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TRANSPORTATION (95 journals)

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Journal Cover Transportation Research Part C: Emerging Technologies
  [SJR: 2.062]   [H-I: 72]   [20 followers]  Follow
    
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 0968-090X
   Published by Elsevier Homepage  [3043 journals]
  • Investigating heterogeneity in social influence by social distance in
           car-sharing decisions under uncertainty: A regret-minimizing hybrid choice
           model framework based on sequential stated adaptation experiments
    • Authors: Jinhee Kim; Soora Rasouli; Harry J.P. Timmermans
      Pages: 47 - 63
      Abstract: Publication date: December 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 85
      Author(s): Jinhee Kim, Soora Rasouli, Harry J.P. Timmermans
      The present study is designed to investigate social influence in car-sharing decisions under uncertainty. Social influence indicates that individuals’ decisions are influenced by the choices made by members of their social networks. An individual may experience different degrees of influence depending on social distance, i.e. the strength of the social relationship between individuals. Such heterogeneity in social influence has been largely ignored in the previous travel behavior research. The data used in this study stems from an egocentric social network survey, which measures the strength of the social relationships of each respondent. In addition, a sequential stated adaptation experiment was developed to capture more explicitly the effect of social network choices on the individual decision-making process. Social distance is regarded as a random latent variable. The estimated social distance and social network choices are incorporated into a social influence variable, which is treated as an explanatory variable in the car-sharing decision model. To simultaneously estimate latent social distance and the effects of social influence on the car-sharing decision, we expand the hybrid choice framework to incorporate the latent social distance model into discrete choice analysis. The estimation results show substantial social influence in car-sharing decisions. The magnitude of social influence varies according to the type of relationship, similarity of socio-demographics and the number of social interactions.

      PubDate: 2017-09-20T20:16:54Z
      DOI: 10.1016/j.trc.2017.09.001
      Issue No: Vol. 85 (2017)
       
  • Closed-form multiclass cell transmission model enhanced with overtaking,
           lane-changing, and first-in first-out properties
    • Authors: Kamonthep Tiaprasert; Yunlong Zhang; Chaodit Aswakul; Jian Jiao; Xin Ye
      Pages: 86 - 110
      Abstract: Publication date: December 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 85
      Author(s): Kamonthep Tiaprasert, Yunlong Zhang, Chaodit Aswakul, Jian Jiao, Xin Ye
      A novel multiclass macroscopic model is proposed in this article. In order to enhance first-in, first-out property (FIFO) and transmission function in the multiclass traffic modeling, a new multiclass cell transmission model with FIFO property (herein called FM-CTM) is extended from its prior multiclass cell transmission model (M-CTM). Also, to enhance its analytical compactness and resultant computational convenience, FM-CTM is formulated in this paper asa set of closed-form matrix equations. The objective is to improve the accuracy of traffic state estimation by enforcing FIFO property when a fast vehicle cannot overtake a slow vehicle due to a limitation of a single-lane road. Moreover, the proposed model takes into account a different priority for vehicles of each class to move forward through congested road conditions, and that makes the flow calculation independent from their free-flow speeds. Some hypothetical and real-world freeway networks with a constant or varying number of lanes are selected to verify FM-CTM by comparing with M-CTM and the conventional CTM. Observed densities of VISSIM and real-world dataset of I-80 are selected to compare with the simulated densities from the three CTMs. The numerical results show that FM-CTM outperforms the other two models by 15% of accuracy measures in most cases. Therefore, the proposed model is expected to be well applicable to the road network with a mixed traffic and varying number of lanes.

      PubDate: 2017-09-20T20:16:54Z
      DOI: 10.1016/j.trc.2017.09.008
      Issue No: Vol. 85 (2017)
       
  • A driver advisory system with dynamic losses for passenger electric
           multiple units
    • Authors: Nima Ghaviha; Markus Bohlin; Christer Holmberg; Erik Dahlquist; Robert Skoglund; Daniel Jonasson
      Pages: 111 - 130
      Abstract: Publication date: December 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 85
      Author(s): Nima Ghaviha, Markus Bohlin, Christer Holmberg, Erik Dahlquist, Robert Skoglund, Daniel Jonasson
      Driver advisory systems, instructing the driver how to control the train in an energy efficient manner, is one the main tools for minimizing energy consumption in the railway sector. There are many driver advisory systems already available in the market, together with significant literature on the mathematical formulation of the problem. However, much less is published on the development of such mathematical formulations, their implementation in real systems, and on the empirical data from their deployment. Moreover, nearly all the designed driver advisory systems are designed as an additional hardware to be added in drivers’ cabin. This paper discusses the design of a mathematical formulation and optimization approach for such a system, together with its implementation into an Android-based prototype, the results from on-board practical experiments, and experiences from the implementation. The system is based on a more realistic train model where energy calculations take into account dynamic losses in different components of the propulsion system, contrary to previous approaches. The experimental evaluation shows a significant increase in accuracy, as compared to a previous approach. Tests on a double-track section of the Mälaren line in Sweden demonstrates a significant potential for energy saving.

      PubDate: 2017-09-27T16:39:41Z
      DOI: 10.1016/j.trc.2017.09.010
      Issue No: Vol. 85 (2017)
       
  • A methodology to evaluate driving efficiency for professional drivers
           based on a maturity model
    • Authors: Laura Pozueco; Xabiel G. Pañeda; Alejandro G. Tuero; Gabriel Díaz; Roberto García; David Melendi; Alejandro G. Pañeda; José A. Sánchez
      Pages: 148 - 167
      Abstract: Publication date: December 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 85
      Author(s): Laura Pozueco, Xabiel G. Pañeda, Alejandro G. Tuero, Gabriel Díaz, Roberto García, David Melendi, Alejandro G. Pañeda, José A. Sánchez
      Over the last decade, transport companies have tried to reduce fuel consumption using efficient driving programs. In them, motorists have to apply different specific techniques while driving. Thus, to succeed in this learning process there are two key elements: the knowledge of efficient driving techniques and the drivers’ motivation. The latter is a human factor which companies usually bring about by using reward systems. In this case, having a fair evaluation mechanism is the keystone to determine goal fulfilment. This paper presents a complete methodology to evaluate driving efficiency of drivers in professional fleets. The evaluation methodology is based on a continuous process which determines the maturity of the motorist in different aspects, such as the efficiency during the start of the vehicle movement, during motion or in stop events. In addition, the evaluation methodology includes an early-classification method to establish the initial efficiency level of the individual drivers which permits an adaptation of the learning process from the beginning. A dashboard has also been developed to support the evaluation methodology. 880 professional drivers have been evaluated with this methodology. Results show that the evaluation methodology identifies drivers’ weaknesses, to be improved in successive iterations of the learning process.
      Graphical abstract image

      PubDate: 2017-10-04T17:16:10Z
      DOI: 10.1016/j.trc.2017.09.017
      Issue No: Vol. 85 (2017)
       
  • Modeling the dynamic effect of information on drivers’ choice behavior
           in the context of an Advanced Traveler Information System
    • Authors: Mauro Dell'Orco; Mario Marinelli
      Pages: 168 - 183
      Abstract: Publication date: December 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 85
      Author(s): Mauro Dell'Orco, Mario Marinelli
      In this paper, we present a modeling approach, based on Fuzzy Data Fusion, to reproduce drivers’ dynamic choice behavior under an Advanced Traveler Information System (ATIS). The proposed model uses the Possibility Theory to model Uncertainty embedded in human perception of information. We have introduced a time-dependent Possibility Distribution of Information to model the users’ changing perception of travel time also based on current network conditions. Drivers’ choice models are often developed and calibrated by using Stated Preference (SP) surveys, amongst others. In this work, we present an experiment to set up an SP-tool based on a driving simulator developed at the Polytechnic University of Bari. The results obtained by the proposed model are analyzed and compared with the driver dynamic behavior observed in the experiment.

      PubDate: 2017-10-04T17:16:10Z
      DOI: 10.1016/j.trc.2017.09.019
      Issue No: Vol. 85 (2017)
       
  • Improving recovery-to-optimality robustness through efficiency-balanced
           design of timetable structure
    • Authors: Chao Lu; Jinjin Tang; Leishan Zhou; Yixiang Yue; Zhitong Huang
      Pages: 184 - 210
      Abstract: Publication date: December 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 85
      Author(s): Chao Lu, Jinjin Tang, Leishan Zhou, Yixiang Yue, Zhitong Huang
      To improve the service quality of the railway system (e.g., punctuality and travel times) and to enhance the robust timetabling methods further, this paper proposes an integrated two-stage approach to consider the recovery-to-optimality robustness into the optimized timetable design without predefined structure information (defined as flexible structure) such as initial departure times, overtaking stations, train order and buffer time. The first-stage timetabling model performs an iterative adjustment of all departure and arrival times to generate an optimal timetable with balanced efficiency and recovery-to-optimality robustness. The second-stage dispatching model evaluates the recovery-to-optimality robustness by simulating how each timetable generated from the first-stage could recover under a set of restricted scenarios of disturbances using the proposed dispatching algorithm. The concept of recovery-to-optimality is examined carefully for each timetable by selecting a set of optimally refined dispatching schedules with minimum recovery cost under each scenario of disturbance. The robustness evaluation process enables an updating of the timetable by using the generated dispatching schedules. Case studies were conducted in a railway corridor as a special case of a simple railway network to verify the effectiveness of the proposed approach. The results show that the proposed approach can effectively attain a good trade-off between the timetable efficiency and obtainable robustness for practical applications.

