Shu Han, Research Associate

Dr. Shu Han is a research associate at VTTI. She holds a Ph.D. degree in Transportation Planning and Management and an M.S. degree in Statistics. She has extensive experience in transportation statistics modeling, safety modeling, driver behavior analysis, and transportation planning. Her primary areas of research include driver behavior risk evaluation, eye-glance behavior assessment, driver impairment study, teen driver behavior study, ADAS efficacy evaluation, truck driver fatigue analysis, highways infrastructure safety evaluation, and arterial roads crash risk analysis. Also, as an experienced data analyst and a certified SAS 9 advance programmer, she has served serval other projects including SHRP2 NDS, Truck NDS, Canada NDS, and Shanghai FOT in which she has processed and analyzed multi-source data with SAS, R, and SQL.

In addition to the traditional statistical models for traffic safety inference and prediction, Dr. Shu Han also explores the application of other methods on driving risk analysis such as Generalized Additive Model, propensity-score based causal inference, Probabilistic Structural Equation Models, and Bayesian Network. These methods incorporate the traditional statistical models and machine learning algorithms, which can better capture the complex and non-linear relationships inherent in driving risk analysis and offer comprehensive solutions for understanding and mitigating the complexities of driving risk.

Contact

• 540-231-1518
• shan@vtti.vt.edu