We formalise and study multi-agent timed models MAPTs (Multi-Agent with Periodic timed Tasks), where each agent is associated with a regular timed schema upon which all possible actions of the agent rely. MAPTs allow for an accelerated semantics and a layered structure of the state space, so that it is possible to explore the latter dynamically and use heuristics to greatly reduce the computation time needed to address reachability problems.

We use an available tool for the Petri net implementation of MAPTs, to explore the state space of autonomous vehicle systems. Then, we compare this exploration with timed automata-based approaches in terms of expressiveness of available queries and computation time.