The University of Queensland

MSGNN: A Multi-structured Graph Neural Network model for real-time incident prediction in large traffic networks

Tran, Thanh, He, Dan, Kim, Jiwon and Hickman, Mark (2023). MSGNN: A Multi-structured Graph Neural Network model for real-time incident prediction in large traffic networks. Transportation Research Part C: Emerging Technologies, 156 104354, 104354. doi: 10.1016/j.trc.2023.104354

A hierarchical multinomial logit model to examine the effects of signal strategies on right-turn crash injury severity at signalised intersections

Islam, Sheikh Manirul, Washington, Simon, Kim, Jiwon and Haque, Md Mazharul (2023). A hierarchical multinomial logit model to examine the effects of signal strategies on right-turn crash injury severity at signalised intersections. Accident Analysis and Prevention, 188 107091, 1-14. doi: 10.1016/j.aap.2023.107091

A Hierarchical Multinomial Logit model to examine the effects of signal strategies on right-turn crash risks by crash movement configuration

Islam, Sheikh Manirul, Washington, Simon, Kim, Jiwon and Haque, Md. Mazharul (2023). A Hierarchical Multinomial Logit model to examine the effects of signal strategies on right-turn crash risks by crash movement configuration. Accident Analysis and Prevention, 184 106993, 106993. doi: 10.1016/j.aap.2023.106993

Autonomous anomaly detection on traffic flow time series with reinforcement learning

He, Dan, Kim, Jiwon, Shi, Hua and Ruan, Boyu (2023). Autonomous anomaly detection on traffic flow time series with reinforcement learning. Transportation Research Part C: Emerging Technologies, 150 104089, 1-21. doi: 10.1016/j.trc.2023.104089

Estimating link flows in road networks with synthetic trajectory data generation: inverse reinforcement learning approach

Zhong, Miner, Kim, Jiwon and Zheng, Zuduo (2023). Estimating link flows in road networks with synthetic trajectory data generation: inverse reinforcement learning approach. IEEE Open Journal of Intelligent Transportation Systems, 4, 14-29. doi: 10.1109/ojits.2022.3233904

An efficient algorithm for maximum trajectory coverage query with approximation guarantee

He, Dan, Zhou, Thomas, Zhou, Xiaofang and Kim, Jiwon (2022). An efficient algorithm for maximum trajectory coverage query with approximation guarantee. IEEE Transactions on Intelligent Transportation Systems, PP (99), 1-13. doi: 10.1109/tits.2022.3207499

Transformer-based map-matching model with limited labeled data using transfer-learning approach

Jin, Zhixiong, Kim, Jiwon, Yeo, Hwasoo and Choi, Seongjin (2022). Transformer-based map-matching model with limited labeled data using transfer-learning approach. Transportation Research Part C: Emerging Technologies, 140 103668, 103668. doi: 10.1016/j.trc.2022.103668

A comprehensive analysis on the effects of signal strategies, intersection geometry, and traffic operation factors on right-turn crashes at signalised intersections: an application of hierarchical crash frequency model

Manirul Islam, Sheikh, Washington, Simon, Kim, Jiwon and Haque, Mazharul (2022). A comprehensive analysis on the effects of signal strategies, intersection geometry, and traffic operation factors on right-turn crashes at signalised intersections: an application of hierarchical crash frequency model. Accident Analysis and Prevention, 171 106663, 106663. doi: 10.1016/j.aap.2022.106663

Targeted advertising in the public transit network using smart card data

Faroqi, Hamed, Mesbah, Mahmoud, Kim, Jiwon and Khodaii, Ali (2022). Targeted advertising in the public transit network using smart card data. Networks and Spatial Economics, 22 (1), 97-124. doi: 10.1007/s11067-022-09558-9

Joint prediction of next location and travel time from urban vehicle trajectories using long short-term memory neural networks

Sun, Jie and Kim, Jiwon (2021). Joint prediction of next location and travel time from urban vehicle trajectories using long short-term memory neural networks. Transportation Research. Part C: Emerging Technologies, 128 103114, 103114. doi: 10.1016/j.trc.2021.103114