      PubDate: 2017-10-04T17:16:10Z
      DOI: 10.1016/j.trc.2017.09.015
      Issue No: Vol. 85 (2017)
       
  • A bi-level model for single-line rail timetable design with consideration
           of demand and capacity
    • Authors: Yuting Zhu; Baohua Mao; Yun Bai; Shaokuan Chen
      Pages: 211 - 233
      Abstract: Publication date: December 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 85
      Author(s): Yuting Zhu, Baohua Mao, Yun Bai, Shaokuan Chen
      This paper proposes abi-level model to solve the timetable design problem for an urban rail line. The upper level model aims at determining the headways between trains to minimize total passenger cost, which includes not only the usual perceived travel time cost, but also penalties during travel. With the headways given by the upper level model, passengers’ arrival times at their origin stops are determined by the lower level model, in which the cost-minimizing behavior of each passenger is taken into account. To make the model more realistic, explicit capacity constraints of individual trains are considered. With these constraints, passengers cannot board a full train, but wait in queues for the next coming train. A two-stage genetic algorithm incorporating the method of successive averages is introduced to solve the bi-level model. Two hypothetical examples and a real world case are employed to evaluate the effectiveness of the proposed bi-level model and algorithm. Results show that the bi-level model performs well in reducing total passenger cost, especially in reducing waiting time cost and penalties. And the section loading-rates of trains in the optimized timetable are more balanced than the even-headway timetable. The sensitivity analyses show that passenger’s desired arrival time interval at destination and crowding penalty factor have a high influence on the optimal solution. And with the dispersing of passengers' desired arrival time intervals or the increase of crowding penalty factor, the section loading-rates of trains become more balanced.

      PubDate: 2017-10-04T17:16:10Z
      DOI: 10.1016/j.trc.2017.09.002
      Issue No: Vol. 85 (2017)
       
  • Agent-based simulation framework for mixed traffic of cars, pedestrians
           and trams
    • Authors: Hideki Fujii; Hideaki Uchida; Shinobu Yoshimura
      Pages: 234 - 248
      Abstract: Publication date: December 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 85
      Author(s): Hideki Fujii, Hideaki Uchida, Shinobu Yoshimura
      In this paper, we report on the construction of a new framework for simulating mixed traffic consisting of cars, trams, and pedestrians that can be used to support discussions about road management, signal control, and public transit. Specifically, a layered road structure that was designed for car traffic simulations was extended to interact with an existing one-dimensional (1D) car-following model and a two-dimensional (2D) discrete choice model for pedestrians. The car model, pedestrian model, and interaction rules implemented in the proposed framework were verified through simulations involving simple road environments. The resulting simulated values were in near agreement with the empirical data. We then used the proposed framework to assess the impact of a tramway extension plan for a real city. The simulation results showed that the impact of the proposed tramway on existing car traffic would not be serious, and by extension, implied that the proposed framework could help stakeholders decide on expansion scenarios that are satisfactory to both tram users and private car owners.

      PubDate: 2017-10-04T17:16:10Z
      DOI: 10.1016/j.trc.2017.09.018
      Issue No: Vol. 85 (2017)
       
  • Forecasting journey time distribution with consideration to abnormal
           traffic conditions
    • Authors: R.X. Zhong; J.C. Luo; H.X. Cai; A. Sumalee; F.F. Yuan; Andy H.F. Chow
      Pages: 292 - 311
      Abstract: Publication date: December 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 85
      Author(s): R.X. Zhong, J.C. Luo, H.X. Cai, A. Sumalee, F.F. Yuan, Andy H.F. Chow
      Travel time is an important index for managers to evaluate the performance of transportation systems and an intuitive measure for travelers to choose routes and departure times. An important part of the literature focuses on predicting instantaneous travel time under recurrent traffic conditions to disseminate traffic information. However, accurate travel time prediction is important for assessing the effects of abnormal traffic conditions and helping travelers make reliable travel decisions under such conditions. This study proposes an online travel time prediction model with emphasis on capturing the effects of anomalies. The model divides a path into short links. A Functional Principal Component Analysis (FPCA) framework is adopted to forecast link travel times based on historical data and real-time measurements. Furthermore, a probabilistic nested delay operator is used to calculate path travel time distributions. To ensure that the algorithm is fast enough for online applications, parallel computation architecture is introduced to overcome the computational burden of the FPCA. Finally, a rolling horizon structure is applied to online travel time prediction. Empirical results for Guangzhou Airport Expressway indicate that the proposed method can capture an abrupt change in traffic state and provide a promising and reliable travel time prediction at both the link and path levels. In the case where the original FPCA is modified for parallelization, accuracy and computational effort are evaluated and compared with those of the sequential algorithm. The proposed algorithm is found to require only a piece rather than a large set of traffic incident records.

      PubDate: 2017-10-12T04:16:35Z
      DOI: 10.1016/j.trc.2017.08.021
      Issue No: Vol. 85 (2017)
       
  • Percolation phenomenon in connected vehicle network through a multi-agent
           approach: Mobility benefits and market penetration
    • Authors: Alireza Mostafizi; Shangjia Dong; Haizhong Wang
      Pages: 312 - 333
      Abstract: Publication date: December 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 85
      Author(s): Alireza Mostafizi, Shangjia Dong, Haizhong Wang
      This paper presents an integrated multi-agent approach, coupled with percolation theory and network science, to measure the mobility impacts (i.e., mean travel time of the system) of connected vehicle (CVtio) network at varying levels of market penetration rate. We capture the characteristics of a CV network, i.e., node degree distribution, vehicular clustering, and giant component size to verify the existence of percolation phenomenon, and further connect the emergence of mobility benefits to the percolation phase transition in the CV network. We show the percolation phase transition properties to appear in a dynamic CV network with time-correlated link and node dynamics. An analytical framework was developed to evaluate the CV network attributes with varying market penetrations (MP) and connection ranges (CR) to identify percolation phenomenon in a mixed CV and Non-CV environment. In addition, a multi-agent CV simulation platform was created to further measure (1) how varying MPs and CRs affect the network-wide mobility measured by the mean travel time of the network; and (2) when percolation transition occurs in CV network to capture the critical MP and CR. Percolation phenomenon in CV network was further validated with the analytical assessments. The results show that (1) percolation phase transition phenomenon is a function of both market penetration and communication range; (2) percolation phase transitions in both mobility and CV network are highly correlated; (3) the application can reduce the average travel time of the system by up to 20% with reasonable market penetration and communication range; (4) critical market penetration is sensitive to communication range, and vice versa; (5) at least 70% of the CVs on the network are required to show in the same cluster for mobility benefits to appear; and (6) for high levels of MP or CR, a low probability of connectivity (PC) does not dramatically change the mean travel time. These results provide solid supports to create evidence-driven frameworks to guide future CV deployment and CV network analysis.

      PubDate: 2017-10-12T04:16:35Z
      DOI: 10.1016/j.trc.2017.09.013
      Issue No: Vol. 85 (2017)
       
  • Controlled time of arrival windows for already initiated energy-neutral
           continuous descent operations
    • Authors: Ramon Dalmau; Xavier Prats
      Pages: 334 - 347
      Abstract: Publication date: December 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 85
      Author(s): Ramon Dalmau, Xavier Prats
      Continuous descent operations with controlled times of arrival at one or several metering fixes could enable environmentally friendly procedures without compromising terminal airspace capacity. This paper focuses on controlled time of arrival updates once the descent has been already initiated, assessing the feasible time window (and associated fuel consumption) of continuous descent operations requiring neither thrust nor speed-brake usage along the whole descent (i.e. only elevator control is used to achieve different metering times). Based on previous works, an optimal control problem is formulated and numerically solved. The earliest and latest times of arrival at the initial approach fix have been computed for the descent of an Airbus A320 under different scenarios, considering the potential altitudes and distances to go when receiving the controlled time of arrival update. The effects of the aircraft mass, initial speed, longitudinal wind and position of the initial approach fix on the time window have been also investigated. Results show that time windows about three minutes could be achieved for certain conditions, and that there is a trade-off between robustness facing controlled time of arrival updates during the descent and fuel consumption. Interestingly, minimum fuel trajectories almost correspond to those of minimum time.

      PubDate: 2017-10-12T04:16:35Z
      DOI: 10.1016/j.trc.2017.09.024
      Issue No: Vol. 85 (2017)
       
  • Traffic data imputation via tensor completion based on soft thresholding
           of Tucker core
    • Authors: J.H. de M. Goulart; A.Y. Kibangou; G. Favier
      Pages: 348 - 362
      Abstract: Publication date: December 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 85
      Author(s): J.H. de M. Goulart, A.Y. Kibangou, G. Favier
      Technological limitations and practical difficulties cause inevitable losses of traffic data in the typical processing chain of an intelligent transportation system. This has motivated the development of imputation algorithms for mitigating the consequences of such losses. As the involved datasets are usually multidimensional and bear strong spatio-temporal correlations, we propose for traffic data imputation a tensor completion algorithm which promotes parsimony of an estimated orthogonal Tucker model by iteratively softly thresholding its core. The motivation of this strategy is discussed on the basis of characteristics typically possessed by real-world datasets. An evaluation of the proposed method using speed data from the Grenoble south ring (France) shows that our algorithm outperforms other imputation methods, including tensor completion algorithms, and delivers good results even when the loss is severely systematic, being mostly concentrated in long time windows (of up to three hours) spread along the considered time horizon.

