100 results found
Fu Z, Jia Q, Chen J, et al., 2018, A fine discrete field cellular automaton for pedestrian dynamics integrating pedestrian heterogeneity, anisotropy, and time-dependent characteristics, Transportation Research Part C: Emerging Technologies, Vol: 91, Pages: 37-61, ISSN: 0968-090X
© 2018 Elsevier Ltd This paper proposes a discrete field cellular automaton (CA) model that integrates pedestrian heterogeneity, anisotropy, and time-dependent characteristics. The pedestrian movement direction, moving/staying, and steering are governed by the transfer equations. Compared with existing studies on fine-discretized CA models, the proposed model is advantageous in terms of flexibility, higher spatial accuracy, wider speed range, relatively low computational cost, and elaborated conflict resolution with synchronous update scheme. Three different application scenarios are created by adjusting the definite conditions of the model: (1) The first one is a unidirectional pedestrian movement in a channel, where a complete jam in the high-density region is observed from the proposed model, which is missing from existing floor field CA models. (2) The second one is evacuation from a room, where the evacuation time is independent of the discretization factor, which is different from previous work. (3) The third one is an ascending evacuation through a 21-storey stair system, where pedestrians move with constant speed or with fatigue. The evacuation time in the latter case is nearly twice of that in the former.
Sidiropoulos S, Majumdar A, Han K, 2018, A framework for the optimization of terminal airspace operations in Multi-Airport Systems, Transportation Research Part B: Methodological, Vol: 110, Pages: 160-187, ISSN: 0191-2615
Major cities like London, New York, and Tokyo are served by several airports, effectively creating a Multi-Airport System (MAS), or Metroplex. The operations of individual Metroplex airports are highly interdependent, rendering their efficient management rather difficult. This paper proposes a framework for the design of dynamic arrival and departure routes in MAS Terminal Maneuvering Areas, which fundamentally changes the operation in MAS airspaces for much improved efficiency when compared to the current situation. The framework consists of three components. The first presents a new procedure for characterizing dynamic arrival and departure routes based on the spatio-temporal distributions of flights. The second component is a novel Analytic Hierarchy Process (AHP) model for the prioritization of the dynamic routes, which takes into account a set of quantitative and qualitative attributes important for MAS operations. The third component is a priority-based method for the positioning of terminal waypoints as well as the design of three-dimensional, conflict-free terminal routes. Such a method accounts for the AHP-derived priorities while satisfying the minimal separation and aircraft maneuverability constraints. The developed framework is applied to a case study of the New York Metroplex, using aircraft trajectories during a heavy traffic period on typical day of operation in the New York Terminal Control Area in November 2011. The proposed framework is quantitatively assessed using the AirTOp fast-time simulation model. The results suggest significant improvements of the new design over the existing one, as measured by several key performance indicators such as travel distance, travel time, fuel burn, and controller workload. The operational feasibility of the framework is further validated qualitatively by subject matter experts from the Port Authority of New York and New Jersey, the operator of the New York Metroplex.
Wang Y, Szeto WY, Han K, et al., 2018, Dynamic traffic assignment: A review of the methodological advances for environmentally sustainable road transportation applications, Transportation Research Part B: Methodological, Vol: 111, Pages: 370-394, ISSN: 0191-2615
© 2018 The fact that road transportation negatively affects the quality of the environment and deteriorates its bearing capacity has drawn a wide range of concerns among researchers. In order to provide more realistic traffic data for estimations of environmental impacts, dynamic traffic assignment (DTA) models have been adopted in transportation planning and traffic management models concerning environmental sustainability. This review summarizes and examines the recent methodological advances of DTA models in environmentally sustainable road transportation applications including traffic signal control concerning vehicular emissions and emission pricing. A classification of emission estimation models and their integration with DTA models are accordingly reviewed as supplementary to the existing reviews. Finally, a variety of future research prospects of DTA for environmentally sustainable road transportation research are discussed. In particular, this review also points out that at present the research about DTA models in conjunction with noise predictive models is relatively deficient.
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
Han K, Friesz TL, 2017, Continuity of the Effective Delay Operator for Networks Based on the Link Delay Model, Networks and Spatial Economics, Vol: 17, Pages: 1095-1110, ISSN: 1566-113X
This paper is concerned with a dynamic traffic network performance model, known as dynamic network loading (DNL), that is frequently employed in the modeling and computation of analytical dynamic user equilibrium (DUE). As a key component of continuous-time DUE models, DNL aims at describing and predicting the spatial-temporal evolution of traffic flows on a network that is consistent with established route and departure time choices of travelers, by introducing appropriate dynamics to flow propagation, flow conservation, and travel delays. The DNL procedure gives rise to the path delay operator, which associates a vector of path flows (path departure rates) with the corresponding path travel costs. In this paper, we establish strong continuity of the path delay operator for networks whose arc flows are described by the link delay model (Friesz et al., Oper Res 41(1):80–91, 1993; Carey, Networks and Spatial Economics 1(3):349–375, 2001). Unlike the result established in Zhu and Marcotte (Transp Sci 34(4):402–414, 2000), our continuity proof is constructed without assuming a priori uniform boundedness of the path flows. Such a more general continuity result has a few important implications to the existence of simultaneous route-and-departure-time DUE without a priori boundedness of path flows, and to any numerical algorithm that allows convergence to be rigorously analyzed.
Han K, Yao T, Jiang C, et al., 2017, Lagrangian-based Hydrodynamic Model for Traffic Data Fusion on Freeways, NETWORKS & SPATIAL ECONOMICS, Vol: 17, Pages: 1071-1094, ISSN: 1566-113X
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
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, 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.
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).
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