication date: Available online 24 June 2015
      Source:Transportation Research Part C: Emerging Technologies
      Author(s): Jie Sun , Henry X. Liu
      In this paper, an eco-routing algorithm is developed for vehicles in a signalized traffic network. The proposed method incorporates a microscopic vehicle emission model into a Markov decision process (MDP). Instead of using GPS-based vehicle trajectory data, which are used by many existing eco-routing algorithm, high resolution traffic data including vehicle arrival and signal status information are used as primary inputs. The proposed method can work with any microscopic vehicle model that uses vehicle trajectories as inputs and gives related emission rates as outputs. Furthermore, a constrained eco-routing problem is proposed to deal with the situation where multiple costs present. This is done by transferring the original MDP based formulation to a linear programming formulation. Besides the primary cost, additional costs are considered as constraints. Two numerical examples are given using the field data obtained from City of Pasadena, California, USA. The eco-routing algorithm for single objective is compared against the traditional shortest path algorithm, Dijkstra’s algorithm. Average reductions of CO emission around 20% are observed.


      PubDate: 2015-06-27T11:11:54Z
       
  • Data-driven linear decision rule approach for distributionally robust
           optimization of on-line signal control
    • Abstract: Publication date: Available online 25 June 2015
      Source:Transportation Research Part C: Emerging Technologies
      Author(s): Hongcheng Liu , Ke Han , Vikash V. Gayah , Terry L. Friesz , Tao Yao
      We propose a two-stage, on-line signal control strategy for dynamic networks using a linear decision rule (LDR) approach and a distributionally robust optimization (DRO) technique. The first (off-line) stage formulates a LDR that maps real-time traffic data to optimal signal control policies. A DRO problem is solved to optimize the on-line performance of the LDR in the presence of uncertainties associated with the observed traffic states and ambiguity in their underlying distribution functions. We employ a data-driven calibration of the uncertainty set, which takes into account historical traffic data. The second (on-line) stage implements a very efficient linear decision rule whose performance is guaranteed by the off-line computation. We test the proposed signal control procedure in a simulation environment that is informed by actual traffic data obtained in Glasgow, and demonstrate its full potential in on-line operation and deployability on realistic networks, as well as its effectiveness in improving traffic.


      PubDate: 2015-06-27T11:11:54Z
       
  • Parking space management via dynamic performance-based pricing
    • Abstract: Publication date: Available online 25 June 2015
      Source:Transportation Research Part C: Emerging Technologies
      Author(s): Daniel Mackowski , Yun Bai , Yanfeng Ouyang
      In congested urban areas, it remains a pressing challenge to reduce unnecessary vehicle circling for parking while at the same time maximize parking space utilization. In observance of new information technologies that have become readily accessible to drivers and parking agencies, we develop a dynamic non-cooperative bi-level model (i.e. Stackelberg leader–follower game) to set parking prices in real-time for effective parking access and space utilization. The model is expected to fit into an integrated parking pricing and management system, where parking reservations and transactions are facilitated by sensing and informatics infrastructures, that ensures the availability of convenient spaces at equilibrium market prices. It is shown with numerical examples that the proposed dynamic parking pricing model has the potential to virtually eliminate vehicle circling for parking, which results in significant reduction in adverse socioeconomic externalities such as traffic congestion and emissions.


      PubDate: 2015-06-27T11:11:54Z
       
  • 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
       
  • Marginal cost congestion pricing based on the network fundamental diagram
    • Abstract: Publication date: July 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 56
      Author(s): M.D. Simoni , A.J. Pel , R.A. Waraich , S.P. Hoogendoorn
      Congestion pricing schemes have been traditionally derived based on analytical representations of travel demand and traffic flows, such as in bottleneck models. A major limitation of these models, especially when applied to urban networks, is the inconsistency with traffic dynamics and related phenomena such as hysteresis and the capacity drop. In this study we propose a new method to derive time-varying tolling schemes using the concept of the Network Fundamental Diagram (NFD). The adopted method is based on marginal cost pricing, while it also enables to account realistically for the dynamics of large and heterogeneous traffic networks. We derive two alternative cordon tolls using network-aggregated traffic flow conditions: a step toll that neglects the spatial distribution of traffic by simply associating the marginal costs of any decrease in production within the NFD to the surplus of traffic; and a step toll that explicitly accounts for how network performance is also influenced by the spatial variance in a 3D-NFD. This pricing framework is implemented in the agent-based simulation model MATSim and applied to a case study of the city of Zurich. The tolling schemes are compared with a uniform toll, and they highlight how the inhomogeneous distribution of traffic may compromise the effectiveness of cordon tolls.