      PubDate: 2017-10-12T04:16:35Z
      DOI: 10.1016/j.trc.2017.09.011
      Issue No: Vol. 85 (2017)
       
  • Electrification of the two-car household: PHEV or BEV'
    • Authors: Lars-Henrik Björnsson; Sten Karlsson
      Pages: 363 - 376
      Abstract: Publication date: December 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 85
      Author(s): Lars-Henrik Björnsson, Sten Karlsson
      In previous works, we have shown two-car households to be better suited than one-car households for leveraging the potential benefits of the battery electric vehicle (BEV), both when the BEV simply replaces the second car and when it is used optimally in combination with a conventional car to overcome the BEV’s range limitation and increase its utilization. Based on a set of GPS-measured car movement data from 64 two-car households in Sweden, we here assess the potential electric driving of a plug-in hybrid electric vehicle (PHEV) in a two-car household and compare the resulting economic viability and potential fuel substitution to that of a BEV. Using estimates of near-term mass production costs, our results suggest that, for Swedish two-car households, the PHEV in general should have a higher total cost of ownership than the BEV, provided the use of the BEV is optimized. However, the PHEV will increasingly be favored if, for example, drivers cannot or do not want to optimize usage. In addition, the PHEV and the BEV are not perfect substitutes. The PHEV may be favored if drivers require that the vehicle be able to satisfy all driving needs (i.e., if drivers don’t accept the range and charge-time restrictions of the BEV) or if drivers requires an even larger battery in the BEV to counter range anxiety. We find that, given a particular usage strategy, the electric drive fraction (EDF) of the vehicle fleet is less dependent on whether PHEVs or BEVs are used to replace one of the conventional cars in two-car households. Instead, the EDF depends more on the usage strategy, i.e., on whether the PHEV/BEV is used to replace the conventional car with the higher annual mileage (“the first car”), the less used car (“the second car”), or is used flexibly to substitute for either in order to optimize use. For example, from a fuel replacement perspective it is often better to replace the first car with a PHEV than to replace the second with a BEV.

      PubDate: 2017-10-12T04:16:35Z
      DOI: 10.1016/j.trc.2017.09.021
      Issue No: Vol. 85 (2017)
       
  • Modeling the information flow propagation wave under vehicle-to-vehicle
           communications
    • Authors: Yong Hoon Kim; Srinivas Peeta; Xiaozheng He
      Pages: 377 - 395
      Abstract: Publication date: December 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 85
      Author(s): Yong Hoon Kim, Srinivas Peeta, Xiaozheng He
      Vehicle-to-vehicle (V2V) communications under the connected vehicle context have the potential to provide new paradigms to enhance the safety, mobility and environmental sustainability of surface transportation. Understanding the information propagation characteristics in space and time is a key enabler for V2V-based traffic systems. Most existing analytical models assume instantaneous propagation of information flow through multi-hop communications. Such an assumption ignores the spatiotemporal relationships between the traffic flow dynamics and V2V communication constraints. This study proposes a macroscopic two-layer model to characterize the information flow propagation wave (IFPW). The traffic flow propagation is formulated in the lower layer as a system of partial differential equations based on the Lighthill-Whitham-Richards model. Due to their conceptual similarities, the upper layer adapts and modifies a spatial Susceptible-Infected epidemic model to describe information dissemination between V2V-equipped vehicles using integro-differential equations. A closed-form solution is derived for the IFPW speed under homogeneous conditions. The IFPW speed is numerically determined for heterogeneous conditions. Numerical experiments illustrate the impact of traffic density and market penetration of V2V-equipped vehicles on the IFPW speed. The proposed model can capture the spatiotemporal relationships between the traffic and V2V communication layers, and aid in the design of novel information propagation strategies to manage traffic conditions under V2V-based traffic systems.

      PubDate: 2017-10-12T04:16:35Z
      DOI: 10.1016/j.trc.2017.09.023
      Issue No: Vol. 85 (2017)
       
  • Validation of an extended discrete first-order model with variable speed
           limits
    • Authors: Yu Han; Andreas Hegyi; Yufei Yuan; Serge Hoogendoorn
      Pages: 1 - 17
      Abstract: Publication date: October 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 83
      Author(s): Yu Han, Andreas Hegyi, Yufei Yuan, Serge Hoogendoorn
      This paper validates the prediction model embedded in a model predictive controller (MPC) of variable speed limits (VSLs). The MPC controller was designed based on an extended discrete first-order model with a triangular fundamental diagram. In our previous work, the extended discrete first-order model was designed to reproduce the capacity drop and the propagation of jam waves, and it was validated with reasonable accuracy without the presence of VSLs. As VSLs influence traffic dynamics, the dynamics including VSLs needs to be validated, before it can be applied as a prediction model in MPC. For conceptual illustrations, we use two synthetic examples to show how the model reproduces the key mechanisms of VSLs that are applied by existing VSL control approaches. Furthermore, the model is calibrated by use of real traffic data from Dutch freeway A12, where the field test of a speed limit control algorithm (SPECIALIST) was conducted. In the calibration, the original model is extended by using a quadrangular fundamental diagram which keeps the linear feature of the model and represents traffic states at the under-critical branch more accurately. The resulting model is validated using various traffic data sets. The accuracy of the model is compared with a second-order traffic flow model. The performance of two models is comparable: both models reproduce accurate results matching with real data. Flow errors of the calibration and validation are around 10%. The extended discrete first-order model-based MPC controller has been demonstrated to resolve freeway jam waves efficiently by synthetic cases. It has a higher computation speed comparing to the second-order model-based MPC.

      PubDate: 2017-08-03T07:02:01Z
      DOI: 10.1016/j.trc.2017.07.009
      Issue No: Vol. 83 (2017)
       
  • Hierarchical perimeter control with guaranteed stability for dynamically
           coupled heterogeneous urban traffic
    • Authors: Hui Fu; Na Liu; Gang Hu
      Pages: 18 - 38
      Abstract: Publication date: October 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 83
      Author(s): Hui Fu, Na Liu, Gang Hu
      Perimeter control based on the Macroscopic Fundamental Diagram (MFD) is widely developed for alleviating or postponing congestion in a protected region. Recent studies reveal that traffic conditions might not be improved if the perimeter control strategies are applied to unstable systems where high demand generates heavy and heterogeneously distributed traffic congestion. Therefore, considering stability of the targeted traffic system is essential, for the sake of developing a feasible and then optimal control strategy. This paper sheds light on this direction. It integrates a stability characterization algorithm of MFD system equations into the Model Predictive Control (MPC) scheme, and features respectively an upper and a lower bound of the feasible control inputs, to guarantee system stability. Firstly, the dynamics of traffic heterogeneity and its effect on the MFD are analyzed, using real data from Guangzhou in China. Piecewise affine functions of average flow are proposed to capture traffic heterogeneity in both regional and subregional MFDs. Secondly, stability of a three-state two-region system is investigated via stable equilibrium and surface boundaries analysis. Finally, a three-layer hierarchical control strategy is introduced for the studied two-region heterogeneous urban networks. The first layer of the controller calculates the stable surface boundaries for the given traffic demands and then determines the bounds of control input (split rate). An MPC approach in the second layer is used to solve an optimization problem with two objectives of minimizing total network delay and maximizing network throughput. Heterogeneity among the subregions is minimized in the last layer by implementing simultaneously a subregional perimeter flow control and an internal flow control. The effectiveness and stability of the proposed control approach are verified by comparison with four existing perimeter control strategies.

      PubDate: 2017-08-03T07:02:01Z
      DOI: 10.1016/j.trc.2017.07.007
      Issue No: Vol. 83 (2017)
       
  • Scalable stability analysis on large connected vehicle systems subject to
           stochastic communication delays
    • Authors: Wubing B. Qin; Gábor Orosz
      Pages: 39 - 60
      Abstract: Publication date: October 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 83
      Author(s): Wubing B. Qin, Gábor Orosz
      In this paper large connected vehicle systems are analyzed where vehicles utilize vehicle-to-vehicle (V2V) communication to control their longitudinal motion. It is shown that packet drops in communication channels introduce stochastic delay variations in the feedback loops. Scalable methods are developed to evaluate stability and disturbance attenuation while utilizing the mean, second moment, and covariance dynamics in open chain and closed ring configurations. The stability results are summarized using stability diagrams in the plane of the control parameters while varying the packet delivery ratio and the number of vehicles. Also, the relationship between the stability of different configurations is characterized. The results emphasize the feasibility of V2V communication-based control in improving traffic flow.

      PubDate: 2017-08-03T07:02:01Z
      DOI: 10.1016/j.trc.2017.07.005
      Issue No: Vol. 83 (2017)
       
  • Rolling horizon stochastic optimal control strategy for ACC and CACC under
           uncertainty
    • Authors: Yang Zhou; Soyoung Ahn; Madhav Chitturi; David A. Noyce
      Pages: 61 - 76
      Abstract: Publication date: October 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 83
      Author(s): Yang Zhou, Soyoung Ahn, Madhav Chitturi, David A. Noyce
      This paper presents a rolling horizon stochastic optimal control strategy for both Adaptive Cruise Control and Cooperative Adaptive Cruise Control under uncertainty based on the constant time gap policy. Specifically, uncertainties that can arise in vehicle control systems and vehicle sensor measurements are represented as normally-distributed disturbances to state and measurement equations in a state-space formulation. Then, acceleration sequence of a controlled vehicle is determined by optimizing an objective function that captures control efficiency and driving comfort over a predictive horizon, constrained by bounded acceleration/deceleration and collision protection. The optimization problem is formulated as a linearly constrained linear quadratic Gaussian problem and solved using a separation principle, Lagrangian relaxation, and Kalman filter. A sensitivity analysis and a scenario-based analysis via simulations demonstrate that the proposed control strategy can generate smoother vehicle control and perform better than a deterministic feedback controller, particularly under small system disturbances and large measurement disturbances.

      PubDate: 2017-09-03T02:26:45Z
      DOI: 10.1016/j.trc.2017.07.011
      Issue No: Vol. 83 (2017)
       
  • Robust planning of dynamic wireless charging infrastructure for battery
           electric buses
    • Authors: Zhaocai Liu; Ziqi Song
      Pages: 77 - 103
      Abstract: Publication date: October 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 83
      Author(s): Zhaocai Liu, Ziqi Song
      Battery electric buses with zero tailpipe emissions have great potential in improving environmental sustainability and livability of urban areas. However, the problems of high cost and limited range associated with on-board batteries have substantially limited the popularity of battery electric buses. The technology of dynamic wireless power transfer (DWPT), which provides bus operators with the ability to charge buses while in motion, may be able to effectively alleviate the drawbacks of electric buses. In this paper, we address the problem of simultaneously selecting the optimal location of the DWPT facilities and designing the optimal battery sizes of electric buses for a DWPT electric bus system. The problem is first constructed as a deterministic model in which the uncertainty of energy consumption and travel time of electric buses is ignored. The methodology of robust optimization (RO) is then adopted to address the uncertainty of energy consumption and travel time. The affinely adjustable robust counterpart (AARC) of the deterministic model is developed, and its equivalent tractable mathematical programming is derived. Both the deterministic model and the robust model are demonstrated with a real-world bus system. The results demonstrate that the proposed deterministic model can effectively determine the allocation of DWPT facilities and the battery sizes of electric buses for a DWPT electric bus system; and the robust model can further provide optimal designs that are robust against the uncertainty of energy consumption and travel time for electric buses.

      PubDate: 2017-09-03T02:26:45Z
      DOI: 10.1016/j.trc.2017.07.013
      Issue No: Vol. 83 (2017)
       
  • Joint optimization of tram timetables and signal timing adjustments at
           intersections
    • Authors: Jungang Shi; Yanshuo Sun; Paul Schonfeld; Jian Qi
      Pages: 104 - 119
      Abstract: Publication date: October 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 83
      Author(s): Jungang Shi, Yanshuo Sun, Paul Schonfeld, Jian Qi
      This paper explores at the planning level the benefits of coordinating tram movements and signal timings at controlled intersections. Although trams may have dedicated travel lanes, they mostly operate in a mixed traffic environment at intersections. To ensure tram progression, pre-set signal timings at intersections are adjusted by activating Transit Signal Priority (TSP) actions, which inevitably add delays to the auto traffic. A mixed integer program is proposed for jointly determining tram schedules for a single tram line and modifying signal timings at major controlled intersections. The objective is to minimize the weighted sum of the total tram travel time and TSP’s negative impacts on other traffic. A real-world case study of Line 5 of the Shenyang Hunnan Modern Tramway shows that by extending the dwell time or link travel time we can significantly reduce the TSP’s negative impacts on the auto traffic while only slightly increasing tram travel times.

      PubDate: 2017-09-03T02:26:45Z
      DOI: 10.1016/j.trc.2017.07.014
      Issue No: Vol. 83 (2017)
       
  • Network traffic flow optimization under performance constraints
    • Authors: Alfréd Csikós; Themistoklis Charalambous; Hamed Farhadi; Balázs Kulcsár; Henk Wymeersch
      Pages: 120 - 133
      Abstract: Publication date: October 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 83
      Author(s): Alfréd Csikós, Themistoklis Charalambous, Hamed Farhadi, Balázs Kulcsár, Henk Wymeersch
      In this paper, a model-based perimeter control policy for large-scale urban vehicular networks is proposed. Assuming a homogeneously loaded vehicle network and the existence of a well-posed Network Fundamental Diagram (NFD), we describe a protected network throughout its aggregated dynamics including nonlinear exit flow characteristics. Within this framework of constrained optimal boundary flow gating, two main performance metrics are considered: (a) first, connected to the NFD, the concept of average network travel time and delay as a performance metric is defined; (b) second, at boundaries, we take into account additional external network queue dynamics governed by uncontrolled inflow demands. External queue capacities in terms of finite-link lengths are used as the second performance metric. Hence, the corresponding performance requirement is an upper bound of external queues. While external queues represent vehicles waiting to enter the protected network, internal queue describes the protected network’s aggregated behavior. By controlling the number of vehicles joining the internal queue from the external ones, herewith a network traffic flow maximization solution subject to the internal and external dynamics and their performance constraints is developed. The originally non-convex optimization problem is transformed to a numerically efficiently convex one by relaxing the performance constraints into time-dependent state boundaries. The control solution can be interpreted as a mechanism which transforms the unknown arrival process governing the number of vehicles entering the network to a regulated process, such that prescribed performance requirements on travel time in the network and upper bound on the external queue are satisfied. Comparative numerical simulation studies on a microscopic traffic simulator are carried out to show the benefits of the proposed method.

      PubDate: 2017-09-03T02:26:45Z
      DOI: 10.1016/j.trc.2017.08.002
      Issue No: Vol. 83 (2017)
       
  • Data-driven fuel consumption estimation: A multivariate adaptive
           regression spline approach
    • Authors: Yuche Chen; Lei Zhu; Jeffrey Gonder; Stanley Young; Kevin Walkowicz
      Pages: 134 - 145
      Abstract: Publication date: October 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 83
      Author(s): Yuche Chen, Lei Zhu, Jeffrey Gonder, Stanley Young, Kevin Walkowicz
      Providing guidance and information to drivers to help them make fuel-efficient route choices remains an important and effective strategy in the near term to reduce fuel consumption from the transportation sector. One key component in implementing this strategy is a fuel-consumption estimation model. In this paper, we developed a mesoscopic fuel consumption estimation model that can be implemented into an eco-routing system. Our proposed model presents a framework that utilizes large-scale, real-world driving data, clusters road links by free-flow speed and fits one statistical model for each of cluster. This model includes predicting variables that were rarely or never considered before, such as free-flow speed and number of lanes. We applied the model to a real-world driving data set based on a global positioning system travel survey in the Philadelphia-Camden-Trenton metropolitan area. Results from the statistical analyses indicate that the independent variables we chose influence the fuel consumption rates of vehicles. But the magnitude and direction of the influences are dependent on the type of road links, specifically free-flow speeds of links. A statistical diagnostic is conducted to ensure the validity of the models and results. Although the real-world driving data we used to develop statistical relationships are specific to one region, the framework we developed can be easily adjusted and used to explore the fuel consumption relationship in other regions.

      PubDate: 2017-09-03T02:26:45Z
      DOI: 10.1016/j.trc.2017.08.003
      Issue No: Vol. 83 (2017)
       
  • Route choice stickiness of public transport passengers: Measuring habitual
           bus ridership behaviour using smart card data
    • Authors: Jiwon Kim; Jonathan Corcoran; Marty Papamanolis
      Pages: 146 - 164
      Abstract: Publication date: October 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 83
      Author(s): Jiwon Kim, Jonathan Corcoran, Marty Papamanolis
      This paper explores how we can use smart card data for bus passengers to reveal individual and aggregate travel behaviour. More specifically, we measure the extent to which both individual and bus routes exhibit habitual behaviour. To achieve this, we introduce a metric called Stickiness Index to quantify the range of preferences of users that always select to travel on the same route (high stickiness) to those with a more varied patterns of route selection (low stickiness). Adopting a visual analytic and modelling approach using a suite of regression models we find evidence to suggest that stickiness varies across the metropolitan area and over a 24-h period wherein higher stickiness is associated with high frequency users where there is substantial variability of route travel times across all alternatives. We argue that our findings are important in their capacity to contribute to a new evidence base with the potential to inform the (re)-design and scheduling of a public transit systems through unveiling the complexities of transit behaviour.

      PubDate: 2017-09-03T02:26:45Z
      DOI: 10.1016/j.trc.2017.08.005
      Issue No: Vol. 83 (2017)
       
  • Optimization of periodic crew schedules with application of column
           generation method
    • Authors: Jaroslav Janacek; Michal Kohani; Matyas Koniorczyk; Peter Marton
      Pages: 165 - 178
      Abstract: Publication date: October 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 83
      Author(s): Jaroslav Janacek, Michal Kohani, Matyas Koniorczyk, Peter Marton
      We present an alternative approach to the problem of periodic crew scheduling. We introduce the concept of frames which leads us to a modeling approach which suits well the current practice of the majority of European railway operators. It results in a model facilitating column generation techniques resulting in a Dantzig-Wolfe type decomposition, and thus suitable for a parallel implementation in a high-performance computing environment. We exploit the properties of network flow models to avoid several additional integer constraints. We compare two approaches to solve the problem. The first approach consists of solving the original problem by single model. The second approach is our step-by-step column generation. The comparison is based on our implementation which we describe in detail along with its application to certain benchmark instances. The benchmarks originate in real or close-to-realistic problems from railway systems in Slovakia and Hungary. The case studies demonstrate that our model is well-suited for real-life applications.

      PubDate: 2017-09-03T02:26:45Z
      DOI: 10.1016/j.trc.2017.07.008
      Issue No: Vol. 83 (2017)
       
  • A copula-based approach for estimating the travel time reliability of
           urban arterial
    • Authors: Min Chen; Guizhen Yu; Peng Chen; Yunpeng Wang
      Pages: 1 - 23
      Abstract: Publication date: September 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 82
      Author(s): Min Chen, Guizhen Yu, Peng Chen, Yunpeng Wang
      Estimating the travel time reliability (TTR) of urban arterial is critical for real-time and reliable route guidance and provides theoretical bases and technical support for sophisticated traffic management and control. The state-of-art procedures for arterial TTR estimation usually assume that path travel time follows a certain distribution, with less consideration about segment correlations. However, the conventional approach is usually unrealistic because an important feature of urban arterial is the dependent structure of travel times on continuous segments. In this study, a copula-based approach that incorporates the stochastic characteristics of segments travel time is proposed to model arterial travel time distribution (TTD), which serves as a basis for TTR quantification. First, segments correlation is empirically analyzed and different types of copula models are examined. Then, fitting marginal distributions for segment TTD is conducted by parametric and non-parametric regression analysis, respectively. Based on the estimated parameters of the models, the best-fitting copula is determined in terms of the goodness-of-fit tests. Last, the model is examined at two study sites with AVI data and NGSIM trajectory data, respectively. The results of path TTD estimation demonstrate the advantage of the proposed copula-based approach, compared with the convolution model without capturing segments correlation and the empirical distribution fitting methods. Furthermore, when considering the segments correlation effect, it was found that the estimated path TTR is more accurate than that by the convolution model.

      PubDate: 2017-07-03T09:56:19Z
      DOI: 10.1016/j.trc.2017.06.007
      Issue No: Vol. 82 (2017)
       
  • Long distance truck tracking from advanced point detectors using a
           selective weighted Bayesian model
    • Authors: Kyung (Kate) Hyun; Andre Tok; Stephen G. Ritchie
      Pages: 24 - 42
      Abstract: Publication date: September 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 82
      Author(s): Kyung (Kate) Hyun, Andre Tok, Stephen G. Ritchie
      Truck flow patterns are known to vary by season and time-of-day, and to have important implications for freight modeling, highway infrastructure design and operation, and energy and environmental impacts. However, such variations cannot be captured by current truck data sources such as surveys or point detectors. To facilitate development of detailed truck flow pattern data, this paper describes a new truck tracking algorithm that was developed to estimate path flows of trucks by adopting a linear data fusion method utilizing weigh-in-motion (WIM) and inductive loop point detectors. A Selective Weighted Bayesian Model (SWBM) was developed to match individual vehicles between two detector locations using truck physical attributes and inductive waveform signatures. Key feature variables were identified and weighted via Bayesian modeling to improve vehicle matching performance. Data for model development were collected from two WIM sites spanning 26miles in California where only 11 percent of trucks observed at the downstream site traversed the whole corridor. The tracking model showed 81 percent of correct matching rate to the trucks declared as through trucks from the algorithm. This high accuracy showed that the tracking model is capable of not only correctly matching through vehicles but also successfully filtering out non-through vehicles on this relatively long distance corridor. In addition, the results showed that a Bayesian approach with full integration of two complementary detector data types could successfully track trucks over long distances by minimizing the impacts of measurement variations or errors from the detection systems employed in the tracking process. In a separate case study, the algorithm was implemented over an even longer 65-mile freeway section and demonstrated that the proposed algorithm is capable of providing valuable insights into truck travel patterns and industrial affiliation to yield a comprehensive truck activity data source.

      PubDate: 2017-07-03T09:56:19Z
      DOI: 10.1016/j.trc.2017.06.004
      Issue No: Vol. 82 (2017)
       
  • Characterising Green Light Optimal Speed Advisory trajectories for
           platoon-based optimisation
    • Authors: Simon Stebbins; Mark Hickman; Jiwon Kim; Hai L. Vu
      Pages: 43 - 62
      Abstract: Publication date: September 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 82
      Author(s): Simon Stebbins, Mark Hickman, Jiwon Kim, Hai L. Vu
      Conceptually, a Green Light Optimal Speed Advisory (GLOSA) system suggests speeds to vehicles, allowing them to pass through an intersection during the green interval. In previous papers, a single speed is computed for each vehicle in a range between acceptable minimum and maximum values (for example between standstill and the speed limit). This speed is assumed to be constant until the beginning of the green interval, and sent as advice to the vehicle. The goal is to optimise for a particular objective, whether it be minimisation of emissions (for environmental reasons), fuel usage or delay. This paper generalises the advice given to a vehicle, by optimising for delay over the entire trajectory instead of suggesting an individual speed, regardless of initial conditions – time until green, distance to intersection and initial speed. This may require multiple acceleration manoeuvres, so the advice is sent as a suggested acceleration at each time step. Such advice also takes into account a suitable safety constraint, ensuring that vehicles are always able to stop before the intersection during a red interval, thus safeguarding against last-minute signal control schedule changes. While the algorithms developed primarily minimise delay, they also help to reduce fuel usage and emissions by conserving kinetic energy. Since vehicles travel in platoons, the effectiveness of a GLOSA system is heavily reliant on correctly identifying the leading vehicle that is the first to be given trajectory advice for each cycle. Vehicles naturally form a platoon behind this leading vehicle. A time loop technique is proposed which allows accurate identification of the leader even when there are complex interactions between preceding vehicles. The developed algorithms are ideal for connected autonomous vehicle environments, because computer control allows vehicles’ trajectories to be managed with greater accuracy and ease. However, the advice algorithms can also be used in conjunction with manual control provided Vehicle-to-Infrastructure (V2I) communication is available.

      PubDate: 2017-07-03T09:56:19Z
      DOI: 10.1016/j.trc.2017.06.014
      Issue No: Vol. 82 (2017)
       
  • A comparison of different container sorting systems in modern rail-rail
           transshipment yards
    • Authors: Stefan Fedtke; Nils Boysen
      Pages: 63 - 87
      Abstract: Publication date: September 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 82
      Author(s): Stefan Fedtke, Nils Boysen
      Rail-rail transshipment yards act as central hub nodes within a railway network and enable a rapid consolidation of containers between different freight trains. To avoid an excessive movement of gantry cranes when transferring a container from one train to another, modern yards apply sorting systems where shuttle cars move containers horizontally along the spread of the yard. This paper compares four elementary sorting systems. Specifically, we compare rubber-tired and rail-mounted shuttles and differentiate whether a pure shuttle system or a lift & shuttle system is applied. In pure shuttle systems, a shuttle receives a container from a crane and transports it towards the destination crane, where it serves as a storage device until being unloaded. A lift & shuttle system applies shuttles with an integrated lifting platform, so that they are able to autonomously store and receive containers from a separate storage rack. Both alternatives exist in rubber-tired and rail-mounted versions. As the shuttles are the main driver of the investment costs, we compare the required fleet size for timely supplying given gantry crane schedules within all four systems. For this purpose, we derive suited scheduling procedures. This way, decision support for yard managers having to identify a suited sorting system and to layout a new terminal is provided.

      PubDate: 2017-07-03T09:56:19Z
      DOI: 10.1016/j.trc.2017.06.012
      Issue No: Vol. 82 (2017)
       
  • Empirics of multi-modal traffic networks – Using the 3D macroscopic
           fundamental diagram
    • Authors: Allister Loder; Lukas Ambühl; Monica Menendez; Kay W. Axhausen
      Pages: 88 - 101
      Abstract: Publication date: September 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 82
      Author(s): Allister Loder, Lukas Ambühl, Monica Menendez, Kay W. Axhausen
      Traffic is multi-modal in most cities. However, the impacts of different transport modes on traffic performance and on each other are unclear – especially at the network level. The recent extension of the macroscopic fundamental diagram (MFD) into the 3D-MFD offers a novel framework to address this gap at the urban scale. The 3D-MFD relates the network accumulation of cars and public transport vehicles to the network travel production, for either vehicles or passengers. No empirical 3D-MFD has been reported so far. In this paper, we present the first empirical estimate of a 3D-MFD at the urban scale. To this end, we use data from loop detectors and automatic vehicle location devices (AVL) of the public transport vehicles in the city of Zurich, Switzerland. We compare two different areas within the city, that differ in their topology and share of dedicated lanes for public transport. We propose a statistical model of the 3D-MFD, which estimates the effects of the vehicle accumulation on car and public transport speeds under multi-modal traffic conditions. The results quantify the effects of both, vehicles and passengers, and confirm that a greater share of dedicated lanes reduces the marginal effects of public transport vehicles on car speeds. Lastly, we derive a new application of the 3D-MFD by identifying the share of public transport users that maximizes the journey speeds in an urban network accounting for all motorized transport modes.

      PubDate: 2017-07-03T09:56:19Z
      DOI: 10.1016/j.trc.2017.06.009
      Issue No: Vol. 82 (2017)
       
  • Nonlinear programming methods based on closed-form expressions for optimal
           train control
    • Authors: Hongbo Ye; Ronghui Liu
      Pages: 102 - 123
      Abstract: Publication date: September 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 82
      Author(s): Hongbo Ye, Ronghui Liu
      This paper proposes a novel approach to solve the complex optimal train control problems that so far cannot be perfectly tackled by the existing methods, including the optimal control of a fleet of interacting trains, and the optimal train control involving scheduling. By dividing the track into subsections with constant speed limit and constant gradient, and assuming the train’s running resistance to be a quadratic function of speed, two different methods are proposed to solve the problems of interest. The first method assumes an operation sequence of maximum traction – speedholding – coasting – maximum braking on each subsection of the track. To maintain the mathematical tractability, the maximum tractive and maximum braking functions are restricted to be decreasing and piecewise-quadratic, based on which the terminal speed, travel distance and energy consumption of each operation can be calculated in a closed-form, given the initial speed and time duration of that operation. With these closed-form expressions, the optimal train control problem is formulated and solved as a nonlinear programming problem. To allow more flexible forms of maximum tractive and maximum braking forces, the second method applies a constant force on each subsection. Performance of these two methods is compared through a case study of the classic single-train control on a single journey. The proposed methods are further utilised to formulate more complex optimal train control problems, including scheduling a subway line while taking train control into account, and simultaneously optimising the control of a leader-follower train pair under fixed- and moving-block signalling systems.

