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2025 Journal Article Understanding everyday public transit travel habits: A measurement framework for the peakedness of departure time distributionsKim, Jiwon and Corcoran, Jonathan (2025). Understanding everyday public transit travel habits: A measurement framework for the peakedness of departure time distributions. Travel Behaviour and Society, 41 101040, 101040. doi: 10.1016/j.tbs.2025.101040 |
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2025 Journal Article Activity-aware urban area embedding with contrastive learning for intelligent transportation systems applicationsLi, Gen, Feng, Tao, He, Dan, Yan, Li and Kim, Jiwon (2025). Activity-aware urban area embedding with contrastive learning for intelligent transportation systems applications. Transportation Research Part C: Emerging Technologies, 178 105252, 105252-178. doi: 10.1016/j.trc.2025.105252 |
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2025 Journal Article An Ensemble Deep Learning Framework for Real-Time Queue Length Estimation at Signalized IntersectionsAbewickrema, Wanuji, Yildirimoglu, Mehmet and Kim, Jiwon (2025). An Ensemble Deep Learning Framework for Real-Time Queue Length Estimation at Signalized Intersections. Data Science for Transportation, 7 (2) 15. doi: 10.1007/s42421-025-00129-1 |
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2025 Journal Article Integrating road network operations planning into real-time traffic management: A conceptual frameworkKeblawi, Mahmud, Maripini, Himabindu, Kim, Jiwon, Hickman, Mark, Zheng, Zuduo and Yildirimoglu, Mehmet (2025). Integrating road network operations planning into real-time traffic management: A conceptual framework. Transportation Research Interdisciplinary Perspectives, 32 101525, 101525. doi: 10.1016/j.trip.2025.101525 |
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2025 Journal Article A gentle introduction and tutorial on Deep Generative Models in transportation researchChoi, Seongjin, Jin, Zhixiong, Ham, Seung Woo, Kim, Jiwon and Sun, Lijun (2025). A gentle introduction and tutorial on Deep Generative Models in transportation research. Transportation Research Part C: Emerging Technologies, 176 105145, 105145-176. doi: 10.1016/j.trc.2025.105145 |
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2025 Journal Article Eco-cooperative adaptive cruise control for platoons in mixed traffic using single-agent and multi-agent reinforcement learningYang, Zhiwei, Zheng, Zuduo, Kim, Jiwon and Rakha, Hesham (2025). Eco-cooperative adaptive cruise control for platoons in mixed traffic using single-agent and multi-agent reinforcement learning. Transportation Research Part D: Transport and Environment, 142 104658, 104658-142. doi: 10.1016/j.trd.2025.104658 |
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2025 Journal Article A Survey and Experimental Study on Neural Trajectory-User Linking ModelsShi, Hua, He, Dan, Jin, Fengmei, Hua, Wen, Kim, Jiwon, Wang, Qilin and Zhou, Xiaofang (2025). A Survey and Experimental Study on Neural Trajectory-User Linking Models. IEEE Transactions on Knowledge and Data Engineering, PP (99), 1-17. doi: 10.1109/TKDE.2025.3607902 |
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2024 Journal Article Modelling two-dimensional driving behaviours at unsignalised intersection using multi-agent imitation learningSun, Jie and Kim, Jiwon (2024). Modelling two-dimensional driving behaviours at unsignalised intersection using multi-agent imitation learning. Transportation Research Part C: Emerging Technologies, 165 104702, 1-16. doi: 10.1016/j.trc.2024.104702 |
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2024 Journal Article Eco-driving strategies using reinforcement learning for mixed traffic in the vicinity of signalized intersectionsYang, Zhiwei, Zheng, Zuduo, Kim, Jiwon and Rakha, Hesham (2024). Eco-driving strategies using reinforcement learning for mixed traffic in the vicinity of signalized intersections. Transportation Research Part C: Emerging Technologies, 165 104683, 1-35. doi: 10.1016/j.trc.2024.104683 |
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2023 Journal Article Toward data-driven simulation of network-wide traffic: a multi-agent imitation learning approach using urban vehicle trajectory dataSun, Jie and Kim, Jiwon (2023). Toward data-driven simulation of network-wide traffic: a multi-agent imitation learning approach using urban vehicle trajectory data. IEEE Transactions on Intelligent Transportation Systems, 25 (7), 6645-6657. doi: 10.1109/tits.2023.3343452 |
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2023 Journal Article Variables affecting the risk of vehicle collisions in Australian road tunnelsHidayat, Edwin, Lange, David, Karlovsek, Jurij and Kim, Jiwon (2023). Variables affecting the risk of vehicle collisions in Australian road tunnels. Journal of Road Safety, 34 (4), 20-30. doi: 10.33492/JACRS-D-22-00032 |
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2023 Journal Article MSGNN: A Multi-structured Graph Neural Network model for real-time incident prediction in large traffic networksTran, 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 |
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2023 Journal Article Multivariate time-varying Kalman filter approach for cycle-based maximum queue length estimationAbewickrema, Wanuji, Yildirimoglu, Mehmet and Kim, Jiwon (2023). Multivariate time-varying Kalman filter approach for cycle-based maximum queue length estimation. Transportation Research Part C: Emerging Technologies, 154 104238, 1-19. doi: 10.1016/j.trc.2023.104238 |
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2023 Journal Article A hierarchical multinomial logit model to examine the effects of signal strategies on right-turn crash injury severity at signalised intersectionsIslam, 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 |
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2023 Journal Article A Hierarchical Multinomial Logit model to examine the effects of signal strategies on right-turn crash risks by crash movement configurationIslam, 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 |
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2023 Journal Article Autonomous anomaly detection on traffic flow time series with reinforcement learningHe, 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 |
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2023 Journal Article Estimating link flows in road networks with synthetic trajectory data generation: inverse reinforcement learning approachZhong, 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 |
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2022 Journal Article An efficient algorithm for maximum trajectory coverage query with approximation guaranteeHe, 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 |
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2022 Journal Article Transformer-based map-matching model with limited labeled data using transfer-learning approachJin, 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 |
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2022 Journal Article 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 modelManirul 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 |
