Minimizing driver interference under a probablistic safety constraint in emergency collision avoidance systems

Jeff Johnson, Yajia Zhang, Kris Hauser

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Automated emergency maneuvering systems can avoid or reduce the severity of collisions by taking control of a vehicle away from the driver during high-risk situations. To do so, these systems must be capable of making certain decisions: there is the choice of when to interfere in the driver's control, which is made challenging in the presence of dynamic obstacles and uncertain information (such as that provided by imperfect sensors), and there is the choice of how to interfere, since, in general, controls that mitigate collisions will not be unique. We address both of these questions with a probabilistic decision threshold framework that overrides the driver's control only when safety drops beneath a problem-specific threshold, and minimizes the magnitude of the interference. We demonstrate its application to two scenarios: collision-imminent braking for obstacles traveling along the vehicle's path, and braking and accelerating for unprotected lane crossings.

Original languageEnglish (US)
Title of host publication2012 15th International IEEE Conference on Intelligent Transportation Systems, ITSC 2012
Pages457-462
Number of pages6
DOIs
StatePublished - 2012
Externally publishedYes
Event2012 15th International IEEE Conference on Intelligent Transportation Systems, ITSC 2012 - Anchorage, AK, United States
Duration: Sep 16 2012Sep 19 2012

Publication series

NameIEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC

Other

Other2012 15th International IEEE Conference on Intelligent Transportation Systems, ITSC 2012
Country/TerritoryUnited States
CityAnchorage, AK
Period9/16/129/19/12

ASJC Scopus subject areas

  • Automotive Engineering
  • Mechanical Engineering
  • Computer Science Applications

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