106 results found
Friesz TL, Han K, 2018, The mathematical foundations of dynamic user equilibrium, Transportation Research Part B: Methodological, ISSN: 0191-2615
This paper is pedagogic in nature, meant to provide researchers a single reference for learning how to apply the emerging literature on differential variational inequalities to the study of dynamic traffic assignment problems that are Cournot-like noncooperative games. The paper is presented in a style that makes it accessible to the widest possible audience. In particular, we apply the theory of differential variational inequalities (DVIs) to the dynamic user equilibrium (DUE) problem. We first show that there is a variational inequality whose necessary conditions describe a DUE. We restate the flow conservation constraint associated with each origin-destination pair as a first-order two-point boundary value problem, thereby leading to a DVI representation of DUE; then we employ Pontryagin-type necessary conditions to show that any DVI solution is a DUE. We also show that the DVI formulation leads directly to a fixed-point algorithm. We explain the fixed-point algorithm by showing the calculations intrinsic to each of its steps when applied to simple examples.
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
Pu J, Liu C, Zhao J, et al., 2018, Vulnerability Assessment of Metro Systems Based on Dynamic Network Structure, 22nd Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), Publisher: SPRINGER INTERNATIONAL PUBLISHING AG, Pages: 525-537, ISSN: 0302-9743
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.
Tian Y, Wan L, Han K, et al., 2018, Optimization of terminal airspace operation with environmental considerations, Transportation Research Part D: Transport and Environment, Vol: 63, Pages: 872-889, ISSN: 1361-9209
© 2018 Elsevier Ltd The rapid growth in air traffic has resulted in increased emission and noise levels in terminal areas, which brings negative environmental impact to surrounding areas. This study aims to optimize terminal area operations by taking into account environmental constraints pertaining to emission and noise. A multi-objective terminal area resource allocation problem is formulated by employing the arrival fix allocation (AFA) problem, while minimizing aircraft holding time, emission, and noise. The NSGA-II algorithm is employed to find the optimal assignment of terminal fixes with given demand input and environmental considerations, by incorporating the continuous descent approach (CDA). A case study of the Shanghai terminal area yields the following results: (1) Compared with existing arrival fix locations and the first-come-first-serve (FCFS) strategy, the AFA reduces emissions by 19.6%, and the areas impacted by noise by 16.4%. AFA and CDA combined reduce the emissions by 28% and noise by 38.1%; (2) Flight delays caused by the imbalance of demand and supply can be reduced by 72% (AFA) and 81% (AFA and CDA) respectively, compared with the FCFS strategy. The study demonstrates the feasibility of the proposed optimization framework to reduce the environmental impact in terminal areas while improving the operational efficiency, as well as its potential to underpin sustainable air traffic management.
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
Yin J, Hu M, Ma Y, et al., 2018, Airport taxi situation awareness with a macroscopic distribution network analysis, Networks and Spatial Economics, ISSN: 1566-113X
This paper proposes a framework for airport taxi situation awareness to enhance the assessment of aircraft ground movements in complex airport surfaces. Through a macroscopic distribution network (MDN) of arrival and departure taxi processes in a spatial-temporal domain, we establish two sets of taxi situation indices (TSIs) from the perspectives of single aircraft and the whole network. These TSIs are characterized into five categories: aircraft taxi time indices (ATTIs), surface instantaneous flow indices (SIFIs), surface cumulative flow indices (SCFIs), aircraft queue length indices (AQLIs), and slot resource demand indices (SRDIs). The coverage of the TSIs system is discussed in detail based on the departure and arrival reference aircraft. A real-world case study of Shanghai Pudong airport demonstrates significant correlations among some of the proposed TSIs such as the ATTIs, SCFIs and AQLIs. We identify the most crucial influencing factors of the taxi process and propose two new metrics to assess the taxi situation at the aircraft and network levels, by establishing taxi situation assessment models instead of using two systems of multiple TSIs. The findings can provide significant references to decision makers regarding airport ground movements for the purposes of air traffic scheduling and congestion control in complex airports.
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
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