Developing and Testing Robust Autonomy: The University of Sydney Campus Data Set

Vision and lidar are complementary sensors that are incorporated into many applications of intelligent transportation systems. These sensors have been used to great effect in research related to perception, navigation, and deep learning applications. Despite this success, the validation of algorithm...

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Bibliographic Details
Published in:IEEE intelligent transportation systems magazine 2020-01, Vol.12 (4), p.23-40
Main Authors: Zhou, Wei, Berrio, Julie Stephany, De Alvis, Charika, Shan, Mao, Worrall, Stewart, Ward, James, Nebot, Eduardo
Format: Article
Language:English
Subjects:
Algorithms
Autonomous vehicles
Cameras
Colleges & universities
Data collection
Intelligent transportation systems
Laser radar
Machine learning
New technology
Robustness
Semantics
Sensors
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Summary:Vision and lidar are complementary sensors that are incorporated into many applications of intelligent transportation systems. These sensors have been used to great effect in research related to perception, navigation, and deep learning applications. Despite this success, the validation of algorithm robustness has recently been recognized as a major challenge for the massive deployment of these new technologies.
ISSN:1939-1390
1941-1197
DOI:10.1109/MITS.2020.2990183