FHWA has a vision of working towards zero deaths with revitalizing adaptation of the Safe System Approach (SSA), which addresses five inter-related elements including safe road users, safe vehicles, safe roads, safe speeds and post-crash care. The market penetration of Advanced Driver-Assistance System (ADAS) technologies installed in vehicles is expected growing rapidly from $27 billion in 2020 to 83 billion by 2030, which is an impressive 12% annual growth rate due to a result of the statistical evidence that ADAS features have capability to compensate for potential crashes caused by human errors, change driving behavior and reduce crash severity.
Scientific quantification and assessment of safety impacts of ADAS technologies to geometric design and future HSM prediction models are key for a successful implementation and short- and long-term direction of SSA in the Connected and Automated Vehicle (CAV) era. The selected National Research Council (NRC) research associate shall mainly perform a research focused on identifying the possible limitation of existing crash prediction models (Highway Safety Manual Part C & D) that do not reflect the influence of vehicle equipped ADAS features, and develop new prediction models and/or applications that reflect these impacts or changes through advanced data collection, conflation and analysis efforts. In addition, the selected NRC associate will participate in providing an in-depth and advanced analytical support on various research topics with the Geometric Design Laboratory (GDL) to assist on-going or planned Data-Driven Safety Analysis (DDSA) related activities, but not limited to, such as:
- Expand/Enhance Performance-Based Geometric Design and Practical Application of HSM and IHSDM
- Develop Second Strategic Highway Research Program (SHRP2) Data-Driven Analysis through Combining Various Safety Data Resources (e.g., HSIS, HPMS/ARNOLD, RITIS/NPMRDS etc.)
- Speed Management for Safety
- Integration of Safety and Operation Research
- Develop a Strategy CAV Consideration for Future Editions of Highway Safety Manual (HSM), Green Book and Manual of Uniform Traffic Control Devices (MUTCD)
- Develop a Strategy Plan to Address the Gaps in the Application of Available Open Data to Advanced Safety Analysis Techniques.
The selected applicant is required to hold a Ph.D. (within 5 years) with innovative ideas and expertise in highway safety, data science, statistical modeling, and data-driven approach. Addtional preferred experience or skillsets of expertise include: 1) HSM Part C & D analysis using statistical programs (e.g., IBM-SPSS, R, Python), 2) programming languages (e.g., SQL, Python, R, Java), 3) collecting data with Application Program Interface (API), 4) GIS-based data Analysis and visualization, 5) HSIS, HPMS, SHRP2 (RID and NDS), and RITIS/NPMRDS data analysis.
Highway Safety, HSM, Statistical Analysis, Big Data, API, Programming Languages, GIS