151. Agent architecture for adaptive behaviours in autonomous driving
- Author
-
Kevin Gurney, Mauro Da Lio, Gastone Pietro Rosati Papini, and Riccardo Dona
- 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 - 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.
- Published
- 2020