Paper Info
Title
Augmented Vehicular Reality: Enabling Extended Vision for Future Vehicles.
Abstract
Like today's autonomous vehicle prototypes, vehicles in the future will have rich sensors to map and identify objects in the environment. For example, many autonomous vehicle prototypes today come with line-of-sight depth perception sensors like 3D cameras. These cameras 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, not just for autonomous vehicles but for other Advanced Driving Assistance Systems (ADAS), we explore a capability called Augmented Vehicular Reality (AVR). AVR broadens the vehicle's visual horizon by enabling it to share visual information with other nearby vehicles, but requires careful techniques to align coordinate frames of reference, and to detect dynamic objects. Preliminary evaluations hint at the feasibility of AVR and also highlight research challenges in achieving AVR's potential to improve autonomous vehicles and ADAS.
Year
DOI
Venue
2017
10.1145/3032970.3032976
HotMobile
Keywords
Field
DocType
Autonomous Cars, ADAS, Collaborative Sensing, Extended Vision
Computer vision,Visibility,Computer science,Extreme weather,Real-time computing,Artificial intelligence,Depth perception,Frame of reference
Conference
Citations 
PageRank 
References 
11
0.62
19
Authors
6
Name
Order
Citations
PageRank
Hang Qiu1505.16
fawad ahmad2324.42
ramesh govindan3154302144.86
Marco Gruteser44631309.81
Fan Bai52017135.11
Gorkem Kar6633.82