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.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:ltu-90155 |
| Date | January 2022 |
| Creators | Edvinger, Carl Jacob, Breitbach, Moritz |
| Publisher | Luleå tekniska universitet, Institutionen för teknikvetenskap och matematik |
| Source Sets | DiVA Archive at Upsalla University |
| Language | Swedish |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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