A Comparison of autonomous vehicle navigation simulators under regulatory and reinforcement learning constraints
View/Open
ccia201915.pdf (537,8Kb) (Restricted access)
Request copy
Què és aquest botó?
Aquest botó permet demanar una còpia d'un document restringit a l'autor. Es mostra quan:
- Disposem del correu electrònic de l'autor
- El document té una mida inferior a 20 Mb
- Es tracta d'un document d'accés restringit per decisió de l'autor o d'un document d'accés restringit per política de l'editorial
Document typeConference lecture
Defense date2019
PublisherIOS Press
Rights accessRestricted access - publisher's policy
Abstract
The transition from conventional vehicles to autonomous vehicles is regulated thorough ADAS (Advanced Driver Assistance Systems) functionalities. The combination of different ADAS functions allows vehicles navigate on a highway autonomously, but at the same time, following the traffic rules and regulations requirements, and also guaranteeing safety on the road. The practical objective in this article is to implement a Reinforcement Learning method whose actions are based in these regulated functions for autonomous vehicles navigation. With this aim, a study of the state-of-the-art of autonomous vehicles simulators has been completed. Hence, the algorithm will be tested using a five-lane highway simulator, previously
selected. Results and performance of the model through experimentation will be presented and evaluated using the simulator for different network architectures.
CitationCabañeros, A.; Angulo, C. A Comparison of autonomous vehicle navigation simulators under regulatory and reinforcement learning constraints. A: International Conference of the Catalan Association for Artificial Intelligence. "Artificial Intelligence Research and Development vol. 319". IOS Press, 2019, p. 115-124.
ISBN978-1-64368-014-9
Publisher versionhttp://ebooks.iospress.nl/volumearticle/52827
Files | Description | Size | Format | View |
---|---|---|---|---|
ccia201915.pdf![]() | 537,8Kb | Restricted access |
Except where otherwise noted, content on this work
is licensed under a Creative Commons license
:
Attribution-NonCommercial-NoDerivs 3.0 Spain