Merit-Based Motion Planning for Autonomous Vehicles in Urban Scenarios

Safe and adaptable motion planning for autonomous vehicles remains an open problem in urban environments, where the variability of situations and behaviors may become intractable using rule-based approaches. This work proposes a use-case-independent motion planning algorithm that generates a set of...

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Published inSensors (Basel, Switzerland) Vol. 21; no. 11; p. 3755
Main Authors Medina-Lee, Juan, Artuñedo, Antonio, Godoy, Jorge, Villagra, Jorge
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 28.05.2021
MDPI
Subjects
Adaptation
Automation
autonomous driving
Autonomous vehicles
Behavior
Business metrics
Candidates
Comfort
Decision making
Design
Design parameters
merit function
Motion planning
Optimization techniques
Planning
Sensors
speed profile
trajectory generation
Urban environments
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Summary:Safe and adaptable motion planning for autonomous vehicles remains an open problem in urban environments, where the variability of situations and behaviors may become intractable using rule-based approaches. This work proposes a use-case-independent motion planning algorithm that generates a set of possible trajectories and selects the best of them according to a merit function that combines longitudinal comfort, lateral comfort, safety and utility criteria. The system was tested in urban scenarios on simulated and real environments, and the results show that different driving styles can be achieved according to the priorities set in the merit function, always meeting safety and comfort parameters imposed by design.
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ISSN:1424-8220
1424-8220
DOI:10.3390/s21113755