Landmarks based human-like guidance for driving navigation in an urban environment
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Publication Date
2018-03-14Journal Title
IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC
ISSN
2153-0009
ISBN
9781538615256
Volume
2018-March
Pages
1-6
Type
Conference Object
Metadata
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Wang, B., Stafford-Fraser, Q., Robinson, P., Dias, E., & Skrypchuk, L. (2018). Landmarks based human-like guidance for driving navigation in an urban environment. IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC, 2018-March 1-6. https://doi.org/10.1109/ITSC.2017.8317802
Abstract
© 2017 IEEE. Driving is a cognitively demanding task, and many current navigation systems present confusing guidance instructions that add to the distraction. Human navigators, by contrast, schedule their advice to minimise distraction, and phrase instructions in terms of visible landmarks to avoid confusion. In this paper, we present the basis for a 'natural navigation' system which interprets distances as references to landmarks. We use Extended Kalman Filtering to integrate visual odometry with other sensor data in order to obtain precise vehicle motion, then, based on the filtered motion parameters, we characterize recognised visual landmarks as locations on the navigational map. The navigation system can then use references to these landmarks in its driver instructions rather than absolute distances. Experimental results show that landmarks can be located on the navigational map with sufficient accuracy using normal vehicle telemetry and a dashboard camera.
Identifiers
External DOI: https://doi.org/10.1109/ITSC.2017.8317802
This record's URL: https://www.repository.cam.ac.uk/handle/1810/279695
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