Title
A Risk-Aware Architecture for Autonomous Vehicle Operation Under Uncertainty
Abstract
A significant barrier to deploying autonomous vehicles (AVs) on a massive scale is safety assurance. Several technical challenges arise due to the uncertain environment in which AVs operate, such as road and weather conditions, errors in perception and sensory data, and model inaccuracy. This paper proposes a system architecture for risk-aware AVs capable of reasoning about uncertainty and deliberately bounding collision risk below a given threshold. The system comprises of three main subsystems. First, a perception subsystem that detects objects within a scene and quantifies the uncertainty arising from different sensing and communication modalities. Second, an intention recognition subsystem that predicts the driving-style and the intention of agent vehicles and pedestrians. Third, a planning subsystem that takes into account the aggregate uncertainty, from perception, intention recognition, and tracking error, and outputs control policies that explicitly bound the probability of collision. We deliberate further on the planner and show, in simulation, that tuning a risk parameter can significantly alter driving behavior. We believe that such a white-box approach is crucial for safe and explainable autonomous driving and the public adoption of AVs.
Year
DOI
Venue
2020
10.1109/SSRR50563.2020.9292629
2020 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR)
Keywords
DocType
ISSN
uncertain environment,weather conditions,sensory data,white-box approach,driving behavior,collision probability,tracking error,sensing modalities,object detection,safety assurance,autonomous vehicle operation,risk-aware architecture,autonomous driving,safe driving,risk parameter,aggregate uncertainty,planning subsystem,pedestrians,agent vehicles,driving-style,intention recognition subsystem,communication modalities,perception subsystem,collision risk,risk-aware AVs,system architecture
Conference
2374-3247
ISBN
Citations 
PageRank 
978-1-6654-0391-7
0
0.34
References 
Authors
12
5
Name
Order
Citations
PageRank
Majid Khonji100.34
Jorge Dias217533.83
Rashid Alyassi301.01
Fahad Almaskari400.34
Lakmal D. Seneviratne557770.91