109 results found
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
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
Wong N, Escribano-Macias J, Han K, et al., Rapid urban evacuation across constrained transport networks, Transportation Research Board 96th Annual Meeting
Han K, Traffic operation facilitated by telecommunication: Some case studies, Washington DC, Transportation Research Board 96th Annual Meeting
This paper focuses on the aspects of traffic management facilitated by modern telecommunication technologies and advanced real-time optimization algorithms. The discussion begins with a recent European project, which provides a real-time decision support system for the reduction of traffic congestion and emissions. The workflow and techniques involved therein are explained, with issues and potential gaps identified. We then move on to a more abstract yet general real-time decision-making framework based on decision rules and distributionally robust optimization. The author’s experience with such a framework is illustrated with several applications, including responsive signal control, adaptive variable message sign, and air traffic management. Finally, this paper ends with some discussions of the opportunities brought, as well as challenges posed, by the increasing capacity and diversity of telecommunication.
Wu F, Stern R, Churchill M, et al., Fuel consumption in oscillatory traffic: experimental results, Transportation Research Board 96th Annual Meeting
Song J, Hu J, Han K, Real-time adaptive traﬃc signal control: Trade-oﬀ between traﬃc and environmental objectives, Transportation Research Board 96th Annual Meeting
Xu Y, Yin S, Dalmau R, et al., Linear holding for reducing additional delays experienced by ﬂights subject to ground holding at no extra fuel cost, Transportation Research Board 96th Annual Meeting
Yin S, Han K, Yang L, et al., Oﬀ-block ﬂow optimization based on cell transmission model for mitigating departure traffic congestion at airport surface, Transportation Research Board 96th Annual Meeting
Pien KC, Han K, Majumdar A, A linear programming approach for system-optimal dynamic traffic assignment in the European Air Traffic Network, Transportation Research Board 96th Annual Meeting
Song J, Jiang C, Han K, et al., Research on visible sensing recognition linkage model & decision support system for PM2.5 distribution in road network: A case study of Chengdu area, Washington DC, USA, Transportation Research Board Annual Meeting
Han K, Liu H, Gayah VV, et al., 2016, A robust optimization approach for dynamic traffic signal control with emission considerations, Pages: 3-26, ISSN: 0968-090X
© 2015 Elsevier Ltd We consider an analytical signal control problem on a signalized network whose traffic flow dynamic is described by the Lighthill–Whitham–Richards (LWR) model (Lighthill and Whitham, 1955; Richards, 1956). This problem explicitly addresses traffic-derived emissions as constraints or objectives. We seek to tackle this problem using a mixed integer mathematical programming approach. Such class of problems, which we call LWR-Emission (LWR-E), has been analyzed before to certain extent. Since mixed integer programs are practically efficient to solve in many cases (Bertsimas et al., 2011b), the mere fact of having integer variables is not the most significant challenge to solving LWR-E problems; rather, it is the presence of the potentially nonlinear and nonconvex emission-related constraints/objectives that render the program computationally expensive. To address this computational challenge, we proposed a novel reformulation of the LWR-E problem as a mixed integer linear program (MILP). This approach relies on the existence of a statistically valid macroscopic relationship between the aggregate emission rate and the vehicle occupancy on the same link. This relationship is approximated with certain functional forms and the associated uncertainties are handled explicitly using robust optimization (RO) techniques. The RO allows emissions-related constraints and/or objectives to be reformulated as linear forms under mild conditions. To further reduce the computational cost, we employ a link-based LWR model to describe traffic dynamics with the benefit of fewer (integer) variables and less potential traffic holding. The proposed MILP explicitly captures vehicle spillback, avoids traffic holding, and simultaneously minimizes travel delay and addresses emission-related concerns.
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.
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
Friesz T, Han K, 2016, Computing dynamic user equilibria in continuous time, 6th International Symposium on Dynamic Traffic Assignment
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
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
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
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
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
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
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).
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
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
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
Han K, Piccoli B, Friesz TL, 2015, Continuity of the path delay operator for dynamic network loading with spillback, Transportation Research Part B - Methodological, Vol: 92, Pages: 211-233, ISSN: 0191-2615
This paper establishes the continuity of the path delay operators for dynamic network loading (DNL) problems based on the Lighthill–Whitham–Richards model, which explicitly capture vehicle spillback. The DNL describes and predicts the spatial-temporal evolution of traffic flow and congestion on a network that is consistent with established route and departure time choices of travelers. The LWR-based DNL model is first formulated as a system of partial differential algebraic equations. We then investigate the continuous dependence of merge and diverge junction models with respect to their initial/boundary conditions, which leads to the continuity of the path delay operator through the wave-front tracking methodology and the generalized tangent vector technique. As part of our analysis leading up to the main continuity result, we also provide an estimation of the minimum network supply without resort to any numerical computation. In particular, it is shown that gridlock can never occur in a finite time horizon in the DNL model.
Pien K-C, Han K, Shang W, et al., 2015, Robustness analysis of the European air traffic network, TRANSPORTMETRICA A-TRANSPORT SCIENCE, Vol: 11, Pages: 772-792, ISSN: 2324-9935
Wang Y, Liu H, Han K, et al., Day-to-day congestion pricing and network resilience, Transportation Research Board 95th Annual Meeting
Shang W, Han K, Ochieng W, An agent-based day-to-day traffic evolution model using percolation theory, Transportation Research Board 95th Annual Meeting, Publisher: Transportation Research Board
This data is extracted from the Web of Science and reproduced under a licence from Thomson Reuters. You may not copy or re-distribute this data in whole or in part without the written consent of the Science business of Thomson Reuters.