TrajGAIL: Generating urban vehicle trajectories using generative adversarial imitation learning

Choi, Seongjin, Kim, Jiwon and Yeo, Hwasoo (2021). TrajGAIL: Generating urban vehicle trajectories using generative adversarial imitation learning. Transportation Research Part C: Emerging Technologies, 128 103091, 103091. doi: 10.1016/j.trc.2021.103091

Assessing traffic disturbance, efficiency, and safety of the mixed traffic flow of connected vehicles and traditional vehicles by considering human factors

Sharma, Anshuman, Zheng, Zuduo, Kim, Jiwon, Bhaskar, Ashish and Mazharul Haque, Md. (2021). Assessing traffic disturbance, efficiency, and safety of the mixed traffic flow of connected vehicles and traditional vehicles by considering human factors. Transportation Research Part C: Emerging Technologies, 124 102934, 1-21. doi: 10.1016/j.trc.2020.102934

Activity-trip based model for friend recommendation with transit smart card records

Faroqi, Hamed, Mesbah, Mahmoud and Kim, Jiwon (2020). Activity-trip based model for friend recommendation with transit smart card records. Journal of Urban Planning and Development, 146 (4) 04020041, 04020041. doi: 10.1061/(asce)up.1943-5444.0000624

Is an informed driver a better decision maker? A grouped random parameters with heterogeneity-in-means approach to investigate the impact of the connected environment on driving behaviour in safety-critical situations

Sharma, Anshuman, Zheng, Zuduo, Kim, Jiwon, Bhaskar, Ashish and Haque, Mazharul (2020). Is an informed driver a better decision maker? A grouped random parameters with heterogeneity-in-means approach to investigate the impact of the connected environment on driving behaviour in safety-critical situations. Analytic Methods in Accident Research, 27 100127, 100127. doi: 10.1016/j.amar.2020.100127

Modelling socioeconomic attributes of public transit passengers

Faroqi, Hamed, Mesbah, Mahmoud and Kim, Jiwon (2020). Modelling socioeconomic attributes of public transit passengers. Journal of Geographical Systems, 22 (4), 519-543. doi: 10.1007/s10109-020-00328-0

Deep-learning based urban vehicle trajectory prediction

Choi, Seongjin, Kim, Jiwon, Yu, Hwapyeong, Ka, Dongho and Yeo Hwasoo (2019). Deep-learning based urban vehicle trajectory prediction. Journal of Korean Society of Transportation, 37 (5), 422-429. doi: 10.7470/jkst.2019.37.5.422

Behavioural advertising in the public transit network

Faroqi, Hamed, Mesbah, Mahmoud and Kim, Jiwon (2019). Behavioural advertising in the public transit network. Research in Transportation Business and Management, 32 100421, 100421. doi: 10.1016/j.rtbm.2019.100421

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 5070794, 1-16. doi: 10.1155/2019/5070794

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), 04019008. doi: 10.1061/JTEPBS.0000222

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, 2673 (4), 036119811983796-684. doi: 10.1177/0361198119837964

Forecasting pedestrian movements using recurrent neural networks: an application of crowd monitoring data

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, 382. doi: 10.3390/s19020382

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

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, 20 (7) 8479365, 2540-2549. doi: 10.1109/TITS.2018.2868122

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

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

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

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

Route choice stickiness of public transport passengers: measuring habitual bus ridership behaviour using smart card data

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

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 1318945, 1-15. doi: 10.1155/2017/1318945

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

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

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

Spatial and temporal characterization of travel patterns in a traffic network using vehicle trajectories

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

How many runs? Analytical method for optimal scenario sampling to estimate travel time variance in traffic networks

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

A finite mixture model of vehicle-to-vehicle and day-to-day variability of traffic network travel times

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

Calibration of traffic flow models under adverse weather and application in mesoscopic network simulation

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

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

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

Correlated parameters in driving behavior models: car-following example and implications for traffic microsimulation

