Car-driving assistance using organization measurement of reactive multi-agent system
Year: 2010
Type: conference-paper
Abstract: This work presents an approach to the obstacle avoidance problem, applicable in the frame of driver assistance. A decision, expressed as a proposed acceleration vector for the vehicle, is elaborated from the evaluation of a set of indicators characterizing the global state of a system of reactive agents (RMAS). Those agents evolve in a virtual environment produced on the base of vehicle’s perceptions of the material environment around it. Agent-to-agent and agent-to-environment interactions are defined in order to produce a distribution of agents over the virtual environment. This distribution, taken as the global state of the system, is analyzed by applying a set of indicators inspired from statistical physics, to calculate a new vehicle’s acceleration vector. This work presents the details of the RMAS model and its interaction laws, together with the global state evaluation functions. The approach has been applied to experimentation with a laboratory vehicle. Some experimental results are presented here.
Source: Procedia Computer Science
Institution: Université de technologie de belfort-montbéliard
Language: English
Subfield: Automotive Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W2005363153