  Agent technology is a software paradigm that permits to implement large and
complex distributed applications. In order to assist the development of
multi-agent systems, agent-oriented methodologies (AOM) have been created in
the last years to support modeling more and more complex applications in many
different domains. By defining in a non-ambiguous way concepts used in a
specific domain, Meta modeling may represent a step towards such
interoperability. In the Transport domain, this paper propose an agent-oriented
meta-model that provides rigorous concepts for conducting transportation system
problem modeling. The aim is to allow analysