95 results found
Chen D, Hu M, Zhang H, et al., 2017, A network based dynamic air traffic flow model for en route airspace system traffic flow optimization, TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW, Vol: 106, Pages: 1-19, ISSN: 1366-5545
Han K, 2017, Framework for Real-Time Traffic Management with Case Studies, TRANSPORTATION RESEARCH RECORD, Pages: 35-43, ISSN: 0361-1981
Liu J, Li K, Yin M, et al., 2017, Optimizing Key Parameters of Ground Delay Program with Uncertain Airport Capacity, JOURNAL OF ADVANCED TRANSPORTATION, ISSN: 0197-6729
Qin F, Sun R, Ochieng WY, et al., 2017, Integrated GNSS/DR/road segment information system for variable road user charging, TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, Vol: 82, Pages: 261-272, ISSN: 0968-090X
Shang W, Han K, Ochieng W, et al., 2017, Agent-based day-to-day traffic network model with information percolation, TRANSPORTMETRICA A-TRANSPORT SCIENCE, Vol: 13, Pages: 38-66, ISSN: 2324-9935
Sidiropoulos S, Han K, Majumdar A, et al., 2017, Robust identification of air traffic flow patterns in Metroplex terminal areas under demand uncertainty, TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, Vol: 75, Pages: 212-227, ISSN: 0968-090X
Song W, Han K, Wang Y, et al., 2017, Statistical metamodeling of dynamic network loading, 22nd International Symposium on Transportation and Traffic Theory (ISTTT), Publisher: ELSEVIER SCIENCE BV, Pages: 263-282, ISSN: 2352-1465
Song W, Han K, Wang Y, et al., 2017, Statistical metamodeling of dynamic network loading, Transportation Research Procedia, Vol: 23, Pages: 263-282, ISSN: 2352-1465
Song W, Han K, Wang Y, et al., 2017, Statistical metamodeling of dynamic network loading, ISSN: 0191-2615
© 2017. Dynamic traffic assignment models rely on a network performance module known as dynamic network loading (DNL), which expresses flow propagation, flow conservation, and travel delay at a network level. The DNL defines the so-called network delay operator, which maps a set of path departure rates to a set of path travel times (or costs). It is widely known that the delay operator is not available in closed form, and has undesirable properties that severely complicate DTA analysis and computation, such as discontinuity, non-differentiability, non-monotonicity, and computational inefficiency. This paper proposes a fresh take on this important and difficult issue, by providing a class of surrogate DNL models based on a statistical learning method known as Kriging. We present a metamodeling framework that systematically approximates DNL models and is flexible in the sense of allowing the modeler to make trade-offs among model granularity, complexity, and accuracy. It is shown that such surrogate DNL models yield highly accurate approximations (with errors below 8%) and superior computational efficiency (9 to 455 times faster than conventional DNL procedures such as those based on the link transmission model). Moreover, these approximate DNL models admit closed-form and analytical delay operators, which are Lipschitz continuous and infinitely differentiable, with closed-form Jacobians. We provide in-depth discussions on the implications of these properties to DTA research and model applications.
Song W, Han K, Wang Y, et al., 2017, Statistical metamodeling of dynamic network loading, Transportation Research Part B: Methodological, ISSN: 0191-2615
Yang L, Yin S, Han K, et al., 2017, Fundamental diagrams of airport surface traffic: Models and applications, Transportation Research Part B: Methodological, Vol: 106, Pages: 29-51, ISSN: 0191-2615
This paper reveals and explores the flow characteristics of airport surface network on both mesoscopic and macroscopic levels. We propose an efficient modeling approach based on the cell transmission model for simulating the spatio-temporal evolution of flow and congestion on taxiway and apron networks. The existence of link-based fundamental diagram that expresses the functional relationship between link density and flow is demonstrated using empirical data collected in Guangzhou Baiyun airport. The proposed CTM-based network model is shown to be an efficient and accurate method capable of supporting air traffic prediction and decision support. In addition, using both CTM-based simulation and empirical data, we further reveal the existence of an aggregate relationship between traffic density and runway throughput, which is referred to as macroscopic fundamental diagram (MFD) in the literature of road traffic. The MFD on the airport surface is analyzed in depth, and utilized to devise several robust off-block control strategies under uncertainties, which are shown to significantly outperform existing off-block control methods.
