Vehicle Localization Based on Visual Lane Marking and Topological Map Matching


== Abstract ==

urate and reliable localization is crucial to autonomous vehicle navigation and driver assistance systems. This paper presents a novel approach for online vehicle localization in a digital map. Two distinct map matching algorithms are proposed: i) Iterative Closest Point (ICP) based lane level map matching is performed with visual lane tracker and grid map ii) decision-rule based approach is used to perform topological map matching. Results of both the map matching algorithms are fused together with GPS and dead reckoning using Extended Kalman Filter to estimate vehicle’s pose relative to the map. The proposed approach has been validated on real life conditions on an equipped vehicle. Detailed analysis of the experimental results show improved localization using the two aforementioned map matching algorithms.


== Original document ==

The different versions of the original document can be found in:

* [https://hal.inria.fr/hal-03043594 https://hal.inria.fr/hal-03043594]

* [http://xplorestaging.ieee.org/ielx7/9187508/9196508/09197543.pdf?arnumber=9197543 http://xplorestaging.ieee.org/ielx7/9187508/9196508/09197543.pdf?arnumber=9197543],
: [http://dx.doi.org/10.1109/icra40945.2020.9197543 http://dx.doi.org/10.1109/icra40945.2020.9197543]

* [https://dblp.uni-trier.de/db/conf/icra/icra2020.html#AsgharGLL20 https://dblp.uni-trier.de/db/conf/icra/icra2020.html#AsgharGLL20],
: [https://doi.org/10.1109/ICRA40945.2020.9197543 https://doi.org/10.1109/ICRA40945.2020.9197543],
: [https://academic.microsoft.com/#/detail/3090448702 https://academic.microsoft.com/#/detail/3090448702]