      PubDate: 2017-07-03T09:56:19Z
      DOI: 10.1016/j.trc.2017.06.011
      Issue No: Vol. 82 (2017)
       
  • Semi-autonomous vehicle motor insurance: A Bayesian Network risk transfer
           approach
    • Authors: Barry Sheehan; Finbarr Murphy; Cian Ryan; Martin Mullins; Hai Yue Liu
      Pages: 124 - 137
      Abstract: Publication date: September 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 82
      Author(s): Barry Sheehan, Finbarr Murphy, Cian Ryan, Martin Mullins, Hai Yue Liu
      All developed economies mandate at least third party auto insurance resulting inW a vast global liability industry. The evolution towards semi-autonomous and eventually driverless vehicles will progressively remove the leading cause of vehicle accidents, human error, and significantly lower vehicle accident rates. However, this transition will force a departure from existing actuarial methods requires careful management to ensure risks are correctly assigned. Personal motor insurance lines are anticipated to diminish as liability shifts towards OEMs, tier 1 and 2 suppliers and software developers. Vehicle accident risks will hinge on vehicular characteristics in addition to driver related risks as drivers alternate between autonomous and manual driving modes. This paper proposes a Bayesian Network statistical risk estimation approach that can accommodate changing risk levels and the emergence of new risk structures. We demonstrate the use of this method for a Level 3 semi-autonomous vehicle for two scenarios, one where the driver is in control and one where the vehicle is in control. This approach is especially suited to use telematics data generated from the vehicle inherent technologies. We validate the efficacy of this approach from the perspective of the insurer and discuss how vehicle technology development will require a greater degree of collaboration between the insurance company and the manufacturers in order to develop a greater understanding of the risks semi-autonomous and fully autonomous vehicles.

      PubDate: 2017-07-03T09:56:19Z
      DOI: 10.1016/j.trc.2017.06.015
      Issue No: Vol. 82 (2017)
       
  • Use of ubiquitous probe vehicle data for identifying secondary crashes
    • Authors: Hong Yang; Zhenyu Wang; Kun Xie; Dong Dai
      Pages: 138 - 160
      Abstract: Publication date: September 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 82
      Author(s): Hong Yang, Zhenyu Wang, Kun Xie, Dong Dai
      Secondary crashes are non-recurrent incidents that frequently affect traffic operations and safety. They are an important performance measure in evaluating traffic incident management programs. Although several methods (e.g., static, contour map-based, and shockwave-based) have been introduced to identify secondary crashes, the applications of the existing methods are often limited by their shortcomings such as the needs for extra incident information, assumptions, simplified model structures, etc. As an alternative, this paper aims to develop a new data-driven analysis framework to support the identification of secondary crashes. Unlike existing methods, the proposed approach is concentrated on exploring the untapped potential of ubiquitous probe vehicle data for secondary crash analysis. It consists of three major components: detection of the impact area of a primary crash, estimation of the boundary of the impact area, and identification of secondary crashes within the boundary. The first component uses clustering methods to highlight the congested area induced by a primary crash. The second component develops metaheuristic optimization algorithms to approximate the boundary of the congested area. With the estimated boundary, a novel identification method is introduced to automatically identify secondary crashes within the boundary. The performance of the proposed approach has been tested under a set of simulation scenarios. The test results show that the proposed approach based on the ant colony optimization can best describe the impact area and re-identify up to 95 percent of the simulated crashes. Although the performance of the proposed approach is related to the market penetration rate, the results suggest that a relatively low market penetration rate can already achieve promising performance.
      Graphical abstract image

      PubDate: 2017-10-12T04:16:35Z
      DOI: 10.1016/j.trc.2017.06.016
      Issue No: Vol. 82 (2017)
       
  • Definition of a merging assistant strategy using intelligent vehicles
    • Authors: Riccardo Scarinci; Andreas Hegyi; Benjamin Heydecker
      Pages: 161 - 179
      Abstract: Publication date: September 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 82
      Author(s): Riccardo Scarinci, Andreas Hegyi, Benjamin Heydecker
      In the area of active traffic management, new technologies provide opportunities to improve the use of current infrastructure. Vehicles equipped with in-car communication systems are capable of exchanging messages with the infrastructure and other vehicles. This new capability offers many opportunities for traffic management. This paper presents a novel merging assistant strategy that exploits the communication capabilities of intelligent vehicles. The proposed control requires the cooperation of equipped vehicles on the main carriageway in order to create merging gaps for on-ramp vehicles released by a traffic light. The aim is to reduce disruptions to the traffic flow created by the merging vehicles. This paper focuses on the analytical formulation of the control algorithm, and the traffic flow theories used to define the strategy. The dynamics of the gap formation derived from theoretical considerations are validated using a microscopic simulation. The validation indicates that the control strategy mostly developed from macroscopic theory well approximates microscopic traffic behaviour. The results present encouraging capabilities of the system. The size and frequency of the gaps created on the main carriageway, and the space and time required for their creation are compatible with a real deployment of the system. Finally, we summarise the results of a previous study showing that the proposed merging strategy reduces the occurrence of congestion and the number of late-merging vehicles. This innovative control strategy shows the potential of using intelligent vehicles for facilitating the merging manoeuvre through use of emerging communications technologies.
      Graphical abstract image

      PubDate: 2017-10-12T04:16:35Z
      DOI: 10.1016/j.trc.2017.06.017
      Issue No: Vol. 82 (2017)
       
  • An integrated modelling approach for the bicriterion vehicle routing and
           scheduling problem with environmental considerations
    • Authors: Konstantinos N. Androutsopoulos; Konstantinos G. Zografos
      Pages: 180 - 209
      Abstract: Publication date: September 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 82
      Author(s): Konstantinos N. Androutsopoulos, Konstantinos G. Zografos
      The consideration of pollution in routing decisions gives rise to a new routing framework where measures of the environmental implications are traded off with business performance measures. To address this type of routing decisions, we formulate and solve a bi-objective time, load and path-dependent vehicle routing problem with time windows (BTL-VRPTW). The proposed formulation incorporates a travel time model representing realistically time varying traffic conditions. A key feature of the problem under consideration is the need to address simultaneously routing and path finding decisions. To cope with the computational burden arising from this property of the problem we propose a network reduction approach. Computational tests on the effect of the network reduction approach on determining non-dominated solutions are reported. A generic solution framework is proposed to address the BTL-VRPTW. The proposed framework combines any technique that creates capacity-feasible routes with a routing and scheduling method that aims to convert the identified routes to problem solutions. We show that transforming a set of routes to BTL-VRPTW solutions is equivalent to solving a bi-objective time dependent shortest path problem on a specially structured graph. We propose a backward label setting technique to solve the emerging problem that takes advantage of the special structure of the graph. The proposed generic solution framework is implemented by integrating the routing and scheduling method into an Ant Colony System algorithm. The accuracy of the proposed algorithm was assessed on the basis of its capability to determine minimum travel time and fuel consumption solutions. Although the computational results are encouraging, there is ample room for future research in algorithmic advances on addressing the proposed problem.

      PubDate: 2017-10-12T04:16:35Z
      DOI: 10.1016/j.trc.2017.06.013
      Issue No: Vol. 82 (2017)
       
  • A day-to-day route flow evolution process towards the mixed equilibria
    • Authors: Bojian Zhou; Min Xu; Qiang Meng; Zhongxiang Huang
      Pages: 210 - 228
      Abstract: Publication date: September 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 82
      Author(s): Bojian Zhou, Min Xu, Qiang Meng, Zhongxiang Huang
      This study investigates a travelers’ day-to-day route flow evolution process under a predefined market penetration of advanced traveler information system (ATIS). It is assumed that some travelers equipped with ATIS will follow the deterministic user equilibrium route choice behavior due to the complete traffic information provided by ATIS, while the other travelers unequipped with ATIS will follow the stochastic user equilibrium route choice behavior. The interaction between these two groups of travelers will result in a mixed equilibrium state. We first propose a discrete day-to-day route flow adjustment process for this mixed equilibrium behavior by specifying the travelers’ route adjustment principle and adjustment ratio. The convergence of the proposed day-to-day flow dynamic model to the mixed equilibrium state is then rigorously demonstrated under certain assumptions upon route adjustment principle and adjustment ratio. In addition, without affecting the convergence of the proposed day-to-day flow dynamic model, the assumption concerning the adjustment ratio is further relaxed, thus making the proposed model more appealing in practice. Finally, numerical experiments are conducted to illustrate and evaluate the performance of the proposed day-to-day flow dynamic model.

      PubDate: 2017-10-12T04:16:35Z
      DOI: 10.1016/j.trc.2017.06.018
      Issue No: Vol. 82 (2017)
       
  • Congestion-aware system optimal route choice for shared autonomous
           vehicles
    • Authors: Michael W. Levin
      Pages: 229 - 247
      Abstract: Publication date: September 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 82
      Author(s): Michael W. Levin
      We study the shared autonomous vehicle (SAV) routing problem while considering congestion. SAVs essentially provide a dial-a-ride service to travelers, but the large number of vehicles involved (tens of thousands of SAVs to replace personal vehicles) results in SAV routing causing significant congestion. We combine the dial-a-ride service constraints with the linear program for system optimal dynamic traffic assignment, resulting in a congestion-aware formulation of the SAV routing problem. Traffic flow is modeled through the link transmission model, an approximate solution to the kinematic wave theory of traffic flow. SAVs interact with travelers at origins and destinations. Due to the large number of vehicles involved, we use a continuous approximation of flow to formulate a linear program. Optimal solutions demonstrate that peak hour demand is likely to have greater waiting and in-vehicle travel times than off-peak demand due to congestion. SAV travel times were only slightly greater than system optimal personal vehicle route choice. In addition, solutions can determine the optimal fleet size to minimize congestion or maximize service.