      PubDate: 2015-06-24T12:55:31Z
       
  • Categorizing bicycling environments using GPS-based public bicycle speed
           data
    • Abstract: Publication date: July 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 56
      Author(s): Shinhye Joo , Cheol Oh , Eunbi Jeong , Gunwoo Lee
      A promising alternative transportation mode to address growing transportation and environmental issues is bicycle transportation, which is human-powered and emission-free. To increase the use of bicycles, it is fundamental to provide bicycle-friendly environments. The scientific assessment of a bicyclist’s perception of roadway environment, safety and comfort is of great interest. This study developed a methodology for categorizing bicycling environments defined by the bicyclist’s perceived level of safety and comfort. Second-by-second bicycle speed data were collected using global positioning systems (GPS) on public bicycles. A set of features representing the level of bicycling environments was extracted from the GPS-based bicycle speed and acceleration data. These data were used as inputs for the proposed categorization algorithm. A support vector machine (SVM), which is a well-known heuristic classifier, was adopted in this study. A promising rate of 81.6% for correct classification demonstrated the technical feasibility of the proposed algorithm. In addition, a framework for bicycle traffic monitoring based on data and outcomes derived from this study was discussed, which is a novel feature for traffic surveillance and monitoring.


      PubDate: 2015-06-24T12:55:31Z
       
  • Analyzing passenger train arrival delays with support vector regression
    • Abstract: Publication date: July 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 56
      Author(s): Nikola Marković , Sanjin Milinković , Konstantin S. Tikhonov , Paul Schonfeld
      We propose machine learning models that capture the relation between passenger train arrival delays and various characteristics of a railway system. Such models can be used at the tactical level to evaluate effects of various changes in a railway system on train delays. We present the first application of support vector regression in the analysis of train delays and compare its performance with the artificial neural networks which have been commonly used for such problems. Statistical comparison of the two models indicates that the support vector regression outperforms the artificial neural networks. Data for this analysis are collected from Serbian Railways and include expert opinions about the influence of infrastructure along different routes on train arrival delays.


      PubDate: 2015-06-24T12:55:31Z
       
  • Air cargo operations: Literature review and comparison with practices
    • Abstract: Publication date: July 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 56
      Author(s): Bo Feng , Yanzhi Li , Zuo-Jun Max Shen
      This study reviews the literature on air cargo operations and compares theoretical studies with the practical problems of airlines, freight forwarders, and terminal service providers. In particular, we review studies in which mathematical models were used to identify the essential characteristics of air cargo operations, such as the intrinsic differences from passenger operations, and to explore the service processes in air cargo operations. The typical models used in previous studies are summarized. We then highlight the insightful findings from an industrial interview and present the gaps between previous research and practical realities. We finally discuss the new research opportunities of air cargo operations according to the gaps.


      PubDate: 2015-06-24T12:55:31Z
       
  • Coordinated cruise control for high-speed train movements based on a
           multi-agent model
    • Abstract: Publication date: July 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 56
      Author(s): Shukai Li , Lixing Yang , Ziyou Gao
      This paper investigates the coordinated cruise control strategy for multiple high-speed trains’ movement. The motion of an ordered set of high-speed trains running on a railway line is modeled by a multi-agent system, in which each train communicates with its neighboring trains to adjust its speed. By using the potential fields and LaSalles invariance principle, we design a new coordinated cruise control strategy for each train based on the neighboring trains’ information, under which each train can track the desired speed, and the headway distances between any two neighboring trains are stabilized in a safety range. Numerical examples are given to illustrate the effectiveness of the proposed methods.


      PubDate: 2015-06-24T12:55:31Z
       
  • Efficiency of a highway use reservation system for morning commute
    • Abstract: Publication date: July 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 56
      Author(s): Wei Liu , Hai Yang , Yafeng Yin
      This paper examines the design and efficiency of a highway use reservation system where commuters need reservations to access a highway facility at specific times. We show that, by accommodating reservation requests to the level that the highway capacity allows, traffic congestion can be relieved. Generally, a more differentiated design of the reservation system yields a higher reduction of travel cost and thus achieves a higher efficiency. The efficiency bound of the system is established. We also show that braking or tactical waiting behaviors of drivers would cause a loss of efficiency, which thus need be proactively accommodated. Given that user heterogeneity cause further loss of efficiency, we explore how two specific types of user heterogeneity affect the system efficiency. Auction-based reservation is then proposed to mitigate the efficiency loss.


