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Effectiveness of ‘Mobileye’

 

Accident Prevention and Accident Mitigation System Effectiveness Report ‘Mobileye’® Technologies Ltd., April, 2007


The ‘Mobileye’®™ AWS (Advance Warning System) is a driver assistance system for accident prevention and accident mitigation. AWS is based on a camera located on the vehicle’s front windshield that watches the road ahead. The AWS utilizes advanced vision technologies for:

  • Lane detection and road curvature calculation – the AWS detects and measures lane position relative to the vehicle and provides distance to lane marks, detection of lane crossing including lane crossing prediction (by calculating Time to Lane Crossing - TLC) for earlier warnings than received from actual rumble-strips.
  • Vehicle detection – the AWS detects vehicles ahead, and measures their distance, azimuth, relative speed and Time To Contact (TTC). The AWS uses these calculations for providing continuous headway and potential collision related information. The road curvature calculation provided by the lane detection capability enables to identify which of the vehicles ahead is in the same lane as the “host vehicle”

 

Its detection of vehicles and lanes markings provides the driver with the following safety alert types:

  • Forward Collision Warning (FCW) – alerting the driver of an impending collision with the vehicle ahead (up to 2.7 seconds before collision occurs)
  • Lane Departure Warning (LDW) – acting as “audible rumble strips”, LDW produces a rumble sound up to 0.5 seconds before unintentionally departing from the lane or the road altogether
  • Headway Monitoring and Warning (HMW) – enables continuous monitoring of the driving distance (headway) kept from the vehicle ahead, and warns the driver when headway decreases to a dangerous level

 

These 3 features correspond with 3 of the leading causes of road accidents:

  • Rear-end accidents caused by driver inattention
  • Lane departure, and Run Off Road (ROR) accidents
  • Rear-end accident caused by insufficient distance keeping

Download the System Effectiveness Report in PDF format (543KB)