Year |
Citation |
Score |
2020 |
Sharma A, Zheng Z, Kim J, Bhaskar A, Haque MM. 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. DOI: 10.1016/J.Amar.2020.100127 |
0.332 |
|
2020 |
Faroqi H, Mesbah M, Kim J. Modelling socioeconomic attributes of public transit passengers Journal of Geographical Systems. 22: 519-543. DOI: 10.1007/S10109-020-00328-0 |
0.338 |
|
2019 |
Duives DC, Wang G, Kim J. Forecasting Pedestrian Movements Using Recurrent Neural Networks: An Application of Crowd Monitoring Data. Sensors (Basel, Switzerland). 19. PMID 30669293 DOI: 10.3390/S19020382 |
0.336 |
|
2019 |
Sharma A, Zheng Z, Kim J, Bhaskar A, Haque MM. Estimating and Comparing Response Times in Traditional and Connected Environments Transportation Research Record: Journal of the Transportation Research Board. 2673: 674-684. DOI: 10.1177/0361198119837964 |
0.396 |
|
2019 |
Faroqi H, Mesbah M, Kim J. Behavioural advertising in the public transit network Research in Transportation Business and Management. 32: 100421. DOI: 10.1016/J.Rtbm.2019.100421 |
0.354 |
|
2019 |
Choi S, Kim J, Yeo H. Attention-based Recurrent Neural Network for Urban Vehicle Trajectory Prediction Procedia Computer Science. 151: 327-334. DOI: 10.1016/J.Procs.2019.04.046 |
0.375 |
|
2018 |
Faroqi H, Mesbah M, Kim J. Applications of transit smart cards beyond a fare collection tool: a literature review Advances in Transportation Studies. 45: 107-122. DOI: 10.4399/978255166098 |
0.325 |
|
2018 |
Choi S, Yeo H, Kim J. Network-Wide Vehicle Trajectory Prediction in Urban Traffic Networks using Deep Learning Transportation Research Record: Journal of the Transportation Research Board. 2672: 173-184. DOI: 10.1177/0361198118794735 |
0.307 |
|
2018 |
Li L, Kim J, Xu J, Zhou X. Time-dependent route scheduling on road networks Sigspatial Special. 10: 10-14. DOI: 10.1145/3231541.3231545 |
0.35 |
|
2018 |
Faroqi H, Mesbah M, Kim J, Tavassoli A. 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 |
0.301 |
|
2017 |
Kim J, Corcoran J, Papamanolis M. Route choice stickiness of public transport passengers: Measuring habitual bus ridership behaviour using smart card data Transportation Research Part C: Emerging Technologies. 83: 146-164. DOI: 10.1016/J.Trc.2017.08.005 |
0.318 |
|
2017 |
Stebbins S, Hickman M, Kim J, Vu HL. 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 |
0.337 |
|
2016 |
Kim J, Wang G. Diagnosis and Prediction of Traffic Congestion on Urban Road Networks Using Bayesian Networks Transportation Research Record: Journal of the Transportation Research Board. 2595: 108-118. DOI: 10.3141/2595-12 |
0.389 |
|
2015 |
Chen Y, Mahmassani HS, Hong Z, Hou T, Kim J, Halat H, Alfelor RM. Online Implementation and Evaluation of Weather-Responsive Coordinated Signal Timing Operations Transportation Research Record: Journal of the Transportation Research Board. 2488: 71-86. DOI: 10.3141/2488-08 |
0.636 |
|
2015 |
Ahn S, Kim J, Dunston PS, Kandil A, Martinez JC. Characterizing Travel Time Distributions in Earthmoving Operations Using GPS Data Computing in Civil Engineering. 288-295. DOI: 10.1061/9780784479247.036 |
0.392 |
|
2015 |
Kim J, Mahmassani HS. Spatial and temporal characterization of travel patterns in a traffic network using vehicle trajectories Transportation Research Procedia. 9: 164-184. DOI: 10.1016/J.Trpro.2015.07.010 |
0.525 |
|
2015 |
Kim J, Mahmassani HS. 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 |
0.564 |
|
2014 |
Kim J, Mahmassani HS. How many runs? Analytical method for optimal scenario sampling to estimate travel time variance in traffic networks Transportation Research Record. 2467: 49-61. DOI: 10.3141/2467-06 |
0.556 |
|
2014 |
Kim J, Mahmassani HS. 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 |
0.551 |
|
2013 |
Kim J, Mahmassani H, Alfelor R, Chen Y, Hou T, Jiang L, Saberi M, Verbas O, Zockaie A. Implementation and evaluation of weather-responsive traffic management strategies Transportation Research Record. 93-106. DOI: 10.3141/2396-11 |
0.699 |
|
2013 |
Hou T, Mahmassani H, Alfelor R, Kim J, Saberi M. Calibration of traffic flow models under adverse weather and application in mesoscopic network simulation Transportation Research Record. 92-104. DOI: 10.3141/2391-09 |
0.735 |
|
2013 |
Kim J, Mahmassani HS, Vovsha P, Stogios Y, Dong J. Scenario-Based Approach to Analysis of Travel Time Reliability with Traffic Simulation Models Transportation Research Record: Journal of the Transportation Research Board. 2391: 56-68. DOI: 10.3141/2391-06 |
0.646 |
|
2011 |
Kim J, Mahmassani HS. Correlated parameters in driving behavior models: Car-following example and implications for traffic microsimulation Transportation Research Record. 62-77. DOI: 10.3141/2249-09 |
0.52 |
|
2010 |
Kim J, Mahmassani HS, Dong J. Likelihood and duration of flow breakdown: Modeling the effect of weather Transportation Research Record. 19-28. DOI: 10.3141/2188-03 |
0.563 |
|
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