Motion Planning Approach Considering Localization Uncertainty

Localization plays an important role in autonomous driving since a high level of accuracy in vehicle localization is indispensable for a safe navigation. Most of the motion planning approaches in the literature assume negligible uncertainty in vehicle localization. However, the accuracy of localizat...

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Bibliographic Details
Published in:IEEE transactions on vehicular technology 2020-06, Vol.69 (6), p.5983-5994
Main Authors: Artunedo, Antonio, Villagra, Jorge, Godoy, Jorge, Castillo, Maria Dolores del
Format: Article
Language:English
Subjects:
Algorithms
Automated driving
Feasibility
Human motion
In vehicle
Localization
localization uncertainty
Motion planning
Navigation
Occupancy
Planning
Probabilistic logic
Real-time systems
Roads
System reliability
Trajectory
Uncertainty
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Summary:Localization plays an important role in autonomous driving since a high level of accuracy in vehicle localization is indispensable for a safe navigation. Most of the motion planning approaches in the literature assume negligible uncertainty in vehicle localization. However, the accuracy of localization systems can be low by design or even can drop depending on the environment in some cases. In these situations, the localization uncertainty can be taken into consideration in motion planning to increase the system reliability. Accordingly, this work presents two main contributions: (i) a probabilistic occupancy grid-based approach for localization uncertainty propagation, and (ii) a motion planning strategy that relies on such occupancy grid. Thus, the proposed motion planning solution for automated driving is able to generate safe human-like trajectories in real time while considering the localization uncertainty, ego-vehicle constrains and obstacles. In order to validate the proposed algorithms, several experiments have been conducted in a real environment.
ISSN:0018-9545
1939-9359
DOI:10.1109/TVT.2020.2985546