      PubDate: 2015-06-24T12:55:31Z
       
  • Application of Lagrangian relaxation approach to α-reliable path
           finding in stochastic networks with correlated link travel times
    • Abstract: Publication date: July 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 56
      Author(s): Weiliang Zeng , Tomio Miwa , Yukiko Wakita , Takayuki Morikawa
      This study investigates the important problem of determining a reliable path in a stochastic network with correlated link travel times. First, the distribution of path travel time is quantified by using trip records from GPS probe vehicles. Second, the spatial correlation of link travel time is explicitly considered by using a correlation coefficient matrix, which is incorporated into the α-reliable path problem by Cholesky decomposition. Third, the Lagrangian relaxation based framework is used to handle the α-reliable path problem, by which the intractable problem with a non-linear and non-additive structure can be decomposed into several easy-to-solve problems. Finally, the path-finding performance of this approach is tested on a real-world network. The results show that 15 iterations of calculation can yield a small relative gap between upper and lower bounds of the optimal solution and the average running time is about 5s for most OD settings. The applicability of α-reliable path finding is validated by a case study.
      Graphical abstract image

      PubDate: 2015-06-24T12:55:31Z
       
  • Flow-based accessibility measurement: The Place Rank approach
    • Abstract: Publication date: July 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 56
      Author(s): Guihua Wang , Yuanguang Zhong , Chung-Piaw Teo , Qizhang Liu
      In this paper, we empirically test the viability of a flow-based approach as an alternative to transport accessibility measurement. To track where commuters travel from and to (but not commute times), we use transactional smartcard data from residents in Singapore to construct the (daily) spatial network of trips generated. We use the Place Rank method to demonstrate the viability of the flow-based approach to study accessibility. We compute the Place Rank of each of 44 planning areas in Singapore. Interestingly, even though the spatial network is constructed using only origin–destination information, we find that the travel time of the trips out of each planning area generally decreases as the area’s Place Rank increases. The same is also the case for in-vehicle time, number of transfers in the network and transfer time. This shows that a flow-based approach can be used to measure the notion of accessibility, which is traditionally assessed using travel time information in the system. We also compare Place Rank with other indicators, namely, bus stop density, eigenvector centrality, clustering coefficient and typographical coefficient to evaluate an area’s accessibility. The results show that these indicators are not as effective as the Place Rank method.


      PubDate: 2015-06-24T12:55:31Z
       
  • The fleet renewal problem with regional emission limitations: Case study
           from Roll-on/Roll-off shipping
    • Abstract: Publication date: July 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 56
      Author(s): Øyvind S. Patricksson , Kjetil Fagerholt , Jørgen G. Rakke
      In this paper, the maritime fleet renewal problem (MFRP) is extended to include regional limitations in the form of emission control areas. The motivation for including this aspect is that strengthening of emission regulations in such areas is expected to be challenging for deep sea shipping in the years to come. In the proposed model, various means to cope with these stricter emission regulations are evaluated for new vessels, and the possibility of upgrading existing vessels with new emission reduction technology is introduced. We consider future fuel prices to be important for the problem, and have chosen to treat them as uncertain, and thus, a stochastic programming model is chosen. A fleet renewal problem faced by the liner shipping operator Wallenius Wilhelmsen Logistics, concerning whether to use low sulphur fuel or have an exhaust gas scrubber system installed to comply with sulphur regulation in emission control areas from 2015, is used as a case study. Furthermore, tests show that the savings from including the aspect of emission control areas in the MFRP are substantial.


      PubDate: 2015-06-24T12:55:31Z
       
  • Assessing the viability of enabling a round-trip carsharing system to
           accept one-way trips: Application to Logan Airport in Boston
    • Abstract: Publication date: July 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 56
      Author(s): Diana Jorge , Cynthia Barnhart , Gonçalo Homem de Almeida Correia
      Although one-way carsharing is suitable for more trip purposes than round-trip carsharing, many companies in the world operate only in the round-trip market. In this paper, we develop a method that optimizes the design of a one-way carsharing service between selected origin–destination pairs of an existing round-trip carsharing system. The goal is to supplement the established round-trip services with new one-way services and increase profitability. We develop an integer programming model to select the set of new one-way services and apply it to the case study of Boston, USA, considering only trips with one endpoint at a station in the round-trip Zipcar service network and the other endpoint at Logan Airport. The airport was chosen as a necessary endpoint for a one-way service because it is a very significant trip generator for which the round-trip carsharing is not suitable. Results show that these supplemental one-way services could be profitable. Enabling relocation operations between the existing round-trip stations and the Airport greatly improves the demand effectively satisfied, leads to an acceptable airport station size (in terms of the number of parking spots required), and is profitable; however, these benefits come with the need to manage relocation operations.


