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A Novel Way of Optimizing Headlight Distributions Based on Real-Life Traffic and Eye Tracking Data Part 3: Driver Gaze Behaviour on Real Roads and Optimized Light Distribution.
- Source :
- Applied Sciences (2076-3417); Sep2023, Vol. 13 Issue 17, p9898, 11p
- Publication Year :
- 2023
-
Abstract
- In order to find optimized headlight distributions based on real traffic data, a three-step approach has been chosen. The complete investigations are too extensive to fit into a single paper; this paper is the last of a three part series. Over the three papers, a novel way to optimize automotive headlight distributions based on real-life traffic and eye tracking data is presented. Across all three papers, a total of 119 test subjects participated in the studies with over 15,000 km of driving, including recordings of gaze behaviour, light data, detection distances, and other objects in traffic. In this third paper, driver gaze behaviour is recorded while driving a 128 km round course, covering urban roads, country roads, and motorways. This gaze behaviour is then analysed and compared to prior work covering driver gaze behaviour. Comparing the gaze distributions with roadway object distributions from part two of this series, Analysis of Real-World Traffic Data in Germany and combining them with the idealized baseline headlight distribution from part one, different optimized headlight distributions can be generated. These headlight distributions can be optimized for different driving requirements based on the data that is used and weighting the different road types differently. The resulting headlight distribution is then compared to a standard light distribution in terms of the required luminous flux, angular distribution, and overall shape. Nonetheless, it is the overall approach that has been taken that we see as the primary novel outcome of this investigation, even more than the actual distribution resulting from this effort. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 20763417
- Volume :
- 13
- Issue :
- 17
- Database :
- Complementary Index
- Journal :
- Applied Sciences (2076-3417)
- Publication Type :
- Academic Journal
- Accession number :
- 171855381
- Full Text :
- https://doi.org/10.3390/app13179898