ARC DECRA
Overview
Jiwon Kim is an ARC DECRA Fellow (2019-2022) and Senior Lecturer in Transport Engineering in the School of Civil Engineering. She joined UQ in 2014 after completing her PhD research at Northwestern University. Her doctoral work was on the travel time reliability of transportation networks. Prior to joining Northwestern, she worked as an assistant manager at Samsung C&T (Engineering & Construction Group). She received Bachelor’s and Master’s degrees in civil engineering from Korea University.
Dr. Kim’s research is broadly in the area of modeling and analysis of intelligent transport systems (ITS) and human mobility, with an emphasis on the analysis of vehicle trajectories in large-scale traffic networks and predictive analytics for real-time traffic management and operations. Her current research focuses on urban mobility analytics, interdisciplinary research that discovers patterns and insights from massive collections of movement data (e.g., GPS trajectories, public transport smart card data, Bluetooth and WiFi data) using data mining and machine learning algorithms and develops solutions to transport-related challenges in our cities.
Research Interests
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Big Data, Machine Learning, and Artificial Intelligence (AI) applications in transportation
Data-driven modeling of transport networks; Computer vision (image/video processing, traffic scene recognition, anomaly detection) -
Urban mobility analytics, Spatio-temporal analysis of trajectory data
Vehicle trajectories in large-scale networks: data mining, pattern recognition, and visualization; Urban mobility insights and travel behavour -
Predictive analytics for real-time traffic management and operations
Real-time traffic estimation and prediction for Intelligent Transportation Systems (ITS); Traffic incident management and decision support systems -
Traffic simulation and Traffic flow theory
Traffic simulation (microsimulation/mesosimulation); Dynamic traffic assignment (DTA); Scenario generation and analysis
Qualifications
- Doctor of Philosophy, Northwestern University
Publications
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Journal Article: Comparing sequential with combined spatiotemporal clustering of passenger trips in the public transit network using smart card data
Faroqi, Hamed, Mesbah, Mahmoud and Kim, Jiwon (2019) Comparing sequential with combined spatiotemporal clustering of passenger trips in the public transit network using smart card data. Mathematical Problems in Engineering, 2019 . doi:10.1155/2019/5070794
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Journal Article: Operational Ssenario definition in traffic simulation-based decision support systems: pattern recognition using a clustering algorithm
Chen, Ying, Kim, Jiwon and Mahmassani, Hani S. (2019) Operational Ssenario definition in traffic simulation-based decision support systems: pattern recognition using a clustering algorithm. Journal of Transportation Engineering Part A: Systems, 145 4: . doi:10.1061/JTEPBS.0000222
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Journal Article: Estimating and comparing response times in traditional and connected environments
Sharma, Anshuman, Zheng, Zuduo, Kim, Jiwon, Bhaskar, Ashish and Haque, Md. Mazharul (2019) Estimating and comparing response times in traditional and connected environments. Transportation Research Record, . doi:10.1177/0361198119837964
Grants
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Making Spatiotemporal Data More Useful: An Entity Linking Approach
(2020–2022) ARC Discovery Projects
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An Integrated Demographic and Transport Demand Modelling Framework (ID-TDM
(2019–2022) iMove Cooperative Research Centre
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Data-driven Simulation of Large Traffic Networks using Trajectory Data
(2019–2022) ARC Discovery Early Career Researcher Award
Supervision
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(2020) Doctor Philosophy
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Automatic detection and analysis of long-term changes in travel patterns of public transport passengers using Smart-Card data
Master Philosophy
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Data fusion and urban trajectory reconstruction for city-wide traffic estimation and prediction
Master Philosophy
Available Projects
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Intelligent Transport Systems (ITS)