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

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

Map-matching on Wireless Traffic Sensor Data with a Sequence-to-Sequence Model

Zhu, Zichun, He, Dan, Hua, Wen, Kim, Jiwon and Shi, Hua (2023). Map-matching on Wireless Traffic Sensor Data with a Sequence-to-Sequence Model. IEEE. doi: 10.1109/mdm58254.2023.00048

An autonomous eco-driving strategy for mixed traffic in the vicinity of signalized intersection using deep reinforcement learning

Yang, Zhiwei, Zheng, Zuduo, Kim, Jiwon and Rakha, Hesham (2023). An autonomous eco-driving strategy for mixed traffic in the vicinity of signalized intersection using deep reinforcement learning. Transportation Research Board Annual Meeting, Washington, DC USA, 8-12 January 2023.

Automatic traffic flow anomaly detection with reinforcement learning

He, Dan, Kim, Jiwon, Ruan, Boyu and Shi, Hua (2023). Automatic traffic flow anomaly detection with reinforcement learning. Transportation Research Board Annual Meeting, Washington, DC USA, 8-12 January 2023.

Interpretable data-driven car-following modelling with adversarial inverse reinforcement learning

Lin, Lin, Kim, Jiwon, Sun, Jie and Ahn, Sanghyung (2023). Interpretable data-driven car-following modelling with adversarial inverse reinforcement learning. Transportation Research Board Annual Meeting, Washington, DC, United States, 8-12 January 2023.

MSGNN: a multi-structured graph neural network model for real-time incident prediction in large traffic networks

Tran, Thanh, He, Dan, Kim, Jiwon and Hickman, Mark (2023). MSGNN: a multi-structured graph neural network model for real-time incident prediction in large traffic networks. Transportation Research Board Annual Meeting, Washington, DC, United States, 8-12 January 2023.

Multivariate time-varying Kalman filter approach for cycle-based maximum queue length estimation

Abewickrema, Wanuji, Yildirimoglu, Mehmet and Kim, Jiwon (2023). Multivariate time-varying Kalman filter approach for cycle-based maximum queue length estimation. Transportation Research Board Annual Meeting, Washington, DC United States, 8-12 January.

A cooperative eco-driving system for mixed traffic on urban roads

Yang, Zhiwei, Zheng, Zuduo, Kim, Jiwon and Rakha, Hesham (2022). A cooperative eco-driving system for mixed traffic on urban roads. Australasian Transport Research Forum, Adelaide, 28-30 September 2022.

Online traffic incident prediction with hybrid graph-based neural network and continual learning

Tran, Thanh, He, Dan, Kim, Jiwon and Hickman, Mark (2022). Online traffic incident prediction with hybrid graph-based neural network and continual learning. Australasian Transport Research Forum, Adelaide, SA Australia, 28-30 September 2022.

Threshold-free anomaly detection on traffic flow data with reinforcement learning

He, Dan, Ruan, Boyu, Kim, Jiwon and Shi, Hua (2022). Threshold-free anomaly detection on traffic flow data with reinforcement learning. Australasian Transport Research Forum, Adelaide, SA Australia, 28-30 September 2022.

Multivariate time-varying Kalman filter approach for cycle-based maximum queue length estimation

Abewickrema, Wanuji, Yildirimoglu, Mehmet and Kim, Jiwon (2022). Multivariate time-varying Kalman filter approach for cycle-based maximum queue length estimation. Australasian Transport Research Forum, Adelaide, SA, Australia, 28-30 September 2022.

Car following modelling with constrained generative adversarial imitation learning

Lin, Lin, Kim, Jiwon and Ahn, Sanghyung (2021). Car following modelling with constrained generative adversarial imitation learning. Australasian Transport Research Forum, Brisbane, QLD, Australia, 8-10 December 2021.

Data-driven traffic incident prediction with hybrid graph-based neural network

Tran, Thanh, He, Dan, Kim, Jiwon and Hickman, Mark (2021). Data-driven traffic incident prediction with hybrid graph-based neural network. Australasian Transport Research Forum, Brisbane, QLD, Australia, 8-10 December 2021.

