Lane Precise Localization With Production Vehicle Sensors And Application To Augmented Reality Navigation
Download Lane Precise Localization With Production Vehicle Sensors And Application To Augmented Reality Navigation PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Lane Precise Localization With Production Vehicle Sensors And Application To Augmented Reality Navigation book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Lane-Precise Localization with Production Vehicle Sensors and Application to Augmented Reality Navigation
Author: Rabe, Johannes
language: en
Publisher: KIT Scientific Publishing
Release Date: 2019-01-10
This works describes an approach to lane-precise localization on current digital maps. A particle filter fuses data from production vehicle sensors, such as GPS, radar, and camera. Performance evaluations on more than 200 km of data show that the proposed algorithm can reliably determine the current lane. Furthermore, a possible architecture for an intuitive route guidance system based on Augmented Reality is proposed together with a lane-change recommendation for unclear situations.
Lane-Precise Localization With Production Vehicle Sensors and Application to Augmented Reality Navigation
This works describes an approach to lane-precise localization on current digital maps. A particle filter fuses data from production vehicle sensors, such as GPS, radar, and camera. Performance evaluations on more than 200 km of data show that the proposed algorithm can reliably determine the current lane. Furthermore, a possible architecture for an intuitive route guidance system based on Augmented Reality is proposed together with a lane-change recommendation for unclear situations. This work was published by Saint Philip Street Press pursuant to a Creative Commons license permitting commercial use. All rights not granted by the work's license are retained by the author or authors.
Probabilistic Motion Planning for Automated Vehicles
Author: Naumann, Maximilian
language: en
Publisher: KIT Scientific Publishing
Release Date: 2021-02-25
In motion planning for automated vehicles, a thorough uncertainty consideration is crucial to facilitate safe and convenient driving behavior. This work presents three motion planning approaches which are targeted towards the predominant uncertainties in different scenarios, along with an extended safety verification framework. The approaches consider uncertainties from imperfect perception, occlusions and limited sensor range, and also those in the behavior of other traffic participants.