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Potential Enhancement for Wrong-way Driver Detection using Precise Attribute Information

Published online by Cambridge University Press:  14 August 2019

Jinyue Wang Open the ORCID record for Jinyue Wang [Opens in a new window] ,
Martin Metzner  and
Volker Schwieger
Jinyue Wang*
Affiliation:
(University of Stuttgart, Institute of Engineering Geodesy, Germany)
Martin Metzner
Affiliation:
(University of Stuttgart, Institute of Engineering Geodesy, Germany)
Volker Schwieger
Affiliation:
(University of Stuttgart, Institute of Engineering Geodesy, Germany)
*
(E-mail: [email protected])
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Abstract

Map-matching is widely used in automotive navigation systems to locate vehicle positions on a given digital road map. Various map-matching algorithms have been developed focusing on different application needs. Within the Ghosthunter project, a weighting-function-based map-matching algorithm has been developed for detecting wrong-way driving in order to improve road safety, particularly in Autobahn entrance and exit areas. This paper aims at exploring the potential use of lane-level attributes and height data in improving the success rate of the previously presented algorithm. This algorithm performs well in entrance and exit areas to the Autobahn, with a high success rate of 99.5% in identifying the road on which the vehicle is actually travelling. In the enhanced algorithm presented in this paper the weight coefficients used for computing the total weighting score of candidate roads are adjusted with the aid of one or both kinds of these precise data. The results confirmed that the usage of these precise data can effectively help to detect and correct mismatches at junctions and overpasses.

Keywords

Map-matchingGNSSLane-level attributeHeight data
Type
Research Article
Information
The Journal of Navigation , Volume 73 , Issue 2 , March 2020 , pp. 384 - 397
Copyright
Copyright © The Royal Institute of Navigation 2019

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