Estimating link flows from limited traffic volume and sparse trajectory data: reinforcement learning approaches

Zhong, Miner, Kim, Jiwon and Zheng, Zuduo (2021). Estimating link flows from limited traffic volume and sparse trajectory data: reinforcement learning approaches. Transportation Research Board Annual Meeting, Washington, DC, United States, 25-29 January 2021.

Joint prediction of next location and travel time from urban vehicle trajectories using long short-term memory neural networks

Sun, Jie and Kim, Jiwon (2021). Joint prediction of next location and travel time from urban vehicle trajectories using long short-term memory neural networks. Transportation Research Board Annual Meeting, Washington, DC, United States, 25-29 January 2021.

Maximum queue length estimation at signalized intersections using shockwave theory and Kalman filter

Abewickrema, Wanuji, Yildirimoglu, Mehmet and Kim, Jiwon (2021). Maximum queue length estimation at signalized intersections using shockwave theory and Kalman filter. Australasian Transport Research Forum 2021, Brisbane, QLD Australia, 8-10 December 2021. Australasian Transport Research Forum.

Network-wide traffic simulation with multi-agent imitation learning

Sun, Jie and Kim, Jiwon (2021). Network-wide traffic simulation with multi-agent imitation learning. Australasian Transport Research Forum, Brisbane, QLD, Australia, 8-10 December 2021.

TrajGAIL: generating urban vehicle trajectories using generative adversarial imitation learning

Choi, Seongjin, Kim, Jiwon and Yeo, Hwasoo (2021). TrajGAIL: generating urban vehicle trajectories using generative adversarial imitation learning. Transportation Research Board Annual Meeting, Washington, DC, United States, 25-29 January 2021.

Route reconstruction using low-quality bluetooth readings

Xu, Yehong, He, Dan, Chao, Pingfu, Kim, Jiwon, Hua, Wen and Zhou, Xiaofang (2020). Route reconstruction using low-quality bluetooth readings. 28th International Conference on Advances in Geographic Information Systems, Online, 3 - 6 November 2020. New York NY, United States: Association for Computing Machinery. doi: 10.1145/3397536.3422224

Drone-based vehicle identification: an empirical study of convolutional neural network performance

Hislop-Lynch, Samuel, Ahn, Sanghyung and Kim, Jiwon (2020). Drone-based vehicle identification: an empirical study of convolutional neural network performance. Transportation Research Board Annual Meeting, Washington, DC, United States, 12–16 January 2020.

Incorporating network traffic state for urban vehicle trajectory prediction

Choi, Seongjin, Kim, Jiwon and Yeo, Hwasoo (2020). Incorporating network traffic state for urban vehicle trajectory prediction. Transportation Research Board Annual Meeting, Washington, DC, United States, 12–16 January 2020.

Investigating the correlation between activity similarity and trip similarity of public transit passengers using smart card data

Faroqi, Hamed, Mesbah, Mahmoud and Kim, Jiwon (2020). Investigating the correlation between activity similarity and trip similarity of public transit passengers using smart card data. World Conference on Transport Research, Mumbai, India, 26-31 May 2019. Amsterdam, Netherlands: Elsevier. doi: 10.1016/j.trpro.2020.08.249

Investigating the impact of the connected environment on driver response time in car-following scenarios

Sharma, Anshuman, Zheng, Zuduo, Kim, Jiwon, Bhaskar, Ashish and Haque, Mazharul (2020). Investigating the impact of the connected environment on driver response time in car-following scenarios. Transportation Research Board Annual Meeting, Washington, DC, United States, 12-16 January 2020.

Real-time prediction of arterial vehicle trajectories: an application to predictive route guidance for an emergency vehicle

Choi, Seongjin, Kim, Jiwon, Yu, Hwapyeong and Yeo, Hwasoo (2019). Real-time prediction of arterial vehicle trajectories: an application to predictive route guidance for an emergency vehicle. 2019 IEEE Intelligent Transportation Systems Conference (ITSC), Auckland, New Zealand, 27-30 October 2019. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/ITSC.2019.8917122

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. 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, 29 April - 2 May, 2019. Amsterdam, Netherlands: Elsevier B.V.. doi: 10.1016/j.procs.2019.04.046

Estimating and comparing response times in traditional and connected environments

Sharma, Anshuman, Zheng, Zuduo, Kim, Jiwon, Bhaskar, Ashish and Haque, Mazharul (2019). Estimating and comparing response times in traditional and connected environments. Transportation Research Board Annual Meeting, Washington, DC, United States, 13 - 17 January 2019.

