A Framework for Real-time Autonomous Road Vehicle Emergency Obstacle Avoidance Maneuvers with Validation Protocol

Download or read book A Framework for Real-time Autonomous Road Vehicle Emergency Obstacle Avoidance Maneuvers with Validation Protocol written by Evan Richard Powell Lowe and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: As passenger vehicle technologies have advanced, so have their capabilities to avoid obstacles, especially with developments in tires, suspensions, steering, as well as safety technologies like ABS, ESC, and more recently, ADAS systems; however, environments around passenger vehicles have also become more complex, and dangerous. As autonomous road vehicle (ARV) development aims to address these complex environments, one area that is still new and open is ARV emergency obstacle avoidance at highway speeds (55-165 km/h) and on slippery road surfaces. When introducing obstacle avoidance capabilities into an ARV, it is important to target performance that meets or exceeds that of human drivers. This dissertation highlights subsystems within an entire ARV, which are crucial for the completion of a highly functional emergency obstacle avoidance maneuver (EOAM), and combines them in a novel framework while considering the nuances of traveling at highway speeds and/or slippery road surfaces. The primary subsystems developed and tested in this research include the synthesis of ARV sensing, perception, decision making, control, and actuation. These subsystems are introduced with some novelties to the current state-of-the-art as well as the holistic ARV EOAM Framework, designed to handle highway speeds and slippery surfaces, as a novelty. Lastly, a newly considered testing and validation methodology for ARV EOAM performance and validation is presented. This general obstacle avoidance capability assessment (GOACA) has implications for adoption by national or even global regulation bodies, regarding ARV EOAM safety performance while requiring all the core ARV systems to perform well, and in harmony, to achieve top marks