Name
Abstract | ||
|---|---|---|
Autonomous vehicle prototypes today come with line-of-sight depth perception sensors like 3D cameras. These 3D sensors are used for improving vehicular safety in autonomous driving, but have fundamentally limited visibility due to occlusions, sensing range, and extreme weather and lighting conditions. To improve visibility and performance, we explore a capability called Augmented Vehicular Reality (AVR). AVR broadens the vehicle's visual horizon by enabling it to wirelessly share visual information with other nearby vehicles. We show that AVR is feasible using off-the-shelf wireless technologies, and it can qualitatively change the decisions made by autonomous vehicle path planning algorithms. Our AVR prototype achieves positioning accuracies that are within a few percentages of car lengths and lane widths, and it is optimized to process frames at 30fps.
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Year | DOI | Venue |
|---|---|---|
2018 | 10.1145/3325867.3325880 | GetMobile: Mobile Computing and Communications |
DocType | Volume | Issue |
Journal | 22 | 4 |
ISSN | Citations | PageRank |
2375-0529 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hang Qiu | 1 | 0 | 0.34 |
| fawad ahmad | 2 | 32 | 4.42 |
| Fan Bai | 3 | 2017 | 135.11 |
| Marco Gruteser | 4 | 4631 | 309.81 |
| ramesh govindan | 5 | 15430 | 2144.86 |