- Big data analytics for intelligent transport
- Data mining and artificial intelligence (AI) applications in traffic analysis
- Spatio-temporal analysis of trajectory data in road networks
- Data-driven approaches to traffic estimation and prediction
- Decision support systems for real-time traffic management and control
- Congestion management and avoidance
- Incident detection and traffic incident management
-
Travel time reliability
- Characterizing travel time variability patterns (e.g., vehicle-to-vehicle, day-to-day, and within-day variability)
- Analysis of network uncertainty sources and their impacts on travel time reliability
- Estimating the probability distribution of route travel times using multi-source data
- Development and use of travel time reliability performance indicators
- Analysis of travel time reliability in mixed traffic
-
Traffic flow theory and simulation
- Advanced analysis techniques for micro- and meso-scopic traffic simulation models (e.g., model calibration, input parameter sampling, sensitivity analysis, and uncertainty analysis)
- Analysis of traffic flow breakdown phenomena
- Modeling driver behavior and traffic flow characteristics under a connected and/or autonomous vehicle environment (e.g., V2V, V2I, and self-driving car)
- Analysis of traffic flow variables using new sources of data (e.g., GPS devices, RFID tags, radar, and video)
Publications
Journal Article
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Faroqi, Hamed, Mesbah, Mahmoud and Kim, Jiwon (2019) Comparing sequential with combined spatiotemporal clustering of passenger trips in the public transit network using smart card data. Mathematical Problems in Engineering, 2019 . doi:10.1155/2019/5070794
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Chen, Ying, Kim, Jiwon and Mahmassani, Hani S. (2019) Operational Ssenario definition in traffic simulation-based decision support systems: pattern recognition using a clustering algorithm. Journal of Transportation Engineering Part A: Systems, 145 4: . doi:10.1061/JTEPBS.0000222
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Estimating and comparing response times in traditional and connected environments
Sharma, Anshuman, Zheng, Zuduo, Kim, Jiwon, Bhaskar, Ashish and Haque, Md. Mazharul (2019) Estimating and comparing response times in traditional and connected environments. Transportation Research Record, . doi:10.1177/0361198119837964
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Duives, Dorine C., Wang, Guangxing and Kim, Jiwon (2019) Forecasting pedestrian movements using recurrent neural networks: an application of crowd monitoring data. Sensors, 19 2: 382. doi:10.3390/s19020382
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Network-wide vehicle trajectory prediction in urban traffic networks using deep learning
Choi, Seongjin, Yeo, Hwasoo and Kim, Jiwon (2018) Network-wide vehicle trajectory prediction in urban traffic networks using deep learning. Transportation Research Record, 2672 45: 173-184. doi:10.1177/0361198118794735
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Urban trajectory analytics: day-of-week movement pattern mining using tensor factorization
Naveh, Kianoosh Soltani and Kim, Jiwon (2018) Urban trajectory analytics: day-of-week movement pattern mining using tensor factorization. IEEE Transactions on Intelligent Transportation Systems, 1-10. doi:10.1109/TITS.2018.2868122
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A model for measuring activity similarity between public transit passengers using smart card data
Faroqi, Hamed, Mesbah, Mahmoud, Kim, Jiwon and Tavassoli, Ahmad (2018) A model for measuring activity similarity between public transit passengers using smart card data. Travel Behaviour and Society, 13 11-25. doi:10.1016/j.tbs.2018.05.004
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Applications of transit smart cards beyond a fare collection tool: a literature review
Faroqi, H., Mesbah, M. and Kim, J. (2018) Applications of transit smart cards beyond a fare collection tool: a literature review. Advances in Transportation Studies, 45 107-122. doi:10.4399/978255166098
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Identification of communities in urban mobility networks using multi-layer graphs of network traffic
Yildirimoglu, Mehmet and Kim, Jiwon (2018) Identification of communities in urban mobility networks using multi-layer graphs of network traffic. Transportation Research Part C: Emerging Technologies, 89 254-267. doi:10.1016/j.trc.2018.02.015
