Name
Abstract | ||
|---|---|---|
Advanced Driver Assistance System (ADAS) algorithms are of significant importance in the modern automotive industry. The algorithms have changed the approach to two important issues of the industry: traffic efficiency, and safety. ADAS algorithms have very demanding requirements, such as real time execution and low memory consumption. Thus, one of the main challenges is to satisfy these requirements without compromising the reliability. Although all components that add to the safety are important, one that is most commonly addressed is drowsiness detection, because the drowsiness is at the top causes of traffic accidents. Automotive grade standards have changed periodically to include and tailor recent techniques and models. In this paper, we present driver drowsiness detection solution which is implemented on the Adaptive AUTOSAR platform. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/ICCE-Berlin.2018.8576255 | 2018 IEEE 8th International Conference on Consumer Electronics - Berlin (ICCE-Berlin) |
Keywords | Field | DocType |
automotive,software,Adaptive AUTOSAR,ADAS,Driver Monitoring,Computer Vision | Advanced driver,Computer science,Traffic efficiency,AUTOSAR,Reliability engineering,Automotive industry | Conference |
ISSN | ISBN | Citations |
2166-6814 | 978-1-5386-6096-6 | 0 |
PageRank | References | Authors |
0.34 | 2 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Milan Dokic | 1 | 0 | 0.34 |
| Stefan Nicetin | 2 | 0 | 0.34 |
| Gordana Velikic | 3 | 10 | 8.37 |
| Tihomir Andelic | 4 | 0 | 0.34 |