Automated Driving Safety - The Art Of Conscious Risk Taking - Minimum Lateral Distances To Pedestrians
Bert Böddeker1, Wilhard von Wendorff2, Nam Nguyen3, Peter Diehl4, Roland Meertens5 and Rolf Johannson6
1Private Germany
2SGS-TÜV Saar GmbH Germany
3HM München Germany
4private Germany
5private Netherlands
6private Sweden
ABSTRACT
The announced release dates for Automated Driving Systems (ADS) with conditional (SAE-L3) and high (SAE-L4) levels of automation according to [20] are getting closer. Still, there is no established state of the art for proving the safety of these systems. The ISO 26262 for automotive functional safety is still valid for these systems but only covers risks from malfunctions of electric and electronic (E/E) systems. A framework for considering issues caused by weaknesses of the intended functionality itself is standardized in the upcoming release of the ISO 21448 - Safety of the Intended Functionality (SOTIF). Rich experience regarding limitations of safety performance of complex sensors can be found in this standard. In this paper, we highlight another aspect of SOTIF that becomes important for higher levels of automation, especially, in urban areas: 'conscious risk taking'. In traditional automotive systems, conflicting goal resolutions are generally left to the car driver. With SAE-level 3 or at latest SAE-level 4 ADS, the driver is not available for decisions anymore. Even 'safe drivers’ do not use the safest possible driving behavior. In the example of occlusions next to the street, a driver balances the risk of occluded pedestrians against the speed of the traffic flow. Our aim is to make such decisions explicit and sufficiently safe. On the example of crossing pedestrians, we show how to use statistics to derive a conscious quantitative risk-based decision from a previously defined acceptance criterion. The acceptance criterion is derived from accident statistics involving pedestrians.
Keywords: ADS, safety, ISO26262, ISO21448, SOTIF, Jaywalker, Acceptance Criteria, Automated Driving, Pedestrian.