      PubDate: 2017-10-12T04:16:35Z
      DOI: 10.1016/j.trc.2017.06.020
      Issue No: Vol. 82 (2017)
       
  • Experimental and empirical investigations of traffic flow instability
    • Authors: Rui Jiang; Cheng-Jie Jin; H.M. Zhang; Yong-Xian Huang; Jun-Fang Tian; Wei Wang; Mao-Bin Hu; Hao Wang; Bin Jia
      Pages: 157 - 173
      Abstract: Publication date: Available online 6 September 2017
      Source:Transportation Research Part C: Emerging Technologies
      Author(s): Rui Jiang, Cheng-Jie Jin, H.M. Zhang, Yong-Xian Huang, Jun-Fang Tian, Wei Wang, Mao-Bin Hu, Hao Wang, Bin Jia
      Traffic instability is an important but undesirable feature of traffic flow. This paper reports our experimental and empirical studies on traffic flow instability. We have carried out a large scale experiment to study the car-following behavior in a 51-car-platoon. The experiment has reproduced the phenomena and confirmed the findings in our previous 25-car-platoon experiment, i.e., standard deviation of vehicle speeds increases in a concave way along the platoon. Based on our experimental results, we argue that traffic speed rather than vehicle spacing (or density) might be a better indicator of traffic instability, because vehicles can have different spacing under the same speed. For these drivers, there exists a critical speed between 30km/h and 40km/h, above which the standard deviation of car velocity is almost saturated (flat) along the 51-car-platoon, indicating that the traffic flow is likely to be stable. In contrast, below this critical speed, traffic flow is unstable and can lead to the formation of traffic jams. Traffic data from the Nanjing Airport Highway support the experimental observation of existence of a critical speed. Based on these findings, we propose an alternative mechanism of traffic instability: the competition between stochastic factors and the so-called speed adaptation effect, which can better explain the concave growth of speed standard deviation in traffic flow.

      PubDate: 2017-09-08T17:05:16Z
      DOI: 10.1016/j.trpro.2017.05.010
      Issue No: Vol. 23 (2017)
       
  • Data-driven spatio-temporal discretization for pedestrian flow
           characterization
    • Authors: Marija Nikolić; Michel Bierlaire
      Pages: 188 - 207
      Abstract: Publication date: Available online 6 September 2017
      Source:Transportation Research Part C: Emerging Technologies
      Author(s): Marija Nikolić, Michel Bierlaire
      We propose a novel approach to pedestrian flow characterization. The definitions of density, flow and velocity existing in the literature are extended through a data-driven spatio-temporal discretization framework. The framework is based on three-dimensional Voronoi diagrams. Synthetic data is used to empirically investigate the performance of the approach and to illustrate its advantages. Our approach outperforms the considered approaches from the literature in terms of the robustness with respect to the simulation noise and with respect to the sampling frequency. Additionally, the proposed approach is by design (i) independent from an arbitrarily chosen discretization; (ii) appropriate for the multidirectional composition of pedestrian traffic; (iii) able to reflect the heterogeneity of the pedestrian population; and (iv) applicable to pedestrian trajectories described either analytically or as a sample of points.

      PubDate: 2017-09-08T17:05:16Z
      DOI: 10.1016/j.trpro.2017.05.012
      Issue No: Vol. 23 (2017)
       
  • Macroscopic Fundamental Diagram for pedestrian networks: Theory and
           applications
    • Authors: Serge P. Hoogendoorn; Winnie Daamen; Victor L. Knoop; Jeroen Steenbakkers; Majid Sarvi
      Pages: 480 - 496
      Abstract: Publication date: Available online 18 September 2017
      Source:Transportation Research Part C: Emerging Technologies
      Author(s): S.P. Hoogendoorn, W. Daamen, V.L. Knoop, J. Steenbakkers, M. Sarvi
      The Network or Macroscopic Fundamental diagram (MFD) has been a topic receiving a lot of attention in the past decade. Both from a theoretical angle and from a more application-oriented perspective, the MFD has proven to be a powerful concept in understanding and managing vehicular network dynamics. In particular, the application in traffic management has inspired the research presented in this contribution, where we explore the existence and the characteristics of the pedestrian Macroscopic Fundamental Diagram (p-MFD). This is first of all done from a theoretical perspective, which results in the main contribution of this research showing how we can derive the p-MFD from assumed local fundamental diagrams (FDs). In doing so, we show that we can relate the average (out-)flow from a pedestrian network as a function of the average spatial density ρ ¯ and the density spatial variation σ 2 . We show that the latter is essential to provide a reasonable description of the overall network conditions. For simple relations between density and speed (i.e. Greenshields and Underwood fundamental diagrams), we derive analytical results; for more commonly used FDs in pedestrian flow theory, such as the triangular FD of Newell or the FD of Weidmann, we show the resulting relation by proposing a straightforward simulation approach. As a secondary contribution of the paper, we show how the p-MFD can be constructed from pedestrian trajectory data stemming from either microsimulation or from experimental studies. We argue that the results found are in line with the theoretical results, providing further evidence for the validity of the p-MFD concept. We furthermore discuss concepts of hysteresis, also observed in vehicular network dynamics, due to the differences in the queue build up and recuperation phases. We finally present some applications of the presented concepts in crowd management, network level-of-service determination, and coarse-scale modelling.

      PubDate: 2017-09-20T20:16:54Z
      DOI: 10.1016/j.trpro.2017.05.027
      Issue No: Vol. 23 (2017)
       
  • An optimization approach for deriving upper and lower bounds of
           transportation network vulnerability under simultaneous disruptions of
           multiple links
    • Authors: Xiangdong Xu; Anthony Chen; Chao Yang
      Pages: 645 - 663
      Abstract: Publication date: Available online 8 September 2017
      Source:Transportation Research Part C: Emerging Technologies
      Author(s): Xiangdong Xu, Anthony Chen, Chao Yang
      This paper aims to develop an optimization approach for deriving the upper and lower bounds of transportation network vulnerability under simultaneous disruptions of multiple links without the need to evaluate all possible combinations as in the enumerative approach. Mathematically, we formulate the upper and lower bounds of network vulnerability asa binary integer bi-level program (BLP). The upper-level subprogram maximizes or minimizes the remaining network throughput under a given number of disrupted links, which corresponds to the upper and lower vulnerability bounds. The lower-level subprogram checks the connectivity of each origin-destination (O-D) pair under a network disruption scenario without path enumeration. Two alternative modeling approaches are provided for the lower-level subprogram: the virtual link capacity-based maximum flow problem formulation and the virtual link cost-based shortest path problem formulation. Computationally, the BLP model can be equivalently reformulated asa single-level mixed integer linear program by making use of the optimality conditions of the lower-level subprograms and linearization techniques for the complementarity conditions and bilinear terms. Numerical examples are also provided to systematically demonstrate the validity, capability, and flexibility of the proposed optimization model. The vulnerability envelope constructed by the upper and lower bounds is able to effectively consider all possible combinations without the need to perform a full network scan, thus avoiding the combinatorial complexity of enumerating multi-disruption scenarios. Using the vulnerability envelope asa network performance assessment tool, planners and managers can more cost-effectively plan for system protection against disruptions, and prioritize system improvements to minimize disruption risks with limited resources.

      PubDate: 2017-09-08T17:05:16Z
      DOI: 10.1016/j.trpro.2017.05.036
      Issue No: Vol. 23 (2017)
       
  • Exploration of day-to-day route choice models by a virtual experiment
    • Authors: Hongbo Ye; Feng Xiao; Hai Yang
      Pages: 679 - 699
      Abstract: Publication date: Available online 6 September 2017
      Source:Transportation Research Part C: Emerging Technologies
      Author(s): Hongbo Ye, Feng Xiao, Hai Yang
      This paper examines existing day-to-day models based on a virtual day-to-day route choice experiment using the latest mobile Internet technologies. With the realized day-to-day path flows and path travel times in the experiment, we calibrate several well-designed path-based day-to-day models that take the Wardrop’s user equilibrium as (part of) their stationary states. The nonlinear effects of path flows and path time differences on path switching are then investigated. Participants’ path preferences, time-varying sensitivity, and learning behavior in the day-to-day process are also examined. The prediction power of various models with various settings (nonlinear effects, time-varying sensitivity, and learning) is compared. The assumption of “rational behavior adjustment process” in Yang and Zhang (2009) is further verified. Finally, evolutions of different Lyapunov functions used in the literature are plotted, and no obvious diversity is observed.

