Kun-Feng Wu, Ph.D.
Affiliations: | 2011 | Pennsylvania State University, State College, PA, United States |
Area:
Civil EngineeringGoogle:
"Kun-Feng Wu"Parents
Sign in to add mentorPaul P. Jovanis | grad student | 2011 | Penn State | |
(Defining, screening, and testing crash surrogates using naturalistic driving data.) |
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Publications
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Wu KK, Lin T. (2022) Investigating the effects of travel lane configuration and lane width on traffic safety where powered-two-wheelers (PTWs) share with larger vehicles: A micro perspective. Accident; Analysis and Prevention. 172: 106682 |
Wu KK, Wang L. (2020) Exploring the combined effects of driving situations on freeway rear-end crash risk using naturalistic driving study data. Accident; Analysis and Prevention. 150: 105866 |
Wu KF, Lin YJ. (2019) Exploring the effects of critical driving situations on driver perception time (PT) using SHRP2 naturalistic driving study data. Accident; Analysis and Prevention. 128: 94-102 |
Huang K, Wu K, Ardiansyah MN. (2019) A stochastic dairy transportation problem considering collection and delivery phases Transportation Research Part E: Logistics and Transportation Review. 129: 325-338 |
Wang SY, Wu KF. (2018) Reducing intercity bus crashes through driver rescheduling. Accident; Analysis and Prevention. 122: 25-35 |
Wu KF, Sasidharan L, Thor CP, et al. (2018) Crash sequence based risk matrix for motorcycle crashes. Accident; Analysis and Prevention. 117: 21-31 |
Wu KF, Ardiansyah N, Ye WJ. (2017) An Evaluation Scheme for Assessing the Effectiveness of Intersection Movement Assist (IMA) on Improving Traffic Safety. Traffic Injury Prevention. 0 |
Wu KF, Thor CP, Ardiansyah MN. (2016) Identify sequence of events likely to result in severe crash outcomes. Accident; Analysis and Prevention. 96: 198-207 |
Wu K, Jovanis PP. (2016) Cohort-Based Analysis Structure for Modeling Driver Behavior with an In-Vehicle Data Recorder Transportation Research Record: Journal of the Transportation Research Board. 2601: 24-32 |
Sasidharan L, Wu KF, Menendez M. (2015) Exploring the application of latent class cluster analysis for investigating pedestrian crash injury severities in Switzerland. Accident; Analysis and Prevention. 85: 219-28 |