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Comparing Collision Threat Measures for Verification of Autonomous Vehicles using Extreme Value Theory

Daniel Åsljung (Institutionen för signaler och system, Mekatronik) ; Jonas Nilsson ; Jonas Fredriksson (Institutionen för signaler och system, Mekatronik)
9th IFAC Symposium on Intelligent Autonomous Vehicles IAV 2016, Leipzig, Germany, 29 June - 1 July 2016 p. 57-62. (2016)
[Konferensbidrag, refereegranskat]

The verification of safety is expected to be one of the largest challenges in the commercialization of autonomous vehicles. Using traditional methods would require infeasible time and resources. Recent research has shown the possibility of using near-collisions in order to estimate the frequency of actual collisions using Extreme Value Theory. However, little research has been done on how the measure for determining the closeness to a collision affect the result of the estimation. This paper compares a collision-based measure against one that relates to an inevitable collision state. The result shows that using inevitable collision states is more robust and that more research needs to be made into measures of collision proximity.

Nyckelord: Automotive, Autonomous vehicles, Safety, Statistical inference, Verification & Validation

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Denna post skapades 2016-12-06. Senast ändrad 2017-11-29.
CPL Pubid: 245873


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Institutioner (Chalmers)

Institutionen för signaler och system, Mekatronik (2005-2017)


Sannolikhetsteori och statistik
Robotteknik och automation

Chalmers infrastruktur

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