Assuring safety of perception and decision making in automated driving
Self-driving vehicle prototypes have shown impressive progress in ongoing pilots, with many of their critical tasks relying on machine learning (ML). Yet, assuring the safety of autonomous vehicles remains an open problem, preventing their deployment.
In this talk, I will first briefly review current automated driving system designs, the fundamental limitations that affect their safety, and the emerging industry standards for assuring automated driving. I will then present on-going research to address the remaining gaps in assuring driving behavior and ML-based perception. For driving behavior, I will consider assuring reactive safety based on physics and driving rules, and proactive safety based on modeling human road-user behavior using game theoretic models. For perception assurance, I will present an uncertainty-centric approach that entails estimating, controlling, and mitigating perceptual uncertainty, and robustifying decision making to the estimated uncertainty. I will close with open problems and future research directions.
About the Speaker:
Krzysztof Czarnecki is a Professor of Electrical and Computer Engineering at the University of Waterloo, where he heads the Waterloo Intelligent Systems Engineering (WISE) Laboratory. He is a leading expert in the safety of automated driving systems (ADS), with focus on assuring the safety of driving behavior and machine-learned functions. As part of his research, he has co-lead the development of UW Moose (started in 2016), Canada’s first self-driving research vehicle, which has been tested on public roads since 2018 (autonomoose.net). His recent research contributions related to ADS safety assurance include an uncertainty-centric framework for assuring the safety of perceptual components based on machine learning, a framework for specifying driving behavior requirements, and methods for modeling and sampling road user behavior. He serves on SAE task forces on driving automation definitions, reference architecture, verification and validation, and maneuvers and behaviors, the Canadian Mirror Committee of ISO TC 22/SC 32 (contribution to ISO/PAS 21448 Safety of the Intended Functionality), and the UL STP 4600 Evaluation of Autonomous Products standards committee. Before working on automated driving, he advised Pratt and Whitney Canada on creating reusable software designs and components for aircraft engine control systems (2011-2015). Before coming to Waterloo, he was a researcher at DaimlerChrysler Research (1995-2002), Germany, focusing on improving software development practices and technologies in enterprise, automotive, and aerospace sectors. He co-authored the book on "Generative Programming" (Addison- Wesley, 2000), which pioneered automated software engineering based on feature modeling, domain-specific languages, and program generation. While at Waterloo, he held the NSERC/Bank of Nova Scotia Industrial Research Chair in Requirements Engineering of Service-oriented Software Systems (2008-2013) and worked on methods and tools for engineering complex software-intensive systems. He received the Premier's Research Excellence Award in 2004 and the British Computing Society in Upper Canada Award for Outstanding Contributions to IT Industry in 2008. He has also received seven Best Paper Awards, two ACM Distinguished Paper Awards, and two Most Influential Paper Awards. His publications have been widely cited (over 25,000 citations on Google Scholar).
Host: Matt Dwyer