Exhibit D - Research Project Requirement: PDF Link

Project Outcome Brief: PDF Link

Final Report: TBD

Project Summary: The potential of CAVs to revolutionize transportation is undeniable. However, unlocking this potential requires addressing the unique challenges rural roads pose. Rigorous testing and innovative solutions are key to enhancing CAV safety in these challenging environments. The proposed project will provide safe mobility and accessibility to populations in rural road areas. Given the operational challenges of CAVs in such settings, the project will 1) develop a conceptual framework by synthesizing the literature on CAV algorithms, 2) develop a CAV testing plan in rural settings utilizing a unique CAV-in-the-loop simulation setup, 3) engage in software development for simulation using CARLA and OpenPilot software, and 4) analyze the results and provide innovative solutions to address challenges, such as adverse weather conditions, complex terrain, hazard classification, and limited sensor range, to improve CAV performance on rural roads. 

Joseph William Beck, Advancing Safety Validation \& Testing of Autonomous Vehicles Using Advanced Simulation Techniques, PhD Dissertation, University of Tennessee

Joe Beck, Shean Huff, Subhadeep Chakraborty, "Diagnosing and Predicting Autonomous Vehicle Operational Safety Using Multiple Simulation Modalities and a Virtual Environment, under review.

Joe Beck, Subhadeep Chakraborty, “Modeling and Propagation of Perception Errors in Autonomous Vehicle Control: A Generative Time-Series Framework for Safety-Critical Evaluation”, under preparation for submission

H. -J. Yang et al., "GENESIS-RL: GEnerating Natural Edge-cases with Systematic Integration of Safety considerations and Reinforcement Learning," 2024 IEEE International Automated Vehicle Validation Conference (IAVVC), Pittsburgh, PA, USA, 2024, pp. 1-8, doi: 10.1109/IAVVC63304.2024.10786471.

Adeel, M., A. Khattak, M. Ashfaq, & Z. Aslam, Understanding the Link Between Weather and Crash Risk: Learning from Modeling of a Unique Crash Database,  Submitted for presentation to the Transportation Research Board, National Academies, 2025.

Adeel, M., A. Khattak, S. Usman, & N. Moradloo, Are we ready for highly automated vehicles? Evaluating automated driving systems’ safety and reliability using inverse probability weighted regression adjustment. Under Review in the Journal of Intelligent Transportation Systems, 2025.