111 results found
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: 1572-9427
Over the last two decades, the electricity industry has shifted from regulation of monopolistic and centralized utilities towards deregulation and promoted competition. With increased competition in electric power markets, system operators are recognizing their pivotal role in ensuring the efficient operation of the electric grid and the maximization of social welfare. In this article, we propose a hypothetical new market of dynamic spa- tial network equilibrium among consumers, system operators and electricity generators as the solution of a dynamic Stackelberg game. In that game, generators form an oligopoly and act as Cournot-Nash competitors who non-cooperatively maximize their own profits. The market monitor attempts to increase social welfare by intelligently employing equi- librium congestion pricing anticipating the actions of generators. The market monitor influences the generators by charging network access fees that influence power flows to- wards a perfectly competitive scenario. Our approach anticipates uncompetitive behavior and minimizes the impacts upon society. The resulting game is modeled as a Mathemat- ical Program with Equilibrium Constraints (MPEC). We present an illustrative example as well as a stylized 15-node network of the Western European electric grid.
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 W, Han K, Wang Y, et al., Statistical metamodeling of dynamic network loading, 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
Sun R, Han K, Hu J, et al., An integrated algorithm based on BeiDou/GPS/IMU and its application for anomalous driving detection., ION GNSS+
Recent years have seen a booming of safety-related Intelligent Transportation System (ITS) applications, which have placed increasingly stringent requirements on the performance of Global Navigation Satellite Systems (GNSS). Examples include lane control, collision avoidance, and intelligent speed assistance. Detecting the lane level anomalous driving behavior is crucial for these safety critical ITS applications. The two major issues associated with the lane-level irregular driving identification are (1) accessibility to high accuracy positioning and vehicle dynamic parameters, and (2) extraction of anomalous driving behavior from these parameters. This paper introduces an integrated algorithm for detecting lane-level anomalous driving. Lane-level high accuracy vehicle positioning is achieved by fusing GPS and Beidou feeds with Inertial Measurement Unit (IMU) using Unscented Particle Filter (UPF). Anomalous driving detection is achieved based on the application of a newly designed Fuzzy Inference System. Computer simulation and real-world field test demonstrate the advantage of the proposed approach over existing ones from previous studies.
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.
Shang W, Han K, Ochieng W, et al., 2016, Agent-based day-to-day traffic network model with information percolation, Transportmetrica A-Transport Science, Vol: 13, Pages: 38-66, ISSN: 2324-9935
This paper explores the impact of travel information sharing on road networks using a two-layer, agent-based, day-to-day traffic network model. The first layer (cyber layer) represents a conceptual communication network where travel information is shared among drivers. The second layer (physical layer) captures the day-to-day evolution in a traffic network where individual drivers seek to minimize their own travel costs by making route choices. A key hypothesis in this model is that instead of having perfect information, the drivers form individual groups, among which travel information is shared and utilized for routing decisions. The formation of groups occurs in the cyber layer according to the notion of percolation, which describes the formation of connected clusters (groups) in a random graph. We apply the novel notion of percolation to capture the disaggregated and distributed nature of travel information sharing. We present a numerical study on the convergence of the transport network, when a range of percolation rates are considered. The findings suggest a positive correlation between the percolation rate and the speed of convergence, which is validated through statistical analysis. A sensitivity analysis is also presented which shows a bifurcation phenomenon with regard to certain model parameters.
Friesz T, Han K, 2016, Computing dynamic user equilibria in continuous time, 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
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
Song W, Han K, Wang Y, et al., 2016, Statistical metamodeling of dynamic network loading, 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, Transportmetrica A: Transport Science, Vol: 12, Pages: 878-908, ISSN: 2324-9943
This paper proposes an intersection-movement-based variational inequality formulation for the multi-class dynamic traffic assignment (DTA) problem involving physical queues using the concept of approach proportion. An extragradient method that requires only pseudomonotonicity and Lipschitz continuity for convergence is developed to solve the problem. We also present a car–truck interaction paradox, which states that allowing trucks to travel or increasing the truck flow in a network can improve network performance for cars in terms of the total car travel time. Numerical examples are set up to illustrate the importance of considering multiple vehicle types and their interactions in a DTA model, the effects of various parameters on the occurrence of the paradox, and the performance of the solution algorithm.
