AI for Human Factors in Highway Safety
Project overview
The Human Factors Laboratory within the FHWA Office of Safety and Operations Research and Development seeks a postdoctoral research associate to explore applications and conduct human-centered research on advanced Artificial Intelligence (AI) and Machine Learning (ML) applications in human factors (HF) as they apply to highway safety. The research will investigate how AI-enabled systems interact with human drivers, bicyclists, pedestrians, and other road users; how AI affects human performance, decision-making, trust, workload, and situational awareness; and how HF principles can be integrated into AI design, deployment, evaluation, and policy to improve road safety.
Background and motivation
While significant progress has been made improving road safety, recent advances in communications, connected vehicle technologies, edge computing, and data analytics have dramatically increased the availability of real-time traffic and behavioral data. Concurrently, AI approaches such as recurrent neural networks (RNNs), reinforcement learning (RL), and generative models offer unprecedented opportunities to transform HF research.
Research goals and priority objectives
The postdoctoral researcher will explore applications and perform original, human-centered AI research that addresses HF challenges in transportation and bridges the gap between AI capabilities and human factors research. Priority objectives (candidate may focus on one or combine several) include:
· Establish the foundation of how AI can be used to facilitate HF research within the Human Factors Laboratory, which includes the Highway Driving Simulator and Virtual Reality Laboratory (Human Factors Laboratory Overview | FHWA).
· Investigate which AI tools have a potential to enhance and become integrated in HF research.
· Make a substantial impact on applied highway research by incorporating AI into the FHWA’s HF tools, workflows, and processes.
· Assess and refine AI models that explicitly represent human behavior dynamics (e.g., gap acceptance, takeover timing, speed limit compliance) to improve highway safety.
· Apply and enhance methods to acquire and synthesize traffic and behavior data with human-relevant labels (e.g., driver intent, conflict precursors, glance distributions, workload proxies).
· Enhance connected/distributed simulation using AI such as incorporating behavioral modeling of human drivers, vulnerable road users, and connected automated vehicles for research.
· Build predictive models that incorporate human behavior and performance to enhance traffic system reliability and safety.
· Integrate cognitive models or human-in-the-loop simulations to capture variability in attention, workload, and trust that affects system responses.
· Develop highway safety-specific, human-centered AI models with explainability to support transparent decision-making and regulatory review.
· Embed HF constraints and domain knowledge (e.g., traffic flow theory, driver control limits) into transportation-domain AI models and optimize them for safety-relevant outcomes.
· Conduct human-subject studies, human-in-the-loop driving simulator experiments, and controlled field pilots to evaluate safety, usability, and acceptance across diverse user groups.
The successful applicant will demonstrate a strong background and knowledge in one of the following research topics and a foundation and strong interest for growth in other topics including Human Factors/Ergonomics, AI models, human-subject research methods, and human-AI interaction design. The selected applicant will work onsite at the Turner-Fairbank Highway Research Center (TFHRC), McLean, Virginia, to collaborate directly with federal researchers and contractor staff with multidisciplinary teams and stakeholders.
Human Factors; Artificial Intelligence; highway safety; transportation; simulation
level
Open to Postdoctoral and Senior applicants
Additional Benefits
relocation
Awardees who reside more than 50 miles from their host laboratory and remain on tenure for at least six months are eligible for paid relocation to within the vicinity of their host laboratory.
health insurance
A group health insurance program is available to awardees and their qualifying dependents in the United States.