We present multi-agent timed models, called MAPTs, where each agent is associated with a regular timed schema upon which all possible actions of the agent rely. MAPTs allow for 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 then use an available tool for the Petri net implementation of MAPTs, to explore the state space of autonomous vehicle systems and compare this exploration with timed automata-based approaches in terms of ex- pressiveness of available queries and computation time.