US 12,084,051 B2
Scenario identification in autonomous driving environments
Magnus Gyllenhammar, Pixbo (SE); and Håkan Sivencrona, Jörlanda (SE)
Assigned to Zenuity AB, Gothenburg (SE)
Filed by ZENUITY AB, Gothenburg (SE)
Filed on Sep. 17, 2021, as Appl. No. 17/477,943.
Claims priority of application No. 20196795 (EP), filed on Sep. 18, 2020.
Prior Publication US 2022/0089153 A1, Mar. 24, 2022
Int. Cl. B60W 30/095 (2012.01); B60W 40/04 (2006.01); B60W 60/00 (2020.01); G06V 20/58 (2022.01)
CPC B60W 30/0956 (2013.01) [B60W 40/04 (2013.01); B60W 60/0015 (2020.02); B60W 60/00274 (2020.02); G06V 20/58 (2022.01); B60W 2554/4041 (2020.02); B60W 2556/40 (2020.02); B60W 2556/50 (2020.02)] 15 Claims
OG exemplary drawing
 
1. A method for identifying scenarios of interest for development, verification and/or validation of an Automated Driving System, ADS, of a vehicle, the method comprising:
obtaining a risk map of a surrounding environment of the vehicle, wherein the risk map is formed based on an actuation capability of the vehicle and a location of free-space areas in the surrounding environment, the actuation capability including an uncertainty estimation for the actuation capability and the location of free-space areas comprising an uncertainty estimation for the estimated location of free-space areas,
wherein the actuation capability of the vehicle comprises one or more of: a braking capacity, a maximum steering angle and a maximum acceleration capability,
wherein the risk map comprises a risk parameter for each of a plurality of area segments comprised in the surrounding environment of the vehicle;
determining a compounded risk value of the ADS based on the risk parameters of a set of area segments of the risk map;
monitoring a scenario trigger by monitoring at least one of:
the determined compounded risk value against a compounded risk trigger threshold,
a development of the risk map over time against a map volatility trigger threshold, or
a development of the compounded risk value over time against a risk volatility threshold; and
if the scenario trigger is detected:
storing sensor data, the stored sensor data being from a time period around a point in time when the scenario trigger was detected.