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Time-dependent route scheduling on road networks
Li, Lei, Kim, Jiwon, Xu, Jiajie and Zhou, Xiaofang (2018) Time-dependent route scheduling on road networks. SIGSPATIAL Special, 10 1: 10-14. doi:10.1145/3231541.3231545
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Kim, Jiwon, Corcoran, Jonathan and Papamanolis, Marty (2017) Route choice stickiness of public transport passengers: measuring habitual bus ridership behaviour using smart card data. Transportation Research. Part C: Emerging Technologies: an international journal, 83 146-164. doi:10.1016/j.trc.2017.08.005
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Spatial-temporal similarity correlation between public transit passengers using smart card data
Faroqi, Hamed, Mesbah, Mahmoud and Kim, Jiwon (2017) Spatial-temporal similarity correlation between public transit passengers using smart card data. Journal of Advanced Transportation, 2017 1-15. doi:10.1155/2017/1318945
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Characterising Green Light Optimal Speed Advisory trajectories for platoon-based optimisation
Stebbins, Simon, Hickman, Mark, Kim, Jiwon and Vu, Hai L. (2017) Characterising Green Light Optimal Speed Advisory trajectories for platoon-based optimisation. Transportation Research Part C: Emerging Technologies, 82 43-62. doi:10.1016/j.trc.2017.06.014
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Diagnosis and prediction of traffic congestion on urban road networks using Bayesian networks
Kim, Jiwon and Wang, Guangxing (2016) Diagnosis and prediction of traffic congestion on urban road networks using Bayesian networks. Transportation Research Record, 2595 1: 108-118. doi:10.3141/2595-12
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Compound Gamma representation for modeling travel time variability in a traffic network
Kim, Jiwon and Mahmassani, Hani S. (2015) Compound Gamma representation for modeling travel time variability in a traffic network. Transportation Research Part B: Methodological, 80 40-63. doi:10.1016/j.trb.2015.06.011
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Kim, Jiwon and Mahmassani, Hani S. (2015) Spatial and temporal characterization of travel patterns in a traffic network using vehicle trajectories. Transportation Research Part C: Emerging Technologies, 59 375-390. doi:10.1016/j.trc.2015.07.010
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Kim, Jiwon and Mahmassani, Hani S. (2014) How many runs? Analytical method for optimal scenario sampling to estimate travel time variance in traffic networks. Transportation Research Record: Journal of the Transportation Research Board, 2467 1: 49-61. doi:10.3141/2467-06
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Kim, Jiwon and Mahmassani, Hani S. (2014) A finite mixture model of vehicle-to-vehicle and day-to-day variability of traffic network travel times. Transportation Research Part C: Emerging Technologies, 46 83-97. doi:10.1016/j.trc.2014.05.011
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Hou, Tian, Mahmassani, Hani S., Alfelor, Roemer M., Kim, Jiwon and Saberi, Meead (2013) Calibration of traffic flow models under adverse weather and application in mesoscopic network simulation. Transportation Research Record, 2391 2391: 92-104. doi:10.3141/2391-09
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Implementation and evaluation of weather-responsive traffic management strategies
Kim, Jiwon, Mahmassani, Hani S., Alfelor, Roemer, Chen, Ying, Hou, Tian, Jiang, Lan, Saberi, Meead, Verbas, Oemer and Zockaie, Ali (2013) Implementation and evaluation of weather-responsive traffic management strategies. Transportation Research Record, 2396 2396: 93-106. doi:10.3141/2396-11
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Scenario-based approach to analysis of travel time reliability with traffic simulation models
Kim, Jiwon, Mahmassani, Hani S., Vovsha, Peter, Stogios, Yannis and Dong, Jing (2013) Scenario-based approach to analysis of travel time reliability with traffic simulation models. Transportation Research Record: Journal of the Transportation Research Board, 2391 1: 56-68. doi:10.3141/2391-06
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Kim, Jiwon and Mahmassani, Hani S. (2011) Correlated parameters in driving behavior models: car-following example and implications for traffic microsimulation. Transportation Research Record, 2249 1: 62-77. doi:10.3141/2249-09
