On Automated Vehicle Collision Risk Estimation using Threat Metrics in Subset Simulation
Paper i proceeding, 2021

This paper presents a method for accelerated evaluation of an automated driving function using the subset simulation method. The focus of the paper is to investigate how the evaluation is affected by the choice of metric that is used to steer the subset simulation towards failure. This is done by comparing the use of some common threat assessment metrics and see how close the estimated failure rate of a function gets to a Monte Carlo simulation reference. The scope of this comparison is an ACC function that is faced with a set of cutin scenarios. It is found that all investigated metrics provide results relatively close to the reference, but the metrics relating to a state where collision is deemed to be unavoidable proved a little better.


Daniel Åsljung

Chalmers, Elektroteknik, System- och reglerteknik

Carl Zandén

Zenseact AB

Jonas Fredriksson

Chalmers, Elektroteknik, System- och reglerteknik

Majid K Vakilzadeh

Zenseact AB

IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC

978-172819142-3 (ISBN)

2021 IEEE International Intelligent Transportation Systems Conference (ITSC)
Indianapolis, IN, USA,




Elektroteknik och elektronik





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