      PubDate: 2017-09-08T17:05:16Z
      DOI: 10.1016/j.trpro.2017.05.038
      Issue No: Vol. 23 (2017)
       
  • Network-oriented household activity pattern problem for system
           optimization
    • Authors: Jiangtao Liu; Jee Eun Kang; Xuesong Zhou; Ram Pendyala
      Pages: 827 - 847
      Abstract: Publication date: Available online 19 September 2017
      Source:Transportation Research Part C: Emerging Technologies
      Author(s): Jiangtao Liu, Jee Eun Kang, Xuesong Zhou, Ram Pendyala
      The recently emerging trend of self-driving vehicles and information sharing technologies, made available by private technology vendors, starts creating a revolutionary paradigm shift in the coming years for traveler mobility applications. By considering a deterministic traveler decision making framework at the household level in congested transportation networks, this paper aims to address the challenges of how to optimally schedule individuals’ daily travel patterns under the complex activity constraints and interactions. We reformulate two special cases of household activity pattern problem (HAPP) through a high-dimensional network construct, and offer a systematic comparison with the classical mathematical programming models proposed by Recker (1995). Furthermore, we consider the tight road capacity constraint asanother special case of HAPP to model complex interactions between multiple household activity scheduling decisions, and this attempt offers another household-based framework for linking activity-based model (ABM) and dynamic traffic assignment (DTA) tools. Through embedding temporal and spatial relations among household members, vehicles and mandatory/optional activities in an integrated space-time-state network, we develop two 0–1 integer linear programming models that can seamlessly incorporate constraints for a number of key decisions related to vehicle selection, activity performing and ridesharing patterns under congested networks. The well-structured network models can be directly solved by standard optimization solvers, and further converted to a set of time-dependent state-dependent least cost path-finding problems through Lagrangian relaxation, which permit the use of computationally efficient algorithms on large-scale high-fidelity transportation networks.

      PubDate: 2017-09-20T20:16:54Z
      DOI: 10.1016/j.trpro.2017.05.046
      Issue No: Vol. 23 (2017)
       
  • Privacy-preserving MaaS fleet management
    • Authors: Francois Belletti; Alexandre M. Bayen
      Pages: 1000 - 1024
      Abstract: Publication date: Available online 18 September 2017
      Source:Transportation Research Part C: Emerging Technologies
      Author(s): Francois Belletti, Alexandre M. Bayen
      On-demand traffic fleet optimization requires operating Mobility as a Service (MaaS) companies such as Uber, Lyft to locally match the offer of available vehicles with their expected number of requests referred to as demand (as well as to take into account other constraints such as driver’s schedules and preferences). In the present article, we show that this problem can be encoded into a Constrained Integer Quadratic Program (CIQP) with block independent constraints that can then be relaxed in the form of a convex optimization program. We leverage this particular structure to yield a scalable distributed optimization algorithm corresponding to computing a gradient ascent in a dual space. This new framework does not require the drivers to share their availabilities with the operating company (as opposed to standard practice in today’s mobility as a service companies). The resulting parallel algorithm can run on a distributed smartphone based platform.

      PubDate: 2017-09-20T20:16:54Z
      DOI: 10.1016/j.trpro.2017.05.055
      Issue No: Vol. 23 (2017)
       
  • Truck platooning on uphill grades under cooperative adaptive cruise
           control (CACC)
    • Authors: Danjue Chen; Soyoung Ahn; Madhav Chitturi; David Noyce
      Pages: 1059 - 1078
      Abstract: Publication date: Available online 7 September 2017
      Source:Transportation Research Part C: Emerging Technologies
      Author(s): Danjue Chen, Soyoung Ahn, Madhav Chitturi, David Noyce
      This paper examines CACC truck platooning on uphill grades. It was found that the design of CT policy should consider the effects of low crawl speeds on significant upgrades. Three simple solutions, which have different impacts on traffic flow efficiency, are proposed. Furthermore, truck platoons, controlled by a state-of-the-art CACC model, become asymptotically unstable beyond some critical grade. The errors are permanent, suggesting that trucks fail to re-engage after the upgrade. This occurs by complex interactions between the CACC control and the bounded acceleration capabilities of trucks. New control concepts are developed to complement the existing control model and achieve asymptotic (and string) stability. The instability mechanisms and new control concepts are not specific to the control model used.

      PubDate: 2017-09-08T17:05:16Z
      DOI: 10.1016/j.trpro.2017.05.058
      Issue No: Vol. 23 (2017)
       
  • Potentials of using social media to infer the longitudinal travel
           behavior: A sequential model-based clustering method
    • Abstract: Publication date: December 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 85
      Author(s): Zhenhua Zhang, Qing He, Shanjiang Zhu
      This study explores the possibility of employing social media data to infer the longitudinal travel behavior. The geo-tagged social media data show some unique features including location-aggregated features, distance-separated features, and Gaussian distributed features. Compared to conventional household travel survey, social media data is less expensive, easier to obtain and the most importantly can monitor the individual’s longitudinal travel behavior features over a much longer observation period. This paper proposes a sequential model-based clustering method to group the high-resolution Twitter locations and extract the Twitter displacements. Further, this study details the unique features of displacements extracted from Twitter including the demographics of Twitter user, as well as the advantages and limitations. The results are even compared with those from traditional household travel survey, showing promises in using displacement distribution, length, duration and start time to infer individual’s travel behavior. On this basis, one can also see the potential of employing social media to infer longitudinal travel behavior, as well as a large quantity of short-distance Twitter displacements. The results will supplement the traditional travel survey and support travel behavior modeling in a metropolitan area.

      PubDate: 2017-10-18T15:03:05Z
       
  • A comparative study of aviation safety briefing media: card, video, and
           video with interactive controls
    • Abstract: Publication date: December 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 85
      Author(s): Luca Chittaro
      Passengers’ safety knowledge is a key factor in determining the chance of surviving any life- or injury-threatening situation that could occur in civil aviation. Aviation regulations require airlines to provide safety briefings to inform passengers of safety procedures on board. The safety briefing card and the safety briefing video are the two media that airlines routinely employ on board to this purpose. Unfortunately, research on aviation safety briefing media has cast serious doubts about their efficacy, urging researchers to better understand what makes safety briefing media effective as well as improving their effectiveness. This paper contributes to such goals in two different ways. First, it proposes the introduction of interactive technology into aviation safety briefings for improving their effectiveness. Second, it illustrates a controlled study that compares the effectiveness of three safety briefing media: the two briefing media that airlines currently employ on-board (safety briefing card and safety briefing video) and a safety briefing video extended with basic interactive controls. The results obtained by the study highlight a superior effectiveness of the two video media over the card media for aviation safety briefings. Moreover, the video with interactive controls produced improvements over the card in a larger number of effectiveness measures than the traditional video. The paper includes a discussion of factors that can explain the better results obtained with the video conditions, and in particular the video with interactive controls, and of possible additional extensions to increase the interactivity of aviation safety briefings.

      PubDate: 2017-10-18T15:03:05Z
       
  • Variable speed limit design based on mode dependent Cell Transmission
           Model
    • Abstract: Publication date: December 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 85
      Author(s): Alfréd Csikós, Balázs Kulcsár
      In this paper a mode dependent variable speed limit (VSL) control strategy is developed for motorway networks. The suggested rolling horizon and coordinated algorithm uses switching mode Cell Transmission Model (CTM) and purports to maximize network throughput. In this line, first, a VSL signal scheduled piecewise affine switching mode CTM is derived based on the polyhedral description of Godunov fluxes. Second, a two-stage, coordinated, rolling horizon VSL sequence generation procedure is proposed. The set of possible VSL signs is selected by applying input constraints in order to eliminate spatial and temporal VSL oscillations. Then, the set of modes is further reduced according to the stable and adjacent reachable modes of the switching mode CTM. Over the remaining set of input signals, network capacity is maximized with the help of solving a mixed integer optimization problem under the form of reference density tracking objective. The method is implemented in simulation environment to demonstrate its computational efficiency and viability to attenuate shockwaves.

      PubDate: 2017-10-18T15:03:05Z
       
  • Modeling origin-destination uncertainty using network sensor and survey
           data and new approaches to robust control
    • Authors: Lee K. Jones; Nathan H. Gartner; Mikhail Shubov; Chronis Stamatiadis; David Einstein
      Abstract: Publication date: Available online 15 September 2017
      Source:Transportation Research Part C: Emerging Technologies
      Author(s): Lee K. Jones, Nathan H. Gartner, Mikhail Shubov, Chronis Stamatiadis, David Einstein
      This study develops new methods for network assessment and control by taking explicit account of demand variability and uncertainty using partial sensor and survey data while imposing equilibrium conditions during the data collection phase. The methods consist of rules for generating possible origin–destination (OD) matrices and the calculation of average and quantile network costs. The assessment methodology leads to improved decision-making in transport planning and operations and is used to develop management and control strategies that result in more robust network performance. Specific contributions in this work consist of: (a) Characterization of OD demand variability, specifically with or without equilibrium assumptions during data collection; (b) exhibiting the highly disconnected nature of OD space demonstrating that many current approaches to the problem of optimal control may be computationally intractable; (c) development of feasible Monte Carlo procedures for the generation of possible OD matrices used in an assessment of network performance; and (d) calculation of robust network controls, with state-of-the-art cost estimation, for the following strategies: Bayes, p-quantile and NBNQ (near-Bayes near-Quantile). All strategies involve the simultaneous calculation of controls and equilibrium conditions. A numerical example for a moderate sized network is presented where it is shown that robust controls can provide approx. 20% cost reduction.

      PubDate: 2017-09-20T20:16:54Z
      DOI: 10.1016/j.trc.2017.09.007
       
  • Editorial Board/Copyright Information
    • Abstract: Publication date: October 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 83


      PubDate: 2017-09-03T02:26:45Z
       
  • Editorial Board/Copyright Information
    • Abstract: Publication date: September 2017
      Source:Transportation Research Part C: Emerging Technologies, Volume 82


      PubDate: 2017-08-03T07:02:01Z
       
 
 
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