Real-time prediction of inter-region traffic flow using urban vehicle trajectory data: a deep learning approach

Wang, Guangxing and Kim, Jiwon (2019). Real-time prediction of inter-region traffic flow using urban vehicle trajectory data: a deep learning approach. Transportation Research Board Annual Meeting, Washington, DC, United States, 13-17 January 2019.

A large-scale neural network model for real-time crash prediction in urban road networks

Wang, Guangxing and Kim, Jiwon (2018). A large-scale neural network model for real-time crash prediction in urban road networks. Transportation Research Board Annual Meeting, Washington, DC USA, 7-11 January 2018.

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 Board Annual Meeting, Washington, DC USA, 7-11 January 2018.

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. 2017 Winter Simulation Conference, WSC 2017, Las Vegas, NV United States, 3-6 December 2017. Piscataway, NJ United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/WSC.2017.8248193

Balancing computational requirements with performance in model predictive traffic control

Stebbins, Simon, Hickman, Mark, Kim, Jiwon and Vu, Hai (2018). Balancing computational requirements with performance in model predictive traffic control. Transportation Research Board Annual Meeting, Washington, DC, United States, 7-11 January 2018.

Identifying relevant predictors and spatial relations of traffic parameters for network-wide short-term traffic prediction

Hasan, Md Mahmud, Kim, Jiwon and Prato, Carlo (2018). Identifying relevant predictors and spatial relations of traffic parameters for network-wide short-term traffic prediction. Transportation Research Board Annual Meeting, Washington, DC, United States, 7-11 January 2018.

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. ATRF 2018 - Australasian Transport Research Forum 2018, Darwin, NT Australia, 30 October – 1 November 2018. Canberra ACT Australia: ATRF, Commonwealth of Australia.

Investigating the correlation between activity similarity and trip similarity of public transit passengers using smart card data

Faroqi, Hamed, Mesbah, Mahmoud and Kim, Jiwon (2018). Investigating the correlation between activity similarity and trip similarity of public transit passengers using smart card data. Australasian Transport Research Forum, Darwin, NT, Australia, 30 October – 1 November 2018.

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. ATRF 2017 - Australasian Transport Research Forum 2017, Auckland, New Zealand, 27 - 29 November 2017. Canberra, ACT Australia: ATRF, Commonwealth of Australia.

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. ATRF 2017 - Australasian Transport Research Forum 2017, Auckland, New Zealand, 27 - 29 November 2017. Canberra ACT Australia: ATRF, Commonwealth of Australia.

Combining intersection control schedule optimisation with green light optimal speed advisory in a connected vehicle environment

Stebbins, Simon, Hickman, Mark, Kim, Jiwon and Vu, Hai (2017). Combining intersection control schedule optimisation with green light optimal speed advisory in a connected vehicle environment. Transportation Research Board Annual Meeting, Washington, DC, United States, 8-12 January 2017.

Granger causality method to detect spatial dependency in a road traffic network and its application in traffic flow prediction

Hasan, Md Mahmud and Kim, Jiwon (2017). Granger causality method to detect spatial dependency in a road traffic network and its application in traffic flow prediction. Transportation Research Board Annual Meeting, Washington, DC, United States, 8 - 12 January 2017.

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. 20th EURO Working Group on Transportation Meeting, EWGT 2017, Budapest, Hungary, 4-6 September 2017. Elsevier. doi: 10.1016/j.trpro.2017.12.070

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. ATRF 2017 - Australasian Transport Research Forum 2017, Auckland, New Zealand, 27 - 29 November 2017. Canberra, ACT Australia: ATRF, Commonwealth of Australia.

