Name
Abstract | ||
|---|---|---|
This article focuses on development baseline for a novel LIDAR for future autonomous cars, which require perception not only in clear weather, but also under harsh weather conditions such as fog and rain. Development of automotive laser scanners is bound to the following requirements: maximize sensor performance, assess the performance level and keep the scanner component costs reasonable (<;1000 €) even if more expensive optical and electronic components are needed. The objective of this article is to review the existing automotive laser scanners and their capabilities to pave the way for developing new scanner prototypes, which are more capable in harsh weather conditions. Testing of scanner capabilities has been conducted in the northern part of the Finland, at Sodankylä Airport, where fog creates a special problem. The scanner has been installed in the airport area for data gathering and analyzes if fog, snow or rain are visible in the scanner data. The results indicate that these conditions degrade sensor performance by 25%, and therefore, future work in software module development should take this into account with in-vehicle system performance estimations concerning the visual range of the scanner. This allows the vehicle to adapt speed, braking distance and stability control systems accordingly. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/ITSC.2016.7795565 | 2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC) |
Keywords | Field | DocType |
in-vehicle system performance estimations,harsh weather conditions,automotive laser scanners,automotive LIDAR sensor development | Data collection,Intelligent decision support system,Simulation,Electronic stability control,Braking distance,Lidar,Scanner,Engineering,Electronic component,Automotive industry | Conference |
ISBN | Citations | PageRank |
978-1-5090-1890-1 | 2 | 0.47 |
References | Authors | |
2 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Matti Kutila | 1 | 40 | 8.63 |
| Pyykonen, P. | 2 | 3 | 2.89 |
| Werner Ritter | 3 | 28 | 8.94 |
| Oliver Sawade | 4 | 28 | 5.84 |
| Bernd Schäufele | 5 | 11 | 3.02 |