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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Testing of AEB in winter conditions

Berg, Oscar January 2021 (has links)
Autonomous driver assistance systems are standard in vehicles. These systems help the driver to prevent an accident by automatically applying brakes on the vehicle. They assist the driver and help to prevent injuries and casualties caused by traffic accidents yearly.  This report shows data about how a vehicles Autonomous Emergency Braking (AEB) system reacts to a road surface with lower friction, for example in winter conditions. To help with the test was a steering robot (SR60 Orbit) and a pedal robot (CBAR 500) used to make the accuracy higher. The target that was used during tests was a Global Vehicle target (GVT). The tests were performed at ArcticFalls proving ground outside Älvsbyn on both asphalt and snow.  The tests show a noticeable difference between the distance it takes the car to stop on asphalt and snow. It emerges from the tests that systems like AEB can’t handle low friction, which is a huge risk for an accident. To prevent the risk of a collision is systems that can measure friction a priority.
2

Improving AEB in winter conditions using road condition sensor

Edvinger, Carl Jacob, Breitbach, Moritz January 2022 (has links)
Autonomous braking systems are becoming more common in modern cars. Autonomous EmergencyBraking (AEB) can help a driver avoid collision by automatically applying the brakes and stop thevehicle before an accident occurs. This can help save lives and reduce the risk of injuries in traffic.Previous work shows that AEB only works well on asphalt. On more slippery surfaces like snow theAEB has a hard time preventing a collision. This report will process the possibility to make an AEB thatwill reduce the risk of collision and injuries by adapting the braking distance for different surfaces. Aroad condition sensor was used to determine the different surfaces and the estimate of the tire toroad friction. This is an optical sensor that is used to categorize surfaces such as dry/wet asphalt,snow, and ice. In order to achieve good repeatability an SR60 Orbit steering robot combined with aCBAR 500 pedal robot was used. For comparison to the car’s AEB a GVT (Global Vehicle Target) wasused as a target.The results from the test show that a surface adapted AEB can make a difference. The adapted AEBstarted braking earlier than the car’s AEB and prevented collisions on snow, whilst the regular AEB had collisions with the GVT on snow.

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