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. ATRF 2017 - Australasian Transport Research Forum 2017, Auckland, New Zealand, 27 - 29 November 2017. Canberra, ACT Australia: ATRF, Commonwealth of Australia.

Trajectory Flow Map: Graph-based approach to analyse temporal evolution of aggregated traffic flows in large-scale urban networks

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. Transportation Research Board 96th Annual Meeting, Washington DC United States, December 2016. Washington, DC United States: Transportation Research Board.

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 Board Annual Meeting, Washington, DC USA, 10-14 January 2016.

Analysing functional connectivity and causal dependence in road traffic networks with Granger causality

Mahmud Hasan, Md and Kim, Jiwon (2016). Analysing functional connectivity and causal dependence in road traffic networks with Granger causality. ATRF 2016 - Australasian Transport Research Forum 2016, Melbourne, VIC Australia, 16 – 18 November 2016. Canberra, ACT Australia: ATRF, Commonwealth of Australia.

Characterizing green light optimal speed advisory trajectories for platoon-based optimization

Stebbins, Simon, Kim, Jiwon, Hickman, Mark and Vu, Hai (2016). Characterizing green light optimal speed advisory trajectories for platoon-based optimization. Transportation Research Board Annual Meeting, Washington, DC, United States, 10-14 January 2016.

Combining model predictive intersection control with green light optimal speed advisory in a connected vehicle environment

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. ATRF 2016 - Australasian Transport Research Forum 2016, Melbourne, VIC Australia, 16 – 18 November 2016. Canberra, ACT Australia: ATRF, Commonwealth of Australia.

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. ATRF 2016 - Australasian Transport Research Forum 2016, Melbourne, VIC Australia, 16 – 18 November 2016. Canberra, ACT Australia: ATRF, Commonwealth of Australia.

Network-wide time-dependent link travel time distributions with temporal and spatial correlations

Zockaie, Ali, Mahmassani, Hani S. and Kim, Jiwon (2016). Network-wide time-dependent link travel time distributions with temporal and spatial correlations. Transportation Research Board Annual Meeting, Washington, DC, United States, 10-14 January 2016.

Real-time information system for spreading rail passengers across train carriages: Agent-based simulation study

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. ATRF 2016 - Australasian Transport Research Forum 2016, Melbourne, VIC Australia, 16 – 18 November 2016. Canberra, ACT Australia: ATRF, Commonwealth of Australia.

The prediction of traffic congestion and incident on urban road networks using Naive Bayes classifier

Wang, Guangxing and Kim, Jiwon (2016). The prediction of traffic congestion and incident on urban road networks using Naive Bayes classifier. ATRF 2016 - Australasian Transport Research Forum 2016, Melbourne, VIC Australia, 16 – 18 November 2016. Canberra, ACT Australia: ATRF, Commonwealth of Australia.

Trajectory clustering for discovering spatial traffic flow patterns in road networks

Kim, Jiwon and Mahmassani, Hani S. (2015). Trajectory clustering for discovering spatial traffic flow patterns in road networks. Transportation Research Board Annual Meeting, Washington, DC USA, 11-15 January 2015.

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. 2015 International Workshop on Computing in Civil Engineering, Austin, TX, United States, 21-23 June 2015. Reston, VA, United States: American Society of Civil Engineers. doi: 10.1061/9780784479247.036

On-line implementation and evaluation of weather responsive coordinated signal timing operations

Chen, Ying, Mahmassani, Hani S., Hong, Zihan, Hou, Tian, Kim, Jiwon, Halat, Hooram and Alfelor, Roemer (2015). On-line implementation and evaluation of weather responsive coordinated signal timing operations. Transportation Research Board Annual Meeting, Washington, DC, United States, 11-15 January 2015.