Yang L, Yin S, Hu M, et al., 2017, Empirical exploration of air traffic and human dynamics in terminal airspaces, TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, Vol: 84, Pages: 219-244, ISSN: 0968-090X
Yu C, Ma W, Han K, et al., 2017, Optimization of vehicle and pedestrian signals at isolated intersections, TRANSPORTATION RESEARCH PART B-METHODOLOGICAL, Vol: 98, Pages: 135-153, ISSN: 0191-2615
Chen D, Hu M, Han K, et al., 2016, Short/medium-term prediction for the aviation emissions in the en route airspace considering the fluctuation in air traffic demand, Transportation Research Part D: Transport and Environment, Vol: 48, Pages: 46-62, ISSN: 1361-9209
This paper proposes a novel short/medium-term prediction method for aviation emissions distribution in en route airspace. An en route traffic demand model characterizing both the dynamics and the fluctuation of the actual traffic demand is developed, based on which the variation and the uncertainty of the short/medium-term traffic growth are predicted. Building on the demand forecast the Boeing Fuel Flow Method 2 is applied to estimate the fuel consumption and the resulting aviation emissions in the en route airspace. Based on the traffic demand prediction and the en route emissions estimation, an aviation emissions prediction model is built, which can be used to forecast the generation of en route emissions with uncertainty limits. The developed method is applied to a real data set from Hefei Area Control Center for the en route emission prediction in the next 5 years, with time granularities of both months and years. To validate the uncertainty limits associated with the emission prediction, this paper also presents the prediction results based on future traffic demand derived from the regression model widely adopted by FAA and Eurocontrol. The analysis of the case study shows that the proposed method can characterize well the dynamics and the fluctuation of the en route emissions, thereby providing satisfactory prediction results with appropriate uncertainty limits. The prediction results show a gradual growth at an average annual rate of 7.74%, and the monthly prediction results reveal distinct fluctuation patterns in the growth.
Chow A, Chan L, Han K, et al., 2016, Agent-based modelling of transport network vulnerability and resilience, 6th International Symposium on Dynamic Traffic Assignment
Friesz T, Han K, 2016, Computing dynamic user equilibria in continuous time, 6th International Symposium on Dynamic Traffic Assignment
Garavello M, Han K, Piccoli B, 2016, Models for Vehicular Traffic on Networks, Publisher: American Institute of Mathematical Sciences, ISBN: 978-1-60133-019-2
Han K, Friesz T, Wang Y, et al., 2016, Infrastructure maintenance with day-to-day traffic dynamics and transient congestion, 6th International Symposium on Dynamic Traffic Assignment
Han K, Liu H, Gayah VV, et al., 2016, A robust optimization approach for dynamic traffic signal control with emission considerations, Publisher: PERGAMON-ELSEVIER SCIENCE LTD, Pages: 3-26, ISSN: 0968-090X
Jiang Y, Szeto WY, Long J, et al., 2016, Multi-class dynamic traffic assignment with physical queues: intersection-movement-based formulation and paradox, TRANSPORTMETRICA A-TRANSPORT SCIENCE, Vol: 12, Pages: 878-908, ISSN: 2324-9935
Jiang Y, Szeto WY, Long J, et al., 2016, Multi-class dynamic traffic assignment with physical queues: Intersection-movement-based formulation and paradox, 6th International Symposium on Dynamic Traffic Assignment
Mascia M, Hu J, Han K, et al., 2016, Impact of traffic management on black carbon emissions: a microsimulation study, Networks & Spatial Economics, Vol: 17, Pages: 269-291, ISSN: 1572-9427
This paper investigates the effectiveness of traffic management tools, includ- ing traffic signal control and en-route navigation provided by variable message signs (VMS), in reducing traffic congestion and associated emissions of CO2, NOx, and black carbon. The latter is among the most significant contributors of climate change, and is associated with many serious health problems. This study combines traffic microsimulation (S-Paramics) with emission modeling (AIRE) to simulate and predict the impacts of different traffic management measures on a number traffic and environmental Key Performance Indicators (KPIs) assessed at different spatial levels. Simulation results for a real road network located in West Glasgow suggest that these traffic management tools can bring a reduction in travel delay and BC emission respectively by up to 6 % and 3 % network wide. The improvement at local levels such as junctions or corridors can be more significant. However, our results also show that the potential benefits of such interventions are strongly dependent on a number of factors, including dynamic demand profile, VMS compliance rate, and fleet composition. Extensive discussion based on the simulation results as well as managerial insights are provided to support traffic network operation and control with environmental goals. The study described by this paper was conducted under the support of the FP7-funded CARBOTRAF project.
