Research
(2021 - present)
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SCI/ESCI/SCOPUS Journals (Total: 4, First author: 3)
SCI/ESCI/SCOPUS Journals (Total: 4, First author: 3)
Choi, J. & Kim, D. K. (2025). Vehicle Trajectory Reconstruction with Estimation of Shockwave Speed Using Traffic Sensor and Probe Vehicle Data. 2025 IEEE 28th International Conference on Intelligent Transportation Systems (ITSC) [Link]
Vehicle trajectories provide both spatiotemporal and attribute information for traffic management. Since traffic sensors and probe vehicles cannot cover all road segments, gathering all observed vehicle trajectories is challenging. Although some studies have proposed data-fusion methods, errors still arise during congestion propagation due to the driver’s reaction times and varying shockwave speeds under different conditions. This study reconstructs vehicle trajectories with shockwave speed estimation. We assume an environment with a virtual traffic sensor and randomly distributed probe vehicles. Our method estimates shockwave speed by detecting jerks in speed profiles of probe vehicles and interpolates shockwave speed using a radial basis function. Trajectories are reconstructed via speed correction and data assimilation grounded in a car-following model. The result of shockwave speed estimation shows the trend between shockwave speed and traffic state. The shockwave speed is higher when the traffic state is under transition flow with deceleration. We evaluate our approach on the Next-Generation Simulation (NGSIM) dataset and demonstrate lower errors than other methods, performing a mean absolute error of 24.76 m in position and 2.44 m/s in speed. This method can support more accurate trajectory reconstruction under various traffic environments.
Kim, B. Y. H., Joo, Y. J., Choi, J., & Kim, D. K. (2025). Queue Length-Based Priority Strategy for Unsignalized Intersections in Mixed-Traffic Environments. Journal of Transportation Engineering, Part A: Systems, 151(9), 04025067. [Link]
This article presents an intersection control strategy involving a mix of connected and autonomous vehicles (CAV) and human-driven vehicles (HDV). A queue length-based priority strategy for multilane unsignalized intersections using calibrated microscopic traffic simulation is proposed in the article. In the strategy, the right of way of a CAV is given according to the waiting queue of its lane. The strategy was implemented at a three-lane four-leg intersection, and its efficiency was compared with that of the conventional fixed signal strategy. The queue length-based priority strategy with fixed and dynamic traffic signal strategies is also extensively compared. The strategy involves not only the idea of responding to the queue but also incorporates vehicles-to-everything (V2X) behaviors into the calculation. The total traffic time graphs of each strategy show that the priority strategy significantly reduces the delay compared to fixed or dynamic traffic signals. The proposed strategy has the potential for application in future road environments and improvements because the effects vary with the increase in CAVs. New criteria for removing traffic signals is also suggested by comparing the intersection control strategies for which total travel time can be reduced by a maximum 25.4% according to the increase in the CAV market penetration rates. The safety indicators among strategies are also compared to ensure that the proposed strategy is applicable to mixed traffic intersections.
Choi, J., Joo, Y. J., & Kim, D. K. (2024). Effects of heterogeneity in driving manoeuvres on calibrating car-following models at a roundabout. Transportmetrica B: Transport Dynamics, 12(1), 2386537. [Link]
Choi, J., Joo, Y. J., & Kim, D. K. (2024). Effects of heterogeneity in driving manoeuvres on calibrating car-following models at a roundabout. Transportmetrica B: Transport Dynamics, 12(1), 2386537. [Link]
This study examines the impact of varied driving manoeuvres – such as entry, circulation, and exit – at roundabouts on the calibration of car-following models. We compare calibrated parameters across three models using car-following trajectories from naturalistic driving data. Subsequently, we assess spatial distributions of calibration errors and evaluate model performances. To ensure fidelity to driving statistics, we validate the distributional similarity with ground truth data through microscopic simulation using Hellinger distance and Kullback-Leibler divergence. Our findings reveal that the car-following models demonstrate improved accuracy when factoring in heterogeneity inherent in roundabout manoeuvres. The Krauss model demonstrates markedly improved accuracy in distributional similarity of gap, velocity, and time-to-collision compared to baseline models. It also reproduces time-to-collision values below one second during circulation manoeuvres. The study underscores the efficacy of the Krauss model, particularly when precisely calibrated for roundabout manoeuvres, in accurately simulating driving behaviours within microscopic simulations.
