Abstract:
Reliable and precise object tracking is an essential requirement for automated driving. The majority of LiDAR-based tracking algorithms resort to raw range measurements o...Show MoreMetadata
Abstract:
Reliable and precise object tracking is an essential requirement for automated driving. The majority of LiDAR-based tracking algorithms resort to raw range measurements only. In contrast, we propose a novel method to extract compact and salient features from LiDAR intensities. Using the example of an evasive steering maneuver of a leading vehicle, we show that leveraging these intensity features allows for a more accurate estimation of object states. The resulting early detection of target object rotation allows an automated driving system additional time for deriving an appropriate driving policy.
Published in: 2019 IEEE Intelligent Vehicles Symposium (IV)
Date of Conference: 09-12 June 2019
Date Added to IEEE Xplore: 29 August 2019
ISBN Information: