Abstract
The advanced driver assistance systems (ADAS) of the future will rely heavily on an accurate and extensive description of the ego vehicle’s environment based on multiple sensors. This paper gives an overview of a framework tackling this task by using Simultaneous Localization And Mapping (SLAM) and Detection And Tracking of Moving Objects (DATMO) techniques in real world scenarios using multiple 4-layer lidar sensors and a radar sensor. After a short literature overview, a modular framework is proposed which allows testing and evaluating different algorithms in outdoor scenarios. An advanced particle filter based tracking algorithm is presented to estimate the shape of extended objects with arbitrary forms. Results are evaluated based on sensor data.
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© 2013 Springer International Publishing Switzerland
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Schütz, M., Dietmayer, K. (2013). A Flexible Environment Perception Framework for Advanced Driver Assistance Systems. In: Fischer-Wolfarth, J., Meyer, G. (eds) Advanced Microsystems for Automotive Applications 2013. Lecture Notes in Mobility. Springer, Heidelberg. https://doi.org/10.1007/978-3-319-00476-1_3
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DOI: https://doi.org/10.1007/978-3-319-00476-1_3
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Print ISBN: 978-3-319-00475-4
Online ISBN: 978-3-319-00476-1
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