Autonomous Driving Data Chain & Interfaces
@article{Kahl2021AutonomousDD, title={Autonomous Driving Data Chain \& Interfaces}, author={Benjamin Kahl}, journal={ArXiv}, year={2021}, volume={abs/2104.01252} }
Recent developments in autonomous driving technology have proven that map data may be used, not only for general routing purposes, but also for to enhance and complement common sensor data. This document reviews the most commonly used interfaces and formats at each step of a self-healing map data chain.
References
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ADASIS and SENSORIS platforms and their impact Automotive Ecosystem" slides, IAEC
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Map Line Interface for Autonomous Driving
- Computer Science2018 21st International Conference on Intelligent Transportation Systems (ITSC)
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It is shown that the usage of mean values and covariance matrices approximate the true distributions rather accurately, and therefore are both from an accuracy point of view and from a bandwidth points of view the way to represent map lines in interfaces.
Automated Driving Data Chain Challenges" slides, Automated Vehicle Symposium
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Evaluation of 3D-distance measurement accuracy of stereo-vision systems
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An accuracy evaluation method of two stereo-vision systems, which use a coordinate measuring machine (CMM) and a reference block, has been presented, and the results have been presented for systems using infra red cameras and webcams.
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A comprehensive statistical evaluation of selected state-of-the-art stereo matching approaches on an extensive dataset is presented and reference values for the precision limits actually achievable in practice are established.
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