Connected Dependability Cage Approach for Safe Automated Driving

TL;DR

This paper introduces a safety framework for automated driving that combines onboard and offboard monitoring to ensure continuous operational safety and responsible control transfer, validated through lab and field tests.

Contribution

It proposes a novel connected dependability cage approach integrating onboard and remote monitoring for safer automated driving system operation.

Findings

Effective continuous ODD monitoring demonstrated in lab and field tests

Smooth responsibility transfer between onboard system and remote safety driver

Insights gained on system reliability and safety management

Abstract

Automated driving systems can be helpful in a wide range of societal challenges, e.g., mobility-on-demand and transportation logistics for last-mile delivery, by aiding the vehicle driver or taking over the responsibility for the dynamic driving task partially or completely. Ensuring the safety of automated driving systems is no trivial task, even more so for those systems of SAE Level 3 or above. To achieve this, mechanisms are needed that can continuously monitor the system's operating conditions, also denoted as the system's operational design domain. This paper presents a safety concept for automated driving systems which uses a combination of onboard runtime monitoring via connected dependability cage and off-board runtime monitoring via a remote command control center, to continuously monitor the system's ODD. On one side, the connected dependability cage fulfills a double functionality: (1) to monitor continuously the operational design domain of the automated driving system, and (2) to transfer the responsibility in a smooth and safe manner between the automated driving system and the off-board remote safety driver, who is present in the remote command control center. On the other side, the remote command control center enables the remote safety driver the monitoring and takeover of the vehicle's control. We evaluate our safety concept for automated driving systems in a lab environment and on a test field track and report on results and lessons learned.