Drivers overtaking bicyclists - An examination using naturalistic driving data
Link Preprint Forbes BibTex Feng, Bao, Hampshire, and DelpAccident Analysis & Prevention, 115, 98-109. (2018)
Research Areas
- Methods: Observational studies, laboratory experiments, inferential statistics, causal inference, computational modeling & simulation, machine learning, and human factors
- Applications: Cycling safety, pedestrian safety, driver behavior & modeling, and active, sustainable, and equitable transportation
Teaching
- IMSE 317 Engineering Probability and Statistics
- IMSE 440 Applied Statistical Models in Engineering
- IMSE 586 Big Data Analytics and Visualization
Education/Experience
- Postdoctoral Fellow, University of Michigan Transportation Research Institute (UMTRI)
- Ph.D. in Industrial and Operations Engineering, the University of Michigan, Ann Arbor
- M.S./B.E. in Mechanical/Automotive Engineering, Tsinghua University, China
Selected Publications
Accident Analysis & Prevention, 115, 98-109. (2018)
Estimating lead vehicle kinematics using camera-based sensor data for distraction detection
PDF BibTex Feng, Bao, Jin, Sun, Saigusa, Tahmasbi-Sarvestani, and DsaInt'l Journal of Automotive Engineering, 9(3), 158-164. (2018)
Effects of quantity and size of buttons of in-vehicle touch screen on drivers' eye glance behavior
Link PDF BibTex Feng, Liu, and ChenInt'l Journal of Human-Computer Interaction, 34(12), 1105-1118. (2018)
Can vehicle longitudinal jerk be used to identify aggressive drivers? An examination using naturalistic driving data
Link BibTex Feng, Bao, Sayer, Flannagan, Manser, and WunderlichAccident Analysis & Prevention, 104, 125-136. (2017)
A computer-aided usability testing tool for in-vehicle infotainment systems
Link Preprint BibTex Feng, Liu, and ChenComputers & Industrial Engineering, 109, 313-324. (2017)