Dr. Kun An

Dr. Kun An

Senior Lecturer in Transport Engineering
Department of Civil Engineering

Dr. An received her Ph.D. degree in Civil Engineering from the Hong Kong University of Science and Technology, Hong Kong in 2014. She is currently a Lecturer with the Institute of Transport Studies at Monash University. The focus of her Ph.D. dissertation was on reliable transit network design considering demand uncertainty. After graduation, she joined the University of Illinois at Urbana & Champaign as a Postdoctoral researcher in 2015. Her research interests include sharing mobility (carsharing, ride-sharing, customized bus), driverless taxis, reliable transit network design, logistics and supply chain design, facility location problem, traffic operation and control.

Qualifications

  • Bachelor's Degree, Traffic Management and Control, Tongji University, 2009
  • Doctor of Philosophy (Ph.D), Civil Engineering, HKUST, 2014
  • Post Doctoral Researcher, University of Illinois at Urbana-Champign, 2016

Expertise

Reliable facility location
Robust optimization
Multi-stage stochastic program

Professional activity:

Journal Reviewer of Transportation Research Part B, Transportation Research Part E, Transportation Research Part A, Transportation Research Part C, Transportation Science, Transportation Research Record, European Journal of Operational Research, Journal of Advanced Transportation, Public Transport, ACM Transactions on Modeling and Computer Simulation, Transportation letters and IEEE Transactions on Intelligent Transportation Systems.

Conference Referee of Transportation Research Board Annual Meeting(TRB), International Conference of Hong Kong Society for Transportation Studies(HKSTS), Australasian Transport Research Forum (ATRF).

Session chair at Australasian Transport Research Forum (ATRF), Auckland, New Zealand, 2017.

Director in organising “The 5th Joint Seminar between Tongji University & Kyoto University on Harmonious City & Transportation”, 2009.

Awards

2010-2014 -Hong Kong PhD Fellowship (most prestigious fellowship in Hong Kong with 135 awardees out of 2996 applicants)

2014 – Nominated for the ADB30 Transportation Network Modelling Committee’s Best Paper Prize in TRB annual meeting (top 3 of 200+ papers)

2013 – 1st Runner-up of Outstanding Student Paper Award in the 18th HKSTS International Conference.

2009 – Excellent Graduate Student of Shanghai, China (top 5% of all the graduate students in Shanghai)

 

Invited talks

Invited talk on “Reliable Sensor Deployment for Object Positioning and Surveillance in a Two Dimensional Space” at Future Transport Control Conference, Shanghai, China, 2017

Invited talk on “Public transport and smart features for growing cities” at the Research Centre for Transport, Port and Shipping Development in Shanghai, China, 2016

Invited talk on “Improving traffic signal control for corridors with variable demand” at Southeast University, China, 2016

Invited talk on “Stochastic Programming for adaptive-coordinated signal control” at Tongji University, China, 2016

Media exposure

Invited comment on Driver License Conversion Policies in Victoria, entitled “HK driver’s license directly convert to Australian’s will be canceled?” Australia. SBS TV, 2017/12

Invited comment on Traffic Signal Settings in Australia, Melbourne, Australia. SBS TV, 2018/01

Research Projects

Current projects

Free-floating carsharing system planning

This project aims to develop a mathematical framework for designing free-floating car sharing systems using electric vehicles. This project expects to generate an in-depth understanding on the market feedback of car sharing infrastructures, Electric Vehicle fleet size, and pricing, in anticipation of the government subsidy for electric vehicles. Expected outcomes of this project include an evolutionary capital investment design to realise the market penetration for car sharing operators, as well as viable operational strategies for vehicle relocation to ensure its profitability. This should provide significant benefits to the environment and to the society due to the increased EV usage and the public transport attribute of car sharing.

Scalable urban traffic control framework driven by distributed information

This project aims to develop a mathematical framework for an in-depth investigation of the role of information in a fundamental interaction between the traffic signal setting and self-interest route/departure time choice of road users. Traffic control is one of the oldest and most cost-effective solutions for the worsening congestion problem in many metropolitan areas. With the modern technological advancement, however, there remain fundamental mathematical challenges in taking that advantage to improve traffic control and combat congestion. The outcome will be insights into the use of information and algorithms that can provide efficient, robust and behaviour consistent (i.e. safe) traffic network management.