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Likelihood and duration of flow breakdown: modeling the effect of weather
Kim, Jiwon, Mahmassani, Hani S. and Dong, Jing (2010) Likelihood and duration of flow breakdown: modeling the effect of weather. Transportation Research Record, 2188 2188: 19-28. doi:10.3141/2188-03
Conference Publication
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Attention-based recurrent neural network for urban vehicle trajectory prediction
Choi, Seongjin, Kim, Jiwon and Yeo, Hwasoo (2019). Attention-based recurrent neural network for urban vehicle trajectory prediction. In: Elhadi Shakshuki, 10th International Conference on Ambient Systems, Networks and Technologies (ANT 2019) / The 2nd International Conference on Emerging Data and Industry 4.0 (EDI40 2019), Leuven, Belgium, (327-334). 29 April - 2 May, 2019. doi:10.1016/j.procs.2019.04.046
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Agent-based simulation modeling of a Bus Rapid Transit (BRT) station using smart card data
Ahn, Sanghyung, Hislop-Lynch, Samuel Richard, Kim, Jiwon and Zhu, Roy (2018). Agent-based simulation modeling of a Bus Rapid Transit (BRT) station using smart card data. In: Chan, V, DAmbrogio, A, Zacharewicz, G and Mustafee, N, 2017 Winter Simulation Conference, WSC 2017. 2017 Winter Simulation Conference, WSC 2017, Las Vegas, NV United States, (4538-4539). 3-6 December 2017. doi:10.1109/WSC.2017.8248193
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Inferring socioeconomic attributes of public transit passengers using classifiers
Faroqi, Hamed, Mesbah, Mahmoud and Kim, Jiwon (2018). Inferring socioeconomic attributes of public transit passengers using classifiers. In: ATRF 2018 - Australasian Transport Research Forum 2018, Proceedings. ATRF 2018 - Australasian Transport Research Forum 2018, Darwin, NT Australia, (). 30 October – 1 November 2018.
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A large scale neural network model for crash prediction in urban road networks
Wang, Guangxing and Kim, Jiwon (2017). A large scale neural network model for crash prediction in urban road networks. In: ATRF 2017 - Australasian Transport Research Forum 2017, Proceedings. ATRF 2017 - Australasian Transport Research Forum 2017, Auckland, New Zealand, (). 27 - 29 November 2017.
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Balancing computational requirements with performance in model predictive traffic control
Stebbins, Simon, Hickman, Mark, Kim, Jiwon and Vu, Hai L. (2017). Balancing computational requirements with performance in model predictive traffic control. In: ATRF 2017 - Australasian Transport Research Forum 2017, Proceedings. ATRF 2017 - Australasian Transport Research Forum 2017, Auckland, New Zealand, (). 27 - 29 November 2017.
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Identification of communities in urban mobility networks using multi-layer graphs of network traffic
Yildirimoglu, Mehmet and Kim, Jiwon (2017). Identification of communities in urban mobility networks using multi-layer graphs of network traffic. In: 20th EURO Working Group on Transportation Meeting, EWGT 2017, Budapest, Hungary, (1034-1041). 4-6 September 2017. doi:10.1016/j.trpro.2017.12.070
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Pedestrian tracking framework utilising computer vision for rapid analysis of public spaces
Hislop-Lynch, Samuel R., Ahn, SangHyung and Kim, Jiwon (2017). Pedestrian tracking framework utilising computer vision for rapid analysis of public spaces. In: ATRF 2017 - Australasian Transport Research Forum 2017, Proceedings. ATRF 2017 - Australasian Transport Research Forum 2017, Auckland, New Zealand, (). 27 - 29 November 2017.
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Spatial variable selection methods for network-wide short-term traffic prediction
Hasan, Md. Mahmud, Kim, Jiwon and Prato, Carlo (2017). Spatial variable selection methods for network-wide short-term traffic prediction. In: ATRF 2017 - Australasian Transport Research Forum 2017, Proceedings. ATRF 2017 - Australasian Transport Research Forum 2017, Auckland, New Zealand, (). 27 - 29 November 2017.
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Kim, Jiwon, Zheng, Kai, Corcoran, Jonathan, Ahn, Sanghyung and Papmanolis, Marty (2017). Trajectory Flow Map: Graph-based approach to analyse temporal evolution of aggregated traffic flows in large-scale urban networks. In: TRB 96th Annual Meeting Compendium of Papers. Transportation Research Board 96th Annual Meeting, Washington DC United States, (). December 2016.