Spatial and temporal characterization of travel patterns in a traffic network using vehicle trajectories

Kim, Jiwon and Mahmassani, Hani S. (2015). Spatial and temporal characterization of travel patterns in a traffic network using vehicle trajectories. International Symposium on Transportation and Traffic Theory, Kobe, Japan, 5-7 August 2015. Amsterdam, Netherlands: Elsevier. doi: 10.1016/j.trpro.2015.07.010

A finite mixture model of vehicle-to-vehicle and day-to-day variability of traffic network travel times

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 Board Annual Meeting, Washington, DC, United States, 12-16 January 2014.

Compound gamma representation for modeling vehicle-to-vehicle and day-to-day travel time variability in a traffic network

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. Transportation Research Board 93rd Annual Meeting, Washington, DC, United States, 12-16 January 2014. Washington, DC, United States: Transportation Research Board.

Compound gamma representation for modeling vehicle-to-vehicle and day-to-day travel time variability in a traffic network

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. Transportation Research Board Annual Meeting, Washington, DC, United States, 12-16 January 2014.

Development of real-time simulation-based decision support system for weather responsive traffic signal operations

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. 2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014, Qingdao, China, 8-11 October 2014. Piscataway, NJ, United States: IEEE. doi: 10.1109/ITSC.2014.6957789

How many runs? Analytical method for optimal scenario sampling to estimate the variance of travel time distributions in vehicular traffic networks

Kim, Jiwon and Mahmassani, Hani (2014). How many runs? Analytical method for optimal scenario sampling to estimate the variance of travel time distributions in vehicular traffic networks. Transportation Research Board Annual Meeting, Washington, DC, United States, 12-16 January 2014.

Pattern recognition using clustering algorithm for scenario definition in traffic simulation-based decision support systems

Chen, Ying, Kim, Jiwon and Mahmassani, Hani S. (2014). Pattern recognition using clustering algorithm for scenario definition in traffic simulation-based decision support systems. 2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014, Qingdao, China, 8-11 October 2014. Piscataway, NJ, United States: IEEE. doi: 10.1109/ITSC.2014.6957787

Toward capturing sources of travel time unreliability in microscopic traffic models: driver heterogeneity, flow breakdown, and crash occurrence

Talebpour, Alireza, Mahmassani, Hani S. and Kim, Jiwon (2013). Toward capturing sources of travel time unreliability in microscopic traffic models: driver heterogeneity, flow breakdown, and crash occurrence. Transportation Research Board Annual Meeting, Washington, DC USA, 13-17 January 2013.

Calibration of Traffic Flow Models Under Adverse Weather and Application in Mesoscopic Network Simulation

Hou, Tian , Mahmassani, Hani , Alfelor, Roemer , Kim, Jiwon and Saberi, Meead (2013). Calibration of Traffic Flow Models Under Adverse Weather and Application in Mesoscopic Network Simulation. Transportation Research Board Annual Meeting, Washington, DC, United States, 13-17 January 2013.

Implementation and evaluation of weather-responsive traffic management strategies: insight from different networks

Kim, Jiwon, Mahmassani, Hani, Alfelor, Roemer, Chen, Ying, Hou, Tian, Jiang, Lan, Saberi, Meead, Verbas, Ömer and Zockaie, Ali (2013). Implementation and evaluation of weather-responsive traffic management strategies: insight from different networks. Transportation Research Board Annual Meeting, Washington, DC, United States, 13-17 January 2013.

Scenario-based approach to analysis of travel time reliability with traffic simulation models

Kim, Jiwon, Mahmassani, Hani, Vovsha, Peter, Stogios, Yannis and Dong, Jing (2013). Scenario-based approach to analysis of travel time reliability with traffic simulation models. Transportation Research Board Annual Meeting, Washington, DC, United States, 13-17 January 2013.

Correlated Parameters in Driving Behavior Models: Car-Following Example and Implications for Traffic Microsimulation

Kim, Jiwon and Mahmassani, Hani S. (2011). Correlated Parameters in Driving Behavior Models: Car-Following Example and Implications for Traffic Microsimulation. Transportation Research Board Annual Meeting, Washington, DC, United States, 23-27 January 2011.

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 Board Annual Meeting, Washington, DC, United States, 10-14 January 2010.

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, 04 09). Too wet? Too cold? Too hot? This is how weather affects the trips we make