      PubDate: 2015-06-24T12:55:31Z
       
  • The concept and impact analysis of a flexible mobility on demand system
    • Abstract: Publication date: July 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 56
      Author(s): Bilge Atasoy , Takuro Ikeda , Xiang Song , Moshe E. Ben-Akiva
      This paper introduces an innovative transportation concept called Flexible Mobility on Demand (FMOD), which provides personalized services to passengers. FMOD is a demand responsive system in which a list of travel options is provided in real-time to each passenger request. The system provides passengers with flexibility to choose from a menu that is optimized in an assortment optimization framework. For operators, there is flexibility in terms of vehicle allocation to different service types: taxi, shared-taxi and mini-bus. The allocation of the available fleet to these three services is carried out dynamically so that vehicles can change roles during the day. The FMOD system is built based on a choice model and consumer surplus is taken into account in order to improve passenger satisfaction. Furthermore, profits of the operators are expected to increase since the system adapts to changing demand patterns. In this paper, we introduce the concept of FMOD and present preliminary simulation results. It is shown that the dynamic allocation of the vehicles to different services provides significant benefits over static allocation. Furthermore, it is observed that the trade-off between consumer surplus and operator’s profit is critical. The optimization model is adapted in order to take into account this trade-off by controlling the level of passenger satisfaction. It is shown that with such control mechanisms FMOD provides improved results in terms of both profit and consumer surplus.


      PubDate: 2015-06-24T12:55:31Z
       
  • A novel three-step procedure to forecast the inspection volume
    • Abstract: Publication date: July 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 56
      Author(s): J.J. Ruiz-Aguilar , I.J. Turias , M.J. Jiménez-Come
      The inspection process of freight traffic at Border Inspection Posts (BIPs) generates significant time delays and congestion within the transport system. The use of forecasting methods to anticipate these situations could be a good solution. Traditional methodologies for time series prediction usually consist on: applying single techniques, combining these techniques with some others such as clustering techniques or hybridizing single prediction techniques. A novel methodology based on a three-step procedure is proposed in this paper in order to better predict the number of inspections at BIPs, integrating a clustering technique and a hybrid prediction model. Specifically, the seasonal auto-regressive integrated moving averages (SARIMA) is used first to predict the data. Then, self-organizing maps (SOM) decomposes the time series into smaller regions with similar statistical properties. Finally, Artificial Neural Networks (ANNs) are applied in each homogeneous regions to forecast the inspections volume, testing different hybrid approaches based on the inputs of the model. The experimental results show that the performance of inspection prediction can be enhanced by using the novel three-stage procedure, providing relevant information for resource planning and turning into a powerful decision-making tool, not only at the inspection process of seaports or airports, but also in the field of time series prediction.
      Graphical abstract image

      PubDate: 2015-06-24T12:55:31Z
       
  • How comfortable are your cycling tracks? A new method for objective
           bicycle vibration measurement
    • Abstract: Publication date: July 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 56
      Author(s): Michal Bíl , Richard Andrášik , Jan Kubeček
      Cycling comfort consists of several factors. Their relevant values are important in the process of bicycle facility planning. Poor surface pavement quality manifests itself in terms of vibrations of a bicycle. This strongly influences the perception of a cycle track, general cycling comfort and the route choice as well. We introduce dynamic comfort index (DCI) which is capable of objectively describing the vibration properties of surface pavement on a track. The DCI is derived from data gathered when riding a bicycle equipped with a GPS device and an accelerometer. The most common types of devices were selected to make the DCI widely applicable. We tested DCI values on various bicycles and surface pavements. DCI values on individual cycling tracks were compared with the subjective feelings of 43 cyclists via questionnaires. A strong correlation (−0.94) was obtained between the objectively measured DCI values and the subjectively assessed evaluations. This makes the DCI approach transferable to any other environment. This method has been applied to an entire road network within the historical center of the city of Olomouc (Czech Republic). It can further be used by bicycle track administrators to monitor surface quality, by planners to obtain relevant surface pavement values, and by individual cyclists for optimal route choice.


