Imperial College London

Dr Ke Han

Faculty of EngineeringDepartment of Civil and Environmental Engineering

Lecturer in Transport Operations and Logistics
 
 
 
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Contact

 

+44 (0)20 7594 5682k.han Website CV

 
 
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Assistant

 

Mrs Maya Mistry +44 (0)20 7594 6100

 
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Location

 

605Skempton BuildingSouth Kensington Campus

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Summary

 

Publications

Publication Type
Year
to

94 results found

Friesz TL, Han K, Meimand A, Neto PA, Yao Tet al., Dynamic user equilibrium based on a hydrodynamic model, Transportation Research Board 91st Annual Meeting., Publisher: Transportation Research Board

CONFERENCE PAPER

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.

CONFERENCE PAPER

Han K, Sun Y, Liu H, Friesz TL, Yao Tet al., A bi-level model of dynamic traffic signal control with continuum approximation, 5th International Symposium on Dynamic Traffic Assignment

CONFERENCE PAPER

Han K, Yao T, Friesz TL, Lagrangian-based hydrodynamic model: freeway traffic estimation, 4th International Symposium on Dynamic Traffic Assignment

CONFERENCE PAPER

Li S, Xu R, Han K, Zhu Wet al., Optimizing train service plans to coordinate transport capacity for urban rail transit lines, Transportation Research Board 97th Annual Meeting

In view of big passenger flow volume and high passenger risk at transfer stations during the peak period, this paper studied the coordination method of urban rail transit network transportation organization from the perspective of capacity matching. The change law of passenger flow was analyzed, and the calculation methods of train remaining carrying capacity, waiting passenger demand and the largest number of people gathered on the platform were determined. The concept of capacity coordination degree (CCD) was proposed, used to describe the matching degree between traffic demand and transport capacity of each line. Based on this, taking the optimal comprehensive CCD of the transfer station as the goal, the first train departure time and train departure interval as decision variables, and guarantee of passenger safety within station as the main constraint, a nonlinear integer programming model of train service plans collaborative optimization was established, and the genetic algorithm was designed. A case study of a two-line intersecting network was carried out. The results show that, after the use of capacity coordination scheme, the total number of running trains increases by only 1, the number of remaining passengers reduces by 68.44%, comprehensive CCD is closer to 1, and the largest number of people gathered in big passenger flow directions decreases by 11.77% and 19.68%, respectively. Transport supply can better meet the passenger demand in all directions, effectively improving the interests of both passengers and operators.

CONFERENCE PAPER

Ma L, Chen Q, Han K, Gao Y, Li Det al., A tale of two stations: Analyzing metro ridership with big data, Transportation Research Board 97th Annual Meeting

This paper presents a multi-dimensional case study of the Beijing metro system. In particular, we examine two non-transfer stations, Zaoying and Jiangtai, which are on the same metro line in central Beijing. Multi-source and heterogeneous data are integrated to analyze and diagnose the drastically different metro ridership at the two stations. These include transit smart card data, taxi GPS data, network data, Point of Interest data, demographic data, online second-hand property price data, cell phone signalling data, and bike sharing data. The different utilization of metro system at these two locations is attributed to a number of factors pertaining to transportation infrastructure, built environment, demographic composition, commuting patterns, and connectivity of multi-modal transit networks. The findings suggest the importance of local accessibility of the metro stations as well as its connectivity with the rest of the transit system, in order to maximize the transport capability of the metro system. Our analysis also highlights the benefit of collecting and analyzing fine-granularity data in order to identify key bottlenecks and inefficiencies in the transportation system, as conventional macroscopic transportation planning data do not sufficiently capture the local accessibility and mobility in an urban environment.

CONFERENCE PAPER

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

CONFERENCE PAPER

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

CONFERENCE PAPER

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

CONFERENCE PAPER

Song J, Jiang C, Han K, Quan S, Fu Let 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

CONFERENCE PAPER

Wang Y, Liu H, Han K, Friesz TL, Yao Tet al., Day-to-day congestion pricing and network resilience, Transportation Research Board 95th Annual Meeting

CONFERENCE PAPER

Wong N, Escribano-Macias J, Han K, Angeloudis Pet al., Rapid urban evacuation across constrained transport networks, Transportation Research Board 96th Annual Meeting

CONFERENCE PAPER

Wu F, Stern R, Churchill M, Delle Monache ML, Han K, Piccoli B, Work DBet al., Fuel consumption in oscillatory traffic: experimental results, Transportation Research Board 96th Annual Meeting