Mascia M, Hu S, Han K, et al., 2016, A holistic approach for performance assessment of personal rapid transit, RESEARCH IN TRANSPORTATION BUSINESS AND MANAGEMENT, Vol: 18, Pages: 70-76, ISSN: 2210-5395
Neto PA, Friesz TL, Han K, 2016, Electric Power Network Oligopoly as a Dynamic Stackelberg Game, NETWORKS & SPATIAL ECONOMICS, Vol: 16, Pages: 1211-1241, ISSN: 1566-113X
Sidiropoulos S, Han K, Majumdar A, et al., 2016, Identifying significant traffic flow patterns in Multi-Airport systems terminal manoeuvring areas under uncertainty
© 2016 American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved. Multi-Airport Systems (MAS), or Metroplex, serve air traffic demand in large metropolitan aeras such as New York, London and Tokyo. Due to the spatial proximity of the airports, Metroplex airspaces are characterized by high complexity and heavy traffic; and current system structures fail to make optimal use of the available spatio-temporal airspace resources. To increase the operational efficiency in such systems, an accurate depiction of the dominant demand patterns over the operational horizon is a prerequisite. This paper proposes a framework for the robust identification of significant air traffic flow patterns in Metroplex systems. The framework is in alignmemt with the Dynamic Route service policy for the effective management of Metroplex operations. A deterministic demand modeling approach is presented first, which takes into account the spatio-temporal changes in demand over the planning horizon of operations for the identification of significant traffic flow patterns. To handle uncertainties in the demand, a Distributionally Robust Optimization (DRO) approach is then proposed, which takes into account historical information regarding both prediction and realization of the traffic demand. Prediction errors are taken into account in a tractable and robust way to ensure the reliability of the optimized control. The DRO approach is applied to decision making in a tactical context (i.e. one-day planning) and on a rolling horizon basis (i.e. every 2 hours). The framework is applied to Time Based Flow Management (TBFM) data for the New York Metroplex (N90). The framework and results are validated by Subject Matter Experts (SMEs) from the Port Authority of New York and New Jersey (PANYNJ).
Sun R, Han K, Hu J, et al., 2016, An Integrated Algorithm Based on BeiDou/GPS/IMU and its Application for Anomalous Driving Detection, 29th International Technical Meeting of The-Satellite-Division-of-the-Institute-of-Navigation (ION GNSS+), Publisher: INST NAVIGATION, Pages: 1885-1890, ISSN: 2331-5911
Sun R, Han K, Hu J, et al., 2016, Integrated solution for anomalous driving detection based on BeiDou/GPS/IMU measurements, TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, Vol: 69, Pages: 193-207, ISSN: 0968-090X
Wang Y, Bu J, Han K, et al., 2016, A novel network approach to study communication activities of air traffic controllers, TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, Vol: 68, Pages: 369-388, ISSN: 0968-090X
Zhao J, Ma W, Liu Y, et al., 2016, Optimal operation of freeway weaving segment with combination of lane assignment and on-ramp signal control, TRANSPORTMETRICA A-TRANSPORT SCIENCE, Vol: 12, Pages: 413-435, ISSN: 2324-9935
Han K, Friesz TL, Szeto WY, et al., 2015, Elastic demand dynamic network user equilibrium: Formulation, existence and computation, TRANSPORTATION RESEARCH PART B-METHODOLOGICAL, Vol: 81, Pages: 183-209, ISSN: 0191-2615
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