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Mahmud Hasan, Md and Kim, Jiwon (2016). Analysing functional connectivity and causal dependence in road traffic networks with Granger causality. In: ATRF 2016 - Australasian Transport Research Forum 2016, Melbourne, VIC Australia, (). 16 – 18 November 2016.
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Stebbins, Simon, Kim, Jiwon, Hickman, Mark and Vu, Hai L. (2016). Combining model predictive intersection control with green light optimal speed advisory in a connected vehicle environment. In: ATRF 2016 - Australasian Transport Research Forum 2016, Proceedings. ATRF 2016 - Australasian Transport Research Forum 2016, Melbourne, VIC Australia, (). 16 – 18 November 2016.
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Graph-based analysis of city-wide traffic dynamics using time-evolving graphs of trajectory data
Kim, Jiwon, Zheng, Kai, Ahn, Sanghyung, Papamanolis, Marty and Chao, Pingfu (2016). Graph-based analysis of city-wide traffic dynamics using time-evolving graphs of trajectory data. In: ATRF 2016 - Australasian Transport Research Forum 2016, Proceedings. ATRF 2016 - Australasian Transport Research Forum 2016, Melbourne, VIC Australia, (). 16 – 18 November 2016.
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Ahn, SangHyung, Kim, Jiwon, Bekti, Antonius, Cheng, Liang-Chuan, Clark, Emma, Robertson, Michelle and Salita, Roland (2016). Real-time information system for spreading rail passengers across train carriages: Agent-based simulation study. In: ATRF 2016 - Australasian Transport Research Forum 2016, Proceedings. ATRF 2016 - Australasian Transport Research Forum 2016, Melbourne, VIC Australia, (). 16 – 18 November 2016.
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Wang, Guangxing and Kim, Jiwon (2016). The prediction of traffic congestion and incident on urban road networks using Naive Bayes classifier. In: ATRF 2016 - Australasian Transport Research Forum 2016, Melbourne, VIC Australia, (). 16 – 18 November 2016.
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Characterizing travel time distributions in earthmoving operations using GPS data
Ahn, Sanghyung, Kim, Jiwon, Dunston, Phillip S., Kandil, Amr and Martinez, Julio C. (2015). Characterizing travel time distributions in earthmoving operations using GPS data. In: William J. O'Brien and Simone Ponticelli, Proceedings of the 2015 International Workshop on Computing in Civil Engineering. 2015 International Workshop on Computing in Civil Engineering, Austin, TX, United States, (288-295). 21-23 June 2015. doi:10.1061/9780784479247.036
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Kim, Jiwon and Mahmassani, Hani S. (2015). Spatial and temporal characterization of travel patterns in a traffic network using vehicle trajectories. In: Masao Kuwahara, Hideyuki Kita and Yasuo Asakura, The 21st International Symposium on Transportation and Traffic Theory. International Symposium on Transportation and Traffic Theory, Kobe, Japan, (164-184). 5-7 August 2015. doi:10.1016/j.trpro.2015.07.010
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Kim, Jiwon and Mahmassani, Hani S. (2014). Compound gamma representation for modeling vehicle-to-vehicle and day-to-day travel time variability in a traffic network. In: TRB 93rd Annual Meeting Compendium of Papers. Transportation Research Board 93rd Annual Meeting, Washington, DC, United States, (). 12-16 January 2014.
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Kim, Jiwon, Mahmassani, Hani S., Hou, Tian and Alfelor, Roemer M. (2014). Development of real-time simulation-based decision support system for weather responsive traffic signal operations. In: 2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014. 2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014, Qingdao, China, (810-815). 8-11 October 2014. doi:10.1109/ITSC.2014.6957789
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Chen, Ying, Kim, Jiwon and Mahmassani, Hani S. (2014). Pattern recognition using clustering algorithm for scenario definition in traffic simulation-based decision support systems. In: 2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014. 2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014, Qingdao, China, (798-803). 8-11 October 2014. doi:10.1109/ITSC.2014.6957787
Other Outputs
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Too wet? Too cold? Too hot? This is how weather affects the trips we make
Corcoran, Jonathan, Pojani, Dorina, Rowe, Francisco, Zhou, Jiangping, Kim, Jiwon, Wei, Ming, Tao, Sui, Sigler, Thomas and Liu, Yan (2018, April 09). Too wet? Too cold? Too hot? This is how weather affects the trips we make. , .
