On Statistical Methods for Safety Validation of Automated Vehicles
Doktorsavhandling, 2022

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performance evaluation

extreme value theory

Automotive

validation

automated vehicles

simulation

verification

automated driving systems

Författare

Daniel Åsljung

Chalmers, Elektroteknik, System- och reglerteknik

Inkluderade delarbeten

Using Extreme Value Theory for Vehicle Level Safety Validation and Implications for Autonomous Vehicles

IEEE Transactions on Intelligent Vehicles,;Vol. 2(2017)p. 288-297

Artikel i vetenskaplig tidskrift

Validation of Collision Frequency Estimation Using Extreme Value Theory

Proceedings of the IEEE Intelligent Transportation Systems Conference, 2017,;Vol. 2018-March(2017)p. 1857-1862

Paper i proceeding

A probabilistic framework for collision probability estimation and an analysis of the discretization precision

IEEE Intelligent Vehicles Symposium, Proceedings,;Vol. 2019-June(2019)p. 52-57

Paper i proceeding

On Automated Vehicle Collision Risk Estimation using Threat Metrics in Subset Simulation

IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC,;(2021)

Paper i proceeding

D. Åsljung, C. Zandén, J. Fredriksson. A Risk Reducing Fleet Monitor for Automated Vehicles Based on Extreme Value Theory

Manuskript

Populärvetenskaplig beskrivning

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Forskningsprojekt

Tidseffektiv RobUSt verifiering av auTonoma fordon - teori och MEtoder (TRUST-ME)

VINNOVA (2014-01373), 2014-05-01 -- 2017-12-31.

Kategorisering

Styrkeområden

Transport

Ämneskategorier (SSIF 2011)

Elektroteknik och elektronik

Sannolikhetsteori och statistik

Identifikatorer

ISBN

978-91-7905-757-2

Övrigt

Serie

Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 5223

Utgivare

Chalmers

Examination

2022-12-06 13:15 -- 16:15

SB-H5

Opponent: Prof. Dr. Simon Burton, Fraunhofer IKS, Germany

Mer information

Senast uppdaterat

2023-10-26