Name
Abstract | ||
|---|---|---|
Current perception systems mostly require direct line of sight to anticipate and ultimately prevent potential collisions at intersections with other road users. We present a fully integrated autonomous system capable of detecting shadows or weak illumination changes on the ground caused by a dynamic obstacle in NLoS scenarios. This additional virtual sensor “ShadowCam” extends the signal range utilized so far by computer-vision ADASs. We show that (1) our algorithm maintains the mean classification accuracy of around 70% even when it doesn't rely on infrastructure - such as AprilTags - as an image registration method. We validate (2) in real-world experiments that our autonomous car driving in night time conditions detects a hidden approaching car earlier with our virtual sensor than with the front facing 2-D LiDAR. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/IROS40897.2019.8967554 | 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) |
Keywords | DocType | ISSN |
autonomous cars,autonomous system,dynamic obstacle,virtual sensor,computer-vision ADASs,image registration method,NLoS obstacle detection,ShadowCam | Conference | 2153-0858 |
ISBN | Citations | PageRank |
978-1-7281-4005-6 | 0 | 0.34 |
References | Authors | |
15 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Felix Naser | 1 | 1 | 0.70 |
| Igor Gilitschenski | 2 | 31 | 4.05 |
| Alexander Amini | 3 | 54 | 10.54 |
| Christina Liao | 4 | 0 | 0.34 |
| Guy Rosman | 5 | 174 | 18.86 |
| Sertac Karaman | 6 | 1190 | 87.27 |
| Daniela Rus | 7 | 7128 | 657.33 |