Sidiropoulos S, Han K, Majumdar A, et al., 2016, Identifying significant traffic flow patterns in Multi-Airport Systems Terminal Manoeuvring Areas under uncertainty, 16th AIAA Aviation Technology, Integration, and Operations Conference
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: 1879-2359
There has been an increasing role played by Global Navigation Satellite Systems (GNSS) in Intelligent Transportation System (ITS) applications in recent decades. In particular, centimetre/decimetre positioning accuracy is required for some safety related applications, such as lane control, collision avoidance, and intelligent speed assistance. Lane-level Anomalous driving detection underpins these safety-related ITS applications. The two major issues associated with such detection are (1) accessing high accuracy vehicle positioning and dynamic parameters; and (2) extraction of irregular driving patterns from such information. This paper introduces a new integrated framework for detecting lane-level anomalous driving, by combining Global Positioning Systems (GPS), BeiDou, and Inertial Measurement Unit (IMU) with advanced algorithms. Specifically, we use Unscented Particle Filter (UPF) to perform data fusion with different positioning sources. The detection of different types of Anomalous driving is achieved based on the application of a Fuzzy Inference System (FIS) with a newly introduced velocity-based indicator. The framework proposed in this paper yield significantly improved accuracy in terms of positioning and Anomalous driving detection compared to state-of-the-art, while offering an economically viable solution for performing these tasks.
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
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
Air traffic controllers play critical roles in the safety, efficiency, and capacity of air traffic management. However, there is inadequate knowledge of the dynamics of the controllers’ activities, especially from a quantitative perspective. This paper presents a novel network approach to uncover hidden patterns of the controllers’ behavior based on the voice communication data. We convert the time series of the controllers’ communication activities, which contain flights’ information, into a time-varying network and a static network, referred to as temporal network and time-aggregated network, respectively. These networks reflect the interaction between the controllers and the flights on a sector level, and allow us to leverage network techniques to yield new and insightful findings regarding regular patterns and unique characteristics of the controllers’ communication activities. The proposed methodology is applied to three real-world datasets, and the resulting networks are closely examined and compared in terms of degree distribution, community structure, and motifs. This network approach introduces a “spatial” element to the conventional analysis of the controllers’ communication events, by identifying connectivity and proximity among flights. It constitutes a major step towards the quantitative description of the controller-flight dynamics, which is not widely seen in the literature.
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.
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: 2324-9943
Lane assignment and on-ramp signal control are two potential methods for mitigating traffic congestion of weaving segments. Unlike methods in the existing literature, where the optimisation strategy is selected beforehand, this paper proposes an integrated optimisation model for a one-side weaving segment that explicitly takes into consideration the two optimisation strategies and their combinations. Therefore, the benefits and drawbacks of different design types could be fairly compared. A mixed-integer-non-linear programme is formulated to simultaneously optimise the optimisation strategy, lane markings, and signal timings. The results of extensive numerical and simulation analyses show that the proposed model could significantly improve the capacity of a weaving segment, especially under a high weaving volume ratio. Furthermore, the lane assignment strategy, combination of lane assignment and on-ramp control, and on-ramp signal control strategy may have better performances when the weaving volume ratio is low, medium, and high, respectively.
Mascia M, Hu J, Han K, et al., 2016, A holistic approach for performance assessment of personal rapid transit, Research in Transportation Business & Management, ISSN: 2210-5395
Personal Rapid Transit (PRT) has received increased attention in recent years due to technological innovation and the need for safer, more efficient, and more sustainable transport systems in dense urban areas. PRT service is on demand, and provides a good level of service due to short waiting time with no intermediate stops. The cost to run the system is lower compared to traditional transport systems due to utilizing autonomous pods.While a number of studies have focused on specific aspects of the performance of PRT, there is still a lack of comprehensive assessment of PRT's performance from the perspectives of both operators and users. This paper addresses this gap by proposing a set of PRT-specific Key Performance Indicators (KPI) relevant to its operational characteristics (e.g. pod utilization, total distance travelled) and user experience (e.g. average waiting time, delay). The proposed KPIs are demonstrated through a simulation study. The findings made in this paper constitute the first step towards comprehensive benchmarking for PRT systems, and facilitate comparative analyses of different PRT systems to help operators identify and implement best practise.
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.
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
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