      PubDate: 2015-06-24T12:55:31Z
       
  • Modelling the adoption intention and installation choice of an automotive
           after-market mild-solar-hybridization kit
    • Abstract: Publication date: July 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 56
      Author(s): Stefano de Luca , Roberta Di Pace , Vincenzo Marano
      Despite the recent commercial success of hybrid, plug-in hybrid and electric vehicles their market share is still insufficient to produce either a significant impact on energy consumption on a global basis or a profitable automotive segment. In this context, the possibility of upgrading conventional vehicles to hybrid electric vehicles is gaining increasing interest. To this aim this paper investigated and modelled the intention to install an after-market hybridization solar-kit (HySolarKit) in order to ascertain the main behavioural determinants of the choice process and set up an operational model with which to estimate the market potential of such technology. In particular, two behavioural stages of the choice process were analysed and modelled: (i) the intention to adopt the HySolarKit; (ii) the choice to install the HySolarKit. Both issues were addressed through ad hoc stated preference surveys carried out in two different Italian cities, and through the specification and the calibration of discrete choice models based on the behavioural paradigm of random utility theory. Different modelling solutions (homoscedastic and heteroscedastic) were compared in terms of goodness-of-fit and sensitivity to level-of-service attributes. The results showed the technological potential of the HySolarKit, and that both behavioural stages may be effectively modelled through random utility theory. Estimation results allowed an interpretation of the main determinants of the investigated phenomena, making it possible to quantify the potential effects and the concerns towards such a green solution, and making it possible to draw up operative marketing strategies. In particular, the intention to adopt the kit mainly depends on socio-economic factors as well as activity-related and attitudinal attributes, whereas the probability of installing the kit is greatly affected, to the same extent, by installation cost, the charging cost and the weekly mileage driven.


      PubDate: 2015-06-24T12:55:31Z
       
  • When is big data big enough? Implications of using GPS-based surveys
           for travel demand analysis
    • Abstract: Publication date: July 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 56
      Author(s): Akshay Vij , K. Shankari
      A number of studies in the last decade have argued that Global Positioning Systems (GPS) based survey offer the potential to replace traditional travel diary surveys. GPS-based surveys impose lower respondent burden, offer greater spatiotemporal precision and incur fewer monetary costs. However, GPS-based surveys do not collect certain key inputs required for the estimation of travel demand models, such as the travel mode(s) taken or the trip purpose, relying instead on data-processing procedures to infer this information. This study assesses the impact that errors in inference can have on travel demand models estimated using data from GPS-based surveys and proposes ways in which these errors can be controlled for during both data collection and model estimation. We use simulated datasets to compare performance across different sample sizes, inference accuracies, model complexities and estimation methods. Findings from the simulated datasets are corroborated with real data collected from individuals living in the San Francisco Bay Area, United States. Results indicate that the benefits of using GPS-based surveys will vary significantly, depending upon the sample size of the data, the accuracy of the inference algorithm and the desired complexity of the travel demand model specification. In many cases, gains in the volume of data that can potentially be retrieved using GPS devices are found to be offset by the loss in quality caused by inaccuracies in inference. This study makes the argument that passively collected GPS-based surveys may never entirely replace surveys that require active interaction with study participants.


      PubDate: 2015-06-24T12:55:31Z
       
  • The Integrated Model on Mobile Payment Acceptance (IMMPA): An empirical
           application to public transport
    • Abstract: Publication date: July 2015
      Source:Transportation Research Part C: Emerging Technologies, Volume 56
      Author(s): L. Di Pietro , R. Guglielmetti Mugion , G. Mattia , M.F. Renzi , M. Toni
      This study examines the users’ acceptance and usage of mobile payments, focusing on the mobile ticketing technologies applied in a public transport context. We investigate the main predictors of the intention to use mobile ticketing and the relation between those predictors, considering the prominent literature on users’ technology acceptance background and extending the knowledge through an innovative contribution. The main models of reference in this study are the Technology Acceptance Model (TAM), the Diffusion of Innovation Model (
      DOI ) and the Unified Theory of Acceptance and Use of Technology (UTAUT) model. The new model that we proposed is called the Integrated Model on Mobile Payment Acceptance (IMMPA), and it was designed specifically for mobile payments in the public transport, on the basis of the models previously mentioned. It was developed by mixing the variables of the existing models and adding new ones tailored to the mobile payment/ticketing framework. The theoretical framework was tested using the Structural Equation Models. The results show that the intention to use a technology is affected by the Usefulness, Ease of use and the Security of that technology. Moreover, the Usefulness is simultaneously influenced by the Ease of use, the Compatibility with users’ values and needs and their Attitude towards mobile services. Furthermore, the model confirms the direct relation between the intention to use a technology and its actual usage. The new predictor, that is the Attitude towards mobile services, includes those requirements that every mobile ticketing payment must address in this context: complete information, further information about time and delay, speed of use, intuitive interface, and path customisation. Another new construct detected is the Security, in reference to mobile payment. Because it could represent an obstacle to mobile ticketing distribution, it must be considered by market operators. The originality of the paper addresses the realisation of a new model, the IMMPA, which was specifically designed for mobile payment in the public transport.


