Development of Fault Detection and Emergency Control for Application to Autonomous Vehicle Seoul National University

Format:

Book

Conference/Event

Author/Creator:

Jong Min, Lee, author.

Contributor:

Oh, Kwang Seok

Song, Taejun

Conference Name:

SAE WCX Digital Summit (2021-04-13 : Live Online, Pennsylvania, United States)

Language:

English

Physical Description:

1 online resource cm

Place of Publication:

Warrendale, PA SAE International 2021

Summary:

This paper describes a failsafe system of automated driving vehicles. The failsafe system consists of the following two parts: sliding mode observer-based environment sensor, chassis sensor fault detection, and emergency deceleration control. Two sliding mode observers are designed to reconstruct the fault of acceleration and environment sensor(Lidar) in a longitudinal direction. In the environment sensor's fault detection part, the longitudinal vehicle model receives clearance and relative velocity values. Therefore, failure diagnosis is possible regardless of environmental sensors, such as radar, lidar, and camera. This paper's sensor data is the failure of Delphi's Electronically Scanning Radar (ESR) and Ibeo's LUX Lidar installed in an autonomous vehicle. The emergency deceleration control algorithm employs the sliding mode control with adaptive convergence time. In the event of a failure, it is significant to control the vehicle within a short period safely. The Adaptive convergence time concept proves a mathematical convergence of the vehicle control time after a failure occurs. As soon as the error occurred, the error was proved to always converge to zero within the final time. Thus, the proposed method introduces the concept of convergence time, and mathematically demonstrates that the state reached the reference target within the specified time when a failure occurred. In the emergency control part, two processing unit hardware structures are adopted to comply with SAE International standard J3016 and NHTSA autonomous vehicle safety report standards. The proposed fail-safe detection algorithm is evaluated through vehicle test data, and the fail-safe control algorithm evaluates through computer simulation and vehicle tests

Notes:

Vendor supplied data

Publisher Number:

2021-01-0075

Access Restriction:

Restricted for use by site license