Title
Towards Guaranteed Safety Assurance of Automated Driving Systems With Scenario Sampling: An Invariant Set Perspective
Abstract
How many scenarios are sufficient to validate the safe Operational Design Domain (ODD) of an Automated Driving System (ADS) equipped vehicle? Is a more significant number of sampled scenarios guaranteeing a more accurate safety assessment of the ADS? Despite the various empirical success of ADS safety evaluation with scenario sampling in practice, some of the fundamental properties are largely unknown. This paper seeks to remedy this gap by formulating and tackling the scenario sampling safety assurance problem from a set invariance perspective. First, a novel conceptual equivalence is drawn between the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">scenario sampling safety assurance problem</i> and the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">data-driven robustly controlled forward invariant set validation and quantification problem</i> . This paper then provides a series of complete solutions with finite-sampling analyses for the safety validation problem that authenticates a given ODD. On the other hand, the quantification problem escalates the validation challenge and starts looking for a safe sub-domain of a particular property. This inspires various algorithms that are provably probabilistic incomplete, probabilistic complete but sub-optimal, and asymptotically optimal. Finally, the proposed asymptotically optimal scenario sampling safety quantification algorithm is also empirically demonstrated through simulation experiments.
Year
DOI
Venue
2022
10.1109/TIV.2021.3117049
IEEE Transactions on Intelligent Vehicles
Keywords
DocType
Volume
Safety,scenario sampling,invariant set,automated driving system
Journal
7
Issue
ISSN
Citations 
3
2379-8858
0
PageRank 
References 
Authors
0.34
13
4
Name
Order
Citations
PageRank
Bowen Weng100.34
Linda Capito200.34
Ümit Özgüner31014166.59
Keith Redmill410113.99