Fac/Staff profile

Shan Bao, Ph.D.

Shan
Bao
Ph.D.

Associate professor, Industrial and Manufacturing Systems Engineering

Education

Ph.D. Industrial Engineering (Human Factors focus), University of Iowa, 2009

B.E. Mechanical Engineering, Hefei University of Technology, China, 2000

204 CIS
4901 Evergreen Rd
Dearborn, MI 48128
313-583-6626

About

Bio

Dr. Bao is an Associate Professor in the Industrial and Manufacturing Systems Engineering Department, University of Michigan-Dearborn. She also has a joint appointment as Associate Research Scientist at the University of Michigan Transportation Research Institute’s Human Factors Group. She received her Ph.D. in mechanical and industrial engineering from the University of Iowa in 2009. Her research interests focus on human factors issues related to connected and automated vehicle technologies, ADAS system evaluation, and big data analysis.  She has served as the PI (with a total funding of 3.4 million dollars) or co-PI (with a total funding of more than 13 million dollars) of 43 research projects. She has published 54 technical publications, including 28 referred journals articles. Shan has served as the chair of the Surface Transportation Technical Group of Human Factors and Ergonomics Society. She is a member of the TRB Vehicle User Characteristics committee and the TRB Human Factors in Road Vehicle Automation subcommittee. 

Research Areas:

  • Driver distraction state detection and prediction
  • Training and education to improve user understanding of automated vehicle technologies
  • Communication and interaction between vehicle and vulnerable road users
  • Seat belt use behavior and the effectiveness of seat belt interlock systems
  • Driving style classification
  • Human factors issues associated with connected and automated vehicle technologies

 

Selected Publications

Fred Feng, Bao, S, Robert C Hampshire, Michael Delp (2018). Drivers overtaking bicyclists—An examination using naturalistic driving data, Accident Analysis & Prevention (115), 98-109.

Zhaojian Li, Bao, S, Ilya V. Kolmanovsky, Xiang Yin (2017). Visual Distraction Detection Using Driving Performance Indicators with Naturalistic Driving Data. IEEE Transactions on Intelligent Transportation Systems, PP(99):1-8.

Yuan Wang, Bao, S,Wenjun Du, Zhirui Ye, James R. Sayer (2017). Examining drivers’ eye glance patterns during distracted driving: Insights from scanning randomness and glance transition matrix. The Journal of Safety Research, 63:149-155.

Fred Feng, Bao, S, Jim Sayer, Carol Flannagan, Mike Manser and Robert Wunderlich (2017). Can vehicle jerk associated with gas pedal operation be used to identify aggressive drivers? An examination using naturalistic driving data, Accident Analysis & Prevention, 104:125-136.

Yuan Wang, Bao, S,Wenjun Du, Zhirui Ye, James R. Sayer (2017). A spectral power analysis of driving behavior changes during the transition from non-distraction to distraction. Traffic Injury Prevention, 18(8):826-831.

Jessica S. Jermakian, Bao, S, Mary Lynn Buonarosa, and James Sayer (2017). Effects of an integrated collision warning system on teenage driver behavior. The journal of safety research, 61, 65-75.

Scott E Bogard, Bao, S, David LeBlanc, Jun Li, Shaobo Qiu, and Bin Liu (2017). Positions of Antenna of DSRC devices and its Impact on Message Packet Drop Rates and Intra-packet Loss. SAE International Journal of Passenger Cars-Electronic and Electrical Systems, 10 (1):2017.

Zhao, Ding., Lam, Henry., Peng, Huei., Bao, S., Leblanc, David., Nobukawa, Kazutoshi., and Pan, Christopher (2017). Accelerated Evaluation of Automated Vehicles Safety in Lane Change Scenarios Based on Importance Sampling Techniques. IEEE Transactions on Intelligent Transportation Systems, 18(3), 595-609.

Ruifeng Zhang, Libo Cao, Bao, S and Jianjie Tan (2016). A method for connected vehicle trajectory prediction and collision warning algorithm based on V2V communication. International Journal of Crashworthiness.

Kazutoshi Nobukawa, Bao, S, David J. LeBlanc, Ding Zhao, Huei Peng, and Christopher S.Pan (2016). An Image-Based Analysis of Gap Acceptance Behavior of Heavy Truck Drivers on Lane Changes. IEEE transactions on Intelligent Transportation Systems, 17(3), 772-781.

 

Teaching Areas:

History

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