Bus bridging service design in response to metro disruptions

Past projects

Multi-stage stochastic program to optimize signal timings under coordinated adaptive control

In the wake of traffic congestion at intersections, it is imperative to shorten delays in corridors with stochastic arrivals. Coordinated adaptive control can adjust green time flexibly to deal with a stochastic demand, while maintaining a minimum through-band for coordinated intersections. In this paper, a multi-stage stochastic program based on phase clearance reliability (PCR) is proposed to optimize base timing plans and green split adjustments of coordinated intersections under adaptive control. The objective is to minimize the expected intersection delay and overflow of the coordinated approach. The overflow or oversaturated effect is explicitly addressed in the delay calculation, which greatly increases the modeling complexity due to the interaction of overflow delays across cycles. The notion of PCR separates the otherwise related green time settings of consecutive cycles into a number of stages, in which the base timing plan and actual timing plan in different cycles are handled sequentially. We then develop a PCR based solution algorithm to solve the problem, and apply the model and the solution algorithm to actual intersections in Shanghai to investigate its performance as compared with Allsop’s method and Webster’s method. Preliminary results show the PCR-based method can significantly shorten delays and almost eliminates overflow for the coordinated approaches, with acceptable delay increases of the non-coordinated approaches. A comparison between the proposed coordinated adaptive logic and a coordinated actuated logic is also conducted in the case study to show the advantages and disadvantages.

Robust grain supply chain design considering post-harvest loss and harvest timing equilibrium

This paper presents a bi-level robust optimization model, where a food company maximizes its profit and minimizes post-harvest loss by optimally deploying grain processing/storage facilities and determining grain purchase price, while a group of spatially distributed non-cooperative farmers determine harvest time, shipment, storage, and market decisions under yield uncertainty and market equilibrium. The non-cooperative behavior of the food company and the farmers is represented by a bi-level Stackelberg leader follower’s game model with mixed-integer decision variables. The proposed model and solution approach are applied to case studies for Illinois and Brazil.

Transit Network Design with Stochastic Demand

This chapter studies transit network design with stochastic demand by considering two types of services—rapid transit services, such as rail, and flexible services, such as dial-a-ride shuttles. Rapid transit services operate on fixed routes and dedicated lanes, and with fixed schedules, whereas dial-a-ride services can make use of the existing road network; hence are much more economical to implement. We integrate these two service networks into one multi-modal network and then determine the optimal combination of these two service types under user equilibrium (UE) flows. Two approaches are used to address the issue of stochastic demand: one is robust optimization; the other is stochastic programming. The robust optimization approach assumes that the stochastic demand is captured in a polyhedral uncertainty set. The UE principle is represented by a set of variational inequality (VI) constraints.

Publications

Book chapters

  1. Kun An and Hong K. Lo. 2016. “Transit Network Design with Stochastic Demand” in Modelling Intelligent Multi-Modal Transit Systems by CRC Press, Chapter 10, 2016.
  2. Inhi Kim and Kun An. 2017. Chapter VIII in Traffic Engineering and Management by the Monash Institute of Transport Studies, pages 743-789, VIC 3800, Australia. 2017.