      PubDate: 2015-06-24T12:55:31Z
       
  • Probe vehicle-based traffic state estimation method with spacing
           information and conservation law
    • Abstract: Publication date: Available online 16 June 2015
      Source:Transportation Research Part C: Emerging Technologies
      Author(s): Toru Seo , Takahiko Kusakabe
      This paper proposes a method of estimating a traffic state based on probe vehicle data that contain spacing and position of probe vehicles. The probe vehicles were assumed to observe spacing by utilizing an advanced driver assistance system, that has been implemented in practice and is expected to spread in the near future. The proposed method relies on the conservation law of the traffic flow but is independent of a fundamental diagram. The conservation law is utilized for reasonable aggregation of the spacing data to acquire the traffic state, i.e., a flow, density and speed. Its independence from a fundamental diagram means that the proposed method does not require predetermined nor exogenous assumptions with regard to the traffic flow model parameters. The proposed method was validated through a simulation experiment under ideal conditions and a field experiment conducted under actual traffic conditions; and empirical characteristics of the proposed method were investigated.


      PubDate: 2015-06-24T12:55:31Z
       
  • A model of bus bunching under reliability-based passenger arrival patterns
    • Abstract: Publication date: Available online 16 June 2015
      Source:Transportation Research Part C: Emerging Technologies
      Author(s): Achille Fonzone , Jan-Dirk Schmöcker , Ronghui Liu
      If bus service departure times are not completely unknown to the passengers, non-uniform passenger arrival patterns can be expected. We propose that passengers decide their arrival time at stops based on a continuous logit model that considers the risk of missing services. Expected passenger waiting times are derived in a bus system that allows also for overtaking between bus services. We then propose an algorithm to derive the dwell time of subsequent buses serving a stop in order to illustrate when bus bunching might occur. We show that non-uniform arrival patterns can significantly influence the bus bunching process. With case studies we find that, even without exogenous delay, bunching can arise when the boarding rate is insufficient given the level of overall demand. Further, in case of exogenous delay, non-uniform arrivals can either worsen or improve the bunching conditions, depending on the level of delay. We conclude that therefore such effects should be considered when service control measures are discussed.


      PubDate: 2015-06-24T12:55:31Z
       
  • Robust constrained control of uncertain macroscopic fundamental diagram
           networks
    • Abstract: Publication date: Available online 16 June 2015
      Source:Transportation Research Part C: Emerging Technologies
      Author(s): Jack Haddad
      This paper considers modeling and control of uncertain Macroscopic Fundamental Diagram (MFD) systems for multiple-region networks. First, the nonlinear vehicle conservation equations based on MFD dynamics, presented in earlier publications, are transformed to linear equations with parameter uncertainties. The parameter uncertainties include the destination decomposition fractions, that are difficult to estimate in reality. Then, the uncertain linear model is utilized to design a robust feedback controller by an interpolation-based approach. This approach (i) guarantees robustness against all parameter uncertainties, (ii) handle control and state constraints, and (iii) present a computationally cheap solution. The main idea is to interpolate between (i) a stabilizing outer controller that respects the control and state constraints and (ii) an inner robustly stable controller designed by any method. The robust control is further challenged to deal with different relative locations of reference accumulation points on the MFD diagrams. Numerical results for a two-region system show that the uncertain linear model can replace the nonlinear model for modeling and control. Moreover, the robust control law is presented as implicit and explicit solutions, where in the implicit case one linear programming (LP) problem is solved at each time instant, while in the explicit case, the control law is shown as a piecewise affine function of state. Finally, a comparison between the interpolating controller and other controllers in the literature is carried out. The results demonstrate the performance advantages from applying the robust interpolating controller.


      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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