Human-driven vehicles (HDVs) and automated vehicles (AVs) of all levels (Level 1-5, AVs1-5) may share the highways in the long and foreseeable future. The increasing vehicle autonomy heterogeneity and diversity may jeopardize the safe and harmonious interaction among such vehicles with mixed autonomy on highways and pose a threat to the safety of all vehicles. This may exacerbate an already growing and alarming national concern on traffic safety. This project aims to advance the state of the art in the Cyber-Physical Systems (CPS) research areas of Autonomy, Safety, and Transportation by ushering in a new CPS paradigm of harmonious and safe integration of highway vehicles with heterogeneous, varying, and mixed human / machine autonomy. Through collaborative research, the project may create new methods and tools to enhance the highway driving safety of heterogeneous vehicles. The outcomes of this work may also be extended to advance other CPS in manufacturing, warehousing, and healthcare applications where interaction among humans and heterogeneous autonomous robots is pervasive and safe coordination among them is critical.
The project seeks to address the emerging challenges associated with vehicles of heterogeneous autonomy in highway transportation by creating a universal framework that can augment AVs1-5 systems to enable safe and harmonious integration of vehicles in highway traffic. The research team will use an interdisciplinary research approach to understand driving behaviors and assess individual perceived safety of other HDVs and AVs1-5, as well as to achieve cooperative, decentralized behavioral coordination and verifiably safe control in highway traffic scenarios. Human-in-the-loop driving simulation experiments and scaled vehicle-traffic system experiments will be conducted to investigate and evaluate the developed methods. Educational activities such as curriculum development and graduate/undergraduate student research participation will be conducted. Research dissemination and K-12 outreach activities will also be pursued to further increase the broader impact of the research.
Abstract
Performance Period: 07/01/2023 - 06/30/2026
Institution: University of Texas at Austin
Sponsor: National Science Foundation
Award Number: 2312466