Choi, J., & Kim, D. K. (2024). Calibration and validation of the rule-based human driver model for car-following behaviors at roundabout using naturalistic driving data. Asian Transport Studies, 10, 100129. [Link]
Choi, J., & Kim, D. K. (2024). Calibration and validation of the rule-based human driver model for car-following behaviors at roundabout using naturalistic driving data. Asian Transport Studies, 10, 100129. [Link]
Understanding driver behavior is crucial for introducing roundabouts. This study focuses on calibrating the parameters of the car-following model using naturalistic data and analyzing the appropriateness of different car-following models on the roundabout. We utilize rounD trajectory dataset. This dataset allows for the precise definition of lead and follow vehicles, enabling the calibration of model parameters accordingly. We compared the calibration results for roundabouts with those obtained for signalized intersections from CitySim. Our results show that the Krauss and intelligent driver models (IDM) achieve mean absolute percentage errors of 10.09% and 23.21%, respectively. Furthermore, IDM exhibited higher errors in the circulation segment of the roundabout, while in the exit segment, the Krauss model showed elevated errors. It contrasted with the homogeneous results obtained in the signalized intersection. These findings provide valuable insights into driver's behavior on roundabouts.
Ongoing Works (Total: 3, First author: 2)
Ongoing Works (Total: 3, First author: 2)
Choi, J. & Kim, D. K. (2026). Vehicle trajectory reconstruction using quantum-inspired model
Choi, J. & Kim, D. K. (2026). Vehicle trajectory reconstruction with congestion propagation detection using fixed and mobile sensor data (Under review) [Preprint Link]
Choi, S., Choi, J., Kim, D. K., & Yun, H. (2026). A two-stage framework for anomaly detection and classification in loop detector data. (Under review)
International Conferences (Total: 9, First author: 6)
International Conferences (Total: 9, First author: 6)
Choi, J. & Kim, D. K. (2026). Vehicle Trajectory Reconstruction with Congestion Propagation Detection Using Fixed and Mobile Sensor Data. Transportation Research Board 105th Annual Meeting (TRBAM), January 11-15, Washington D.C., U.S.
Kim, B. Y., Choi, J. & Kim, D. K. (2026). Enhancing Platoon Maintenance Stability through Packet Loss Response Strategies. Transportation Research Board 105th Annual Meeting (TRBAM), January 11-15, Washington D.C., U.S.
Choi, J. & Kim, D. K. (2025). Vehicle Trajectory Reconstruction with Estimation of Shockwave Speed Using Traffic Sensor and Probe Vehicle Data. 2025 IEEE International Conference on Intelligent Transportation Systems, November 18-21, Gold Coast, Australia.
Choi, J., Kim, B. Y., Choi, S., & Kim, D. K. (2025).Assessing the Post-Event Congestion Mitigation in a 24-Hour Traffic Scenario Using Simulation of Urban Mobility (SUMO). 20th ITS Asia-Pacific Forum (ITSAPF), May 28-30, Suwon, South Korea.
Choi, S., Choi, J., & Kim, D. K. (2025).Transformer Based Anomaly Detection for Traffic Sensor Malfunctions. 20th ITS Asia-Pacific Forum (ITSAPF), May 28-30, 2025, Suwon, South Korea.
Kim, B. Y., Joo, Y. J., Choi, J. & Kim, D. K. (2024). Queue Length-based Priority Strategy for Multi-lane Unsignalized Intersection under Mixed Traffic Environment. Transportation Research Board 103rd Annual Meeting (TRBAM), January 7-11, Washington D.C., U.S.
Choi, J., Joo, Y. J., & Kim, D. K. (2024). Effects of Heterogeneity in Driving Maneuvers at a Roundabout on Parameter Calibration in Car-Following Models. Transportation Research Board 103rd Annual Meeting (TRBAM), January 7-11, Washington D.C., U.S.
Choi, J. & Kim, D.K. (2023). Calibration and Validation of the Rule-based Human Driver Model for Roundabout Car-following Behaviors Using Naturalistic Driving Data. 15th International Conference of Eastern Asia Society for Transportation Studies (EASTS), September 4-7, Shah Alam, Malaysia.
Choi, J., Joo, Y., & Kim, D. K. (2023). Anomaly Detection with Classifying Sensor Faults in Urban Traffic Based on a Long-Short Term Memory Auto-Encoder Considering Data Resolution. Transportation Research Board 102nd Annual Meeting (TRBAM), January 8-12, Washington D.C., U.S.