CONFERENCE PAPER

Xu Y, Yin S, Dalmau R, Prats X, Han Ket 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

CONFERENCE PAPER

Yang L, Yin S, Hu M, Han K, Xu Yet al., Empirical study of air traffic dynamics using coupled network modeling and non-linear analysis, Transportation Research Board 97th Annual Meeting

CONFERENCE PAPER

Yin J, Hu M, Ma Y, Han K, Chen Det al., Spatial-temporal topology and performance analysis of airport taxi network, Transportation Research Board 97th Annual Meeting

This paper proposes a spatial-temporal topology from a macroscopic view to analyze the performance of airport taxi network operations. Through a macroscopic modelling of arrival and departure aircraft taxi processes in the airport taxi network, we establish a system of taxi network performance indicators (TNPIs) consisting 5 categories and 26 indicators, which includes the surface instantaneous flow indicators (SIFIs), surface cumulative flow indicators (SCFIs), aircraft queue length indicators (AQLIs), slot resource demand indicators (SRDIs) and aircraft taxi time indicators (ATTIs). Then, we analyze the correlation among different TNPIs. By identifying the key factors affecting aircraft taxi time such as takeoff and landing queue length, we provide models for predicting aircraft taxi time based on multiple regression analysis. The real-world case study in Shanghai Pudong airport demonstrates significant correlations among some of the proposed TNPIs, and the results also show the significantly improved accuracy of the proposed prediction models over some conventional models, which brings significant benefits to analyze the performance of airport taxi network and support decision making in airport operations.

CONFERENCE PAPER

Yin S, Han K, Yang L, Hu Met al., Off-block flow optimization based on cell transmission model for mitigating departure traffic congestion at airport surface, Transportation Research Board 96th Annual Meeting

CONFERENCE PAPER

Chen D, Hu M, Zhang H, Yin J, Han Ket 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

© 2017 Elsevier Ltd This study proposes a mesoscopic dynamic air traffic model based on a dynamic network for en route airspaces by characterizing the dynamics and distribution of traffic speed. Based on this model, we solve a flow optimization problem for enforcing capacity constraints with the minimum operational cost using a dual decomposition method. A case study of an en route airspace in Shanghai demonstrates the accuracy of the proposed model in successfully capturing the flow dynamics, as well as the effectiveness of the proposed optimization framework to reduce en route delays by balancing the dynamic traffic demand and airspace capacity.

JOURNAL ARTICLE

Han K, 2017, Framework for Real-Time Traffic Management with Case Studies, Transportation Research Record: Journal of the Transportation Research Board, Vol: 2658, Pages: 35-43, ISSN: 0361-1981

JOURNAL ARTICLE

Liu J, Li K, Yin M, Zhu X, Han Ket al., 2017, Optimizing Key Parameters of Ground Delay Program with Uncertain Airport Capacity, JOURNAL OF ADVANCED TRANSPORTATION, ISSN: 0197-6729

JOURNAL ARTICLE

Qin F, Sun R, Ochieng WY, Feng S, Han K, Wang Yet 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

JOURNAL ARTICLE

Shang W, Han K, Ochieng W, Angeloudis Pet 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

JOURNAL ARTICLE

Sidiropoulos S, Han K, Majumdar A, Ochieng WYet 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

JOURNAL ARTICLE

Song W, Han K, Wang Y, Friesz T, del Castillo Eet 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

CONFERENCE PAPER

Song W, Han K, Wang Y, Friesz T, del Castillo Eet al., 2017, Statistical metamodeling of dynamic network loading, Transportation Research Procedia, Vol: 23, Pages: 263-282, ISSN: 2352-1465

JOURNAL ARTICLE

Song W, Han K, Wang Y, Friesz TL, del Castillo Eet 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.

CONFERENCE PAPER

Song W, Han K, Wang Y, Friesz TL, del Castillo Eet al., 2017, Statistical metamodeling of dynamic network loading, Transportation Research Part B: Methodological, ISSN: 0191-2615

JOURNAL ARTICLE

Yang L, Yin S, Hu M, Han K, Zhang Het 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

JOURNAL ARTICLE

Yu C, Ma W, Han K, Yang Xet al., 2017, Optimization of vehicle and pedestrian signals at isolated intersections, TRANSPORTATION RESEARCH PART B-METHODOLOGICAL, Vol: 98, Pages: 135-153, ISSN: 0191-2615

JOURNAL ARTICLE

Chen D, Hu M, Han K, Zhang H, Yin Jet 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.

JOURNAL ARTICLE

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