Grants (Administered at UQ)
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Making Spatiotemporal Data More Useful: An Entity Linking Approach
(2020–2022) ARC Discovery Projects
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An Integrated Demographic and Transport Demand Modelling Framework (ID-TDM
(2019–2022) iMove Cooperative Research Centre
-
Data-driven Simulation of Large Traffic Networks using Trajectory Data
(2019–2022) ARC Discovery Early Career Researcher Award
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Real-time Analytics on Urban Trajectory Data for Road Traffic Management
(2019–2022) ARC Linkage Projects
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Urban mobility analytics-based crash risk prediction for real-time traffic incident management
(2018–2019) UQ Early Career Researcher
PhD and MPhil Supervision
Current Supervision
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Automatic detection and analysis of long-term changes in travel patterns of public transport passengers using Smart-Card data
Master Philosophy — Principal Advisor
Other advisors:
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Data fusion and urban trajectory reconstruction for city-wide traffic estimation and prediction
Master Philosophy — Principal Advisor
Other advisors:
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Prediction of Traffic Congestion and Incidents on Urban Road Networks Using Deep Learning
Doctor Philosophy — Principal Advisor
Other advisors:
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Developing a Model for Targeted Transit Advertising using Smart Card Data
Doctor Philosophy — Associate Advisor
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Visualisation of passenger and freight transport flows
Master Philosophy — Associate Advisor
Other advisors:
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Computer Vision Based Pedestrian Trajectory Analysis
Doctor Philosophy — Associate Advisor
Other advisors:
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Safety Evaluation on right turn traffic control strategies at signalized intersections using two-level hierarchical models with cross-level interaction
Doctor Philosophy — Associate Advisor
Other advisors:
Completed Supervision
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(2020) Doctor Philosophy — Principal Advisor
Other advisors:
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Understanding and Modelling the Car-Following Behaviour of Connected Vehicles
(2019) Doctor Philosophy — Associate Advisor
Other advisors:
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Computer vision based pedestrian trajectory analysis
(2018) Master Philosophy — Associate Advisor
Other advisors:
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(2018) Doctor Philosophy — Associate Advisor
Other advisors:
Possible Research Projects
Note for students: The possible research projects listed on this page may not be comprehensive or up to date. Always feel free to contact the staff for more information, and also with your own research ideas.
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Intelligent Transport Systems (ITS)
- Big data analytics for intelligent transport
- Data mining and artificial intelligence (AI) applications in traffic analysis
- Spatio-temporal analysis of trajectory data in road networks
- Data-driven approaches to traffic estimation and prediction
- Decision support systems for real-time traffic management and control
- Congestion management and avoidance
- Incident detection and traffic incident management
-
Travel time reliability
- Characterizing travel time variability patterns (e.g., vehicle-to-vehicle, day-to-day, and within-day variability)
- Analysis of network uncertainty sources and their impacts on travel time reliability
- Estimating the probability distribution of route travel times using multi-source data
- Development and use of travel time reliability performance indicators
- Analysis of travel time reliability in mixed traffic
-
Traffic flow theory and simulation
- Advanced analysis techniques for micro- and meso-scopic traffic simulation models (e.g., model calibration, input parameter sampling, sensitivity analysis, and uncertainty analysis)
- Analysis of traffic flow breakdown phenomena
- Modeling driver behavior and traffic flow characteristics under a connected and/or autonomous vehicle environment (e.g., V2V, V2I, and self-driving car)
- Analysis of traffic flow variables using new sources of data (e.g., GPS devices, RFID tags, radar, and video)
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Other topics
- Use of video data (e.g., CCTV) for road traffic management and control
- Resilient transport systems; vulnerability and risk assessment of road networks related to extreme weather events
Dr. Kim is also happy to consider other topics related to transport planning and operations, traffic modeling and analysis, and urban traffic management.