Domestic Journal (in Korean) (Total: 2, First author: 2)
Domestic Journal (in Korean) (Total: 2, First author: 2)
Referee Works for Journal / Conference
Referee Works for Journal / Conference
International Journal of Urban Sciences (SCIE)
Journal of Transportation Engineering Part A: Systems (SCIE)
Asian Transport Studies (ESCI)
The IEEE International Conference on Intelligent Transportation Systems (2025, 2026)
Transportation Research Board (TRB) Annual Meeting (2026)
The IEEE Intelligent Vehicle Symposium (2026)
Domestic Conferences (Total: 19, First author: 11)
Domestic Conferences (Total: 19, First author: 11)
Choi, S., Choi, J., Yun, H. & Kim, D. K. (2026). Detecting Non-Recurring Congestion on Freeways Using the Fundamental Diagram. Proceedings of the KOR-KST Conference.
Choi, J. & Kim, D. K. (2026). A Framework for Vehicle Trajectory Reconstruction Using Quantum-Inspired Model. Proceedings of the KOR-KST Conference.
Choi, S., Choi, J., Yun, H. & Kim, D. K. (2025). Data-driven Incident Detection in High Dimensional Latent Space for Unremarkable Traffic Event. The 2025 Korean Institute of ITS Fall Conference.
Choi, J. & Kim, D. K. (2025). Emission Estimation with Vehicle Trajectory Reconstruction Using Traffic Sensor and Probe Vehicle Data. Proceedings of the KOR-KST Conference.
Choi, S., Choi, J., Yun, H. & Kim, D. K. (2025). Real-Time Detection of Anomalies in Traffic Sensors with an Encoder-Decoder Architecture. Proceedings of the KOR-KST Conference.
Kim, B.Y., Choi, J., & Kim, D. K. (2025). Enhancing Platoon Maintenance Stability Considering Communication Loss. Proceedings of the KOR-KST Conferencee.
Chae, J., Choi, J., & Kim, D. K. (2025). A Reactive Rerouting Strategy for Mitigating Non-recurrent Congestion in Mixed Traffic Environment. Proceedings of the KOR-KST Conference.
Choi, S., Choi, J., Yun, H. & Kim, D. K. (2025). Variational Autoencoder based Detection and Reconstruction of Traffic Sensor Malfunctions. The 2025 Korean Institute of ITS Spring Conference.
Choi, J. & Kim, D. K. (2025). Data-Fusion based Estimation of Congestion Propagation for Vehicle Trajectory Reconstruction. The 2025 Korean Institute of ITS Spring Conference.
Choi, S., Choi, J., Moon, S., & Kim, D. K. (2024). Effects of Inter-Driver Heterogeneity on Car-Following Behavior Considering Intra-Driver Heterogeneity. The 2024 Korean Institute of ITS Fall Conference, 521-526.
Choi, J. & Kim, D. K. (2024). Payne-Whitham Model-based Reconstructing Vehicle Trajectory Using Data-Fusion of Traffic Detector and Probe Vehicles. The 2024 Korean Institute of ITS Fall Conference, 225-230.
Choi, S., Choi, J., Moon, S., & Kim, D. K. (2024). Risk Assessment for Left-Turn Vehicles in the Dilemma Zone at Signalized Intersections. The 2024 Korean Institute of ITS Spring Conference, 687-692.
Choi, J. & Kim, D. K. (2024). Modeling the Life of Bike Sharing System Using Survival Analysis. The 2024 Korean Institute of ITS Spring Conference, 540-550.
Choi, J., Joo, Y. J., & Kim, D. K. (2023). Modeling the Maneuvers on the Roundabout for Microscopic Simulation Considering Driving Segments. The 2023 Korean Institute of ITS Fall Conference, 951-959.
Choi, J. & Kim, D. K. (2023). Roundabout Car-following Parameter Estimation Considering Surrogate Safety Measure Validation in Simulation. The 2022 Korean Institute of ITS Spring Conference, 393-399.
Choi, J. & Kim, D. K. (2022). A Spatio-temporal Factor Analysis of Round-trip Pattern in Station-based Bike Sharing. The 2022 Korean Institute of ITS Fall Conference, 154-160.
Choi, J., Joo, Y., & Kim, D. K. (2022). A Study on Data Types and Resolution for Anomaly Detection in the Urban Road Network. The Korean Institute of ITS International Conference, 597-603.
Choi, J., Song, J., Kang, M., & Hwang, K. Y. (2021). A Clustering Analysis on the Machine Learning-Based Bus Routes Types and Bus Stations for Adoption of Demand Responsive Transport. Proceedings of the KOR-KST Conference, 481-482.
Choi, J., Kang, M., Song, J., & Hwang, K. Y. (2021). The Prediction of Motorcycle Accident Severity on the Spatial Grids Based on DNN. The 2021 Korean Institute of ITS Fall Conference, 349-354.
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