Paper Info
Title
High Integrity Localization With Multi-Lane Camera Measurements
Abstract
Localization with high integrity is crucial for highly autonomous vehicles. This requires that the localization system send a warning to a client application when it should not be used. The concept of integrity was firstly developed for aviation applications and recently became an active research area for autonomous vehicles. GNSS information merged with dead reckoning sensors is not sufficient for lane level localization in all navigation environments. Map-aided localization with vision sensors is essential to provide redundant and complementary information. In this work, a multi-sensor data fusion method that takes advantage of a high definition (HD) map is presented and the integrity of the obtained solution is quantified. A Fault Detection and Exclusion (FDE) step is added to exclude the faulty measurements from the fusion procedure. A second step is to bound the estimation errors in the Along Track (AT) and Cross Track (CT) directions through Protection Levels (PL). For this step, the usual Gaussian distribution is replaced by a Student's distribution with an adapted degree of freedom chosen according to the navigation environment. The performance of the approach is evaluated with an experimental vehicle equipped with a camera able to detect up to four lane markings simultaneously.
Year
DOI
Venue
2019
10.1109/IVS.2019.8813988
2019 30TH IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV19)
Field
DocType
ISSN
Computer vision,Computer science,Artificial intelligence
Conference
1931-0587
Citations 
PageRank 
References 
0
0.34
0
Authors
3
Name
Order
Citations
PageRank
Joelle Al Hage100.34
Philippe Xu200.34
Philippe Bonnifait345255.82