Using Crash Databases to Predict Effectiveness of New Autonomous Vehicle Maneuvers for Lane-Departure Injury Reduction

Forskningsoutput: TidskriftsbidragArtikel i vetenskaplig tidskrift

Abstract

Autonomous vehicle functions in safety-critical situations show promise in reducing the risk and saving lives in accidents compared to existing safety systems. Consequently, it is from many perspectives advantageous to be able to quantify the potential benefits of new autonomous systems for vehicle maneuvers at-the-limit of tire friction. Here, to estimate the potential in terms of saved lives and reduced degree of injuries in accidents for new, not yet existing systems, a framework has been developed by combining available historic data, in the form of crash databases, and statistical methods with comparative calculations of vehicle behavior using numerical optimization rather than simulation. The framework performs effectively, it gives interesting insights into the relation between more traditional active yaw control and optimal autonomous lane-keeping control, and it clearly demonstrates the potential of saved lives by using autonomous vehicle maneuvers.

Detaljer

Författare
Enheter & grupper
Externa organisationer
  • Linköping University
Forskningsområden

Ämnesklassifikation (UKÄ) – OBLIGATORISK

  • Farkostteknik
  • Transportteknik och logistik

Nyckelord

Originalspråkengelska
Sidor (från-till)3479-3490
Antal sidor12
TidskriftIEEE Transactions on Intelligent Transportation Systems
Volym22
Utgåva nummer6
Tidigt onlinedatum2020 apr 8
StatusPublished - 2021 jun 1
PublikationskategoriForskning
Peer review utfördJa

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