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Jiwon Kim
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Cited by
Cited by
Year
Spatial and temporal characterization of travel patterns in a traffic network using vehicle trajectories
J Kim, HS Mahmassani
Transportation Research Part C: Emerging Technologies 59, 375-390, 2015
1922015
Correlated parameters in driving behavior models: Car-following example and implications for traffic microsimulation
J Kim, HS Mahmassani
Transportation research record 2249 (1), 62-77, 2011
1312011
Characterising Green Light Optimal Speed Advisory trajectories for platoon-based optimisation
S Stebbins, M Hickman, J Kim, HL Vu
Transportation Research Part C: Emerging Technologies 82, 43-62, 2017
1082017
Calibration of traffic flow models under adverse weather and application in mesoscopic network simulation
T Hou, HS Mahmassani, RM Alfelor, J Kim, M Saberi
Transportation Research Record 2391 (1), 92-104, 2013
882013
Identification of communities in urban mobility networks using multi-layer graphs of network traffic
M Yildirimoglu, J Kim
Transportation Research Part C: Emerging Technologies 89, 254-267, 2018
832018
Route choice stickiness of public transport passengers: Measuring habitual bus ridership behaviour using smart card data
J Kim, J Corcoran, M Papamanolis
Transportation Research Part C: Emerging Technologies 83, 146-164, 2017
832017
Compound Gamma representation for modeling travel time variability in a traffic network
J Kim, HS Mahmassani
Transportation Research Part B: Methodological 80, 40-63, 2015
78*2015
TrajGAIL: Generating urban vehicle trajectories using generative adversarial imitation learning
S Choi, J Kim, H Yeo
Transportation Research Part C: Emerging Technologies 128, 103091, 2021
742021
Likelihood and duration of flow breakdown: modeling the effect of weather
J Kim, HS Mahmassani, J Dong
Transportation Research Record 2188 (1), 19-28, 2010
722010
Incorporating weather impacts in traffic estimation and prediction systems
HS Mahmassani, J Dong, J Kim, RB Chen, B Park
US Department of Transport, Washington 108, 2009
712009
Assessing traffic disturbance, efficiency, and safety of the mixed traffic flow of connected vehicles and traditional vehicles by considering human factors
A Sharma, Z Zheng, J Kim, A Bhaskar, MM Haque
Transportation Research Part C: Emerging Technologies 124, 102934, 2021
642021
Joint prediction of next location and travel time from urban vehicle trajectories using long short-term memory neural networks
J Sun, J Kim
Transportation Research Part C: Emerging Technologies 128, 103114, 2021
522021
Diagnosis and Prediction of Traffic Congestion on Urban Road Networks Using Bayesian Networks
J Kim, G Wang
Transportation Research Record: Journal of the Transportation Research Board …, 2016
492016
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 …
A Sharma, Z Zheng, J Kim, A Bhaskar, MM Haque
Analytic methods in accident research 27, 100127, 2020
482020
Attention-based Recurrent Neural Network for Urban Vehicle Trajectory Prediction
S Choi, J Kim, H Yeo
Procedia Computer Science 151, 327-334, 2019
482019
A finite mixture model of vehicle-to-vehicle and day-to-day variability of traffic network travel times
J Kim, HS Mahmassani
Transportation Research Part C: Emerging Technologies 46, 83-97, 2014
462014
Network-Wide Vehicle Trajectory Prediction in Urban Traffic Networks Using Deep Learning
S Choi, H Yeo, J Kim
Transportation Research Record 2672 (45), 173-184, 2018
452018
Estimating and comparing response times in traditional and connected environments
A Sharma, Z Zheng, J Kim, A Bhaskar, MM Haque
Transportation Research Record 2673 (4), 674-684, 2019
432019
Scenario-based approach to analysis of travel time reliability with traffic simulation models
J Kim, HS Mahmassani, P Vovsha, Y Stogios, J Dong
Transportation Research Record 2391 (1), 56-68, 2013
422013
Forecasting Pedestrian Movements Using Recurrent Neural Networks: An Application of Crowd Monitoring Data
DC Duives, G Wang, J Kim
Sensors 19 (2), 382, 2019
382019
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Articles 1–20