(Created page with " == Abstract == Modern automated and cooperative driver assistance systems (CoDAS) rely deeply on the position estimation. Regardless of absolute positioning accuracy, the re...") |
m (Scipediacontent moved page Draft Content 129460447 to Lorenz et al 2015a) |
(No difference)
| |
Latest revision as of 00:23, 29 January 2021
Abstract
Modern automated and cooperative driver assistance systems (CoDAS) rely deeply on the position estimation. Regardless of absolute positioning accuracy, the relative position in regard to driving environment and other vehicles needs to be of high quality to enable sophisticated functions. Global Navigation Satellite Systems (GNSS) fulfill this demand only partially. In this paper we present an algorithm to accurately infer the driving lane by utilizing Dedicated Short Range Communication (DSRC) and map data alone. We evaluate our approach against simulated and real-life data from Europes largest cooperative vehicle Field Operational Test (FOT): simTD. This lane detection algorithm will be an enabler for CoDAS functions like collaborative driving and merging developed in the TEAM IP project.
Original document
The different versions of the original document can be found in:
Document information
Published on 01/01/2015
Volume 2015, 2015
DOI: 10.1109/itsc.2015.352
Licence: CC BY-NC-SA license
Share this document
Keywords
claim authorship
Are you one of the authors of this document?