Back to Search
Start Over
Agent architecture for adaptive behaviours in autonomous driving
- Source :
- IEEE Access, Vol 8, Pp 154906-154923 (2020)
- Publication Year :
- 2020
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2020.
-
Abstract
- Evolution has endowed animals with outstanding adaptive behaviours which are grounded in the organization of their sensorimotor system. This paper uses inspiration from these principles of organization in the design of an artificial agent for autonomous driving. After distilling the relevant principles from biology, their functional role in the implementation of an artificial system are explained. The resulting Agent, developed in an EU H2020 Research and Innovation Action, is used to concretely demonstrate the emergence of adaptive behaviour with a significant level of autonomy. Guidelines to adapt the same principled organization of the sensorimotor system to other agents for driving are also obtained. The demonstration of the system abilities is given with example scenarios and open access simulation tools. Prospective developments concerning learning via mental imagery are finally discussed.
- Subjects :
- Functional role
Adaptive Behaviour Affordance Competition Hypothesis Autonomous Driving Explainable Artificial Intelligence
General Computer Science
media_common.quotation_subject
Adaptive behaviour
03 medical and health sciences
0302 clinical medicine
autonomous driving
Human–computer interaction
0502 economics and business
General Materials Science
Agent architecture
media_common
050210 logistics & transportation
explainable artificial intelligence
05 social sciences
Sensorimotor system
General Engineering
affordance competition hypothesis
Action (philosophy)
Trajectory
lcsh:Electrical engineering. Electronics. Nuclear engineering
lcsh:TK1-9971
030217 neurology & neurosurgery
Autonomy
Mental image
Subjects
Details
- Language :
- English
- ISSN :
- 21693536
- Database :
- OpenAIRE
- Journal :
- IEEE Access, Vol 8, Pp 154906-154923 (2020)
- Accession number :
- edsair.doi.dedup.....fbbefcfe93f1d85e894cd21f8fef0944