Vehicle Localization Based on Visual Lane Marking and Topological Map Matching

Asghar, Rabbia; Garzón, Mario Garzon; Lussereau, Jerome; Laugier, Christian

Vehicle Localization Based on Visual Lane Marking and Topological Map Matching

Conference paper (2020)

Authors

Rabbia Asghar Université Grenoble Alpes

Mario Garzon Garzón Université Grenoble Alpes

Jerome Lussereau Université Grenoble Alpes

Christian Laugier Université Grenoble Alpes

Affiliation

External organisation

Autonomous Vehicles Lane Level Matching Map Relative Localization Topological Map Matching

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Published Date

2020

Language

English

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Abstract

Accurate 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.

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