Journal Articles

  1. Kun An*, Wentao Jing and Inhi Kim, and, “Battery swapping facility planning for electric buses with local charging systems”. International Journal of Sustainable Transportation. In Press, 2019.
  2. Siyang Xie, Kun An and Y.F. Ouyang, “Planning of Facility Location under Correlated Disruptions”. Transportation Research Part B. In Press, 2019.
  3. Mingtao Xu, Kun An*, Zhirui Ye, Le Hai Vu, and Chao Wang, “Optimizing Multi-agent Based Urban Traffic Control System”. Journal of Intelligent Transportation Systems. DOI: 10.1080/15472450.2018.1501273,
  4. Mingtao Xu, Kun An, Zhirui Ye, Jinlong Luo and Wei Wang, “A Bi-Level Model to Resolve Conflicting Transit Priority Requests at Urban Arterials”. IEEE transactions on ITS. Issue: 99, 1-12. DOI: 10.1109/TITS.2018.2853102. 2018.
  5. Long T. Truong, Graham Currie, Mark Wallace, Chris De Gruyter and Kun An, “Coordinated Transit Signal Priority Model Considering Stochastic Bus Arrival Time”. IEEE transactions on ITS. Issue: 99, 1-9. 2018. https://doi.org/10.1109/TITS.2018.2844199
  6. Kai Huang, G. Correia and Kun An*, “Solving the Station-based One-way Carsharing Network Planning Problem with Relocations and Non-linear Demand,” Transportation Research Part C. 90, 1-17,
  7. Wanjing Ma, Li Zou, Kun An, Nathan H. Gartner and Meng Wang, “A Partition-enabled Multi-mode Band Approach to Arterial Traffic Signal Optimization”. IEEE transactions on ITS. 1-10. DOI: 10.1109/TITS.2018.2815520.
  8. Wentao Jin, M. Ramezani, Kun An and Inhi Kim, “Battery Swapping Facility Location Problem with Localized Charging System Serving Electric Buses”. PLoS One, 13(3): e0194354. 2018. https://doi.org/10.1371/journal.pone.0194354.
  9. Kun An, Siyang  Xie and Y.F. Ouyang, “Reliable Sensor Deployment for Object Positioning and Surveillance Via Trilateration”. Transportation Research Part B & presented at ISTTT22, on line on December 2017.
  10. Wentao Jing, Kun An, M. Ramezani, and I. Kim, “Location Design of Electric Vehicle Charging Facilities: A Path-Distance Constrained Stochastic User Equilibrium Approach”. Journal of Advanced Transportation, vol. 2017, Article ID 4252946, 2017.
  11. Wanjing Ma, Kun An* and Hong K. Lo, Reliable Optimization of Coordinated Intersections under Demand Uncertainty. Transportation Research Part C, 72: 342–359, 2016.
  12. Kun An and Y.F. Ouyang, Robust Grain Supply Chain Design Considering Post-Harvest Loss and Harvest Timing Equilibrium. Transportation Research Part E 88: 110-128, 2016.
  13. Kun An and Hong K. Lo. Two-phase Stochastic Program for Transit Network Design under Demand Uncertainty. Transportation Research Part B. 84, 157-181, 2016.
  14. Kun An and Hong K. Lo. Robust Transit Network Design with Stochastic Demand Considering Development density. Transportation Research Part B. 81(3), 737-754, 2015.
  15. Baoxin Han, Wanjing Ma, Kun An and Nan Zhang, Investigating the Applicability of Exclusive Pedestrian Phase at Actuated Signalized Intersections, Journal of Advanced Transportation. 49(6), 752-767, 2015.
  16. Kun An and Hong K. Lo, Transit Network Design under Demand Uncertainty, Transportation Research Record. 2467, 101-109, 2014.
  17. Kun An and Hong K. Lo, Ferry Service Network Design with Stochastic Demand under Equilibrium Flows, Transportation Research Part B. 66, 70-89, 2014.
  18. Hong K. Lo, Kun An and Wei-hua Lin, Ferry Network Design under Demand Uncertainty, Transportation Research Part E, 59, 48-73, 2013.
  19. Ma, Y. Lu, Kun An and J. Zhao, “Probabilistic Model for Signalized Intersection Capacity with Short Lanes”, Journal of Tongji University (Natural Science), 40 (11), 2012. (In Chinese)
  20. Ma, H. Xie and Kun An, “Methodological Review for Identification of the Oversaturated Condition of Signalized Intersections”, Journal of Transportation Information and Safety, 29(5), 2011. (In Chinese)
  21. Kun An, X. Yang, Y. Bai and T. Zhu, “Safety Analysis and Simulation Evaluation of Urban Road Access Points”, Journal of Transportation Information and Safety, 28(1), 2010. (In Chinese)

Under Review

  1. Kun An*, “A stochastic model for charging infrastructure location, bus fleet sizing, and charging scheduling of battery electric bus systems”. Submitted to Transportation Research Part C.
  2. Kai Huang, Kun An* G and Correia, “Planning of One-way Electric Carharing Systems with Continuous State of Charge Functions,” Submitted to Transportation Research Part B.

 

 

 

 

 

Linkage Seed Fund, Monash University, Australia, Investigate the transport methods for the stability of blood samples, 2019

Lead CI,            Fund: 27, 200 AUD

ARC DP18, Scalable urban traffic control framework driven by distributed information, 2018-2020

CI,  with Hai Vu,            Fund: 294, 139AUD

Discovery Seed Fund, Monash University, Australia, Sustainable charging infrastructure deployment for electric vehicles, 2017-2018

Lead CI,            Fund: 29, 780 AUD

Jiangsu Province, China, Research on Collaborative Model of Green Travel in Intelligent City Integration platform in China, 2017-2019

CI, with Terry Liu and Inhi Kim,         Fund: 4, 000, 000 RMB (760, 000 AUD)

Traffic Safety Key Laboratory, China, Road Rage Characteristics and Prevention methods, 2016-2017

CI, with Inhi Kim,         Fund: 30, 000 RMB (6, 000 AUD)

Supervision

PHD

Ali Shan
Carsharing system evaluation
2018.11 to -

Kai Huang
Carsharing system planning
2016.12 to -

Nora Estgfaeller
Impacts of bus concentration on ridership
2016.09 to -

Long TRUONG
Public Transport Priority Effects
2014 to 2016

Wentao Jing
Electric vehicle charging station location
2014 to 2018

Fanglei Jin
Visiting Student from Beijing Jiaotong University: Customer attitude analysis
2018.10 to 2019.04

Yao Chen
visiting student from Beijing Jiaotong Uni: Bus bridging route design
2017.09 to 2018.04

Mingtao Xu
visiting student from South East Uni: Fussy control methods for coordinated adaptive signals
2016.10 to 2017.08

Teaching Commitments

  • CIV5406 - Modelling Transportation Systems
  • CIV5319 - Quantitative Methods for Transportation Systems Analysis
  • CIV5305/5305 - Travel Demand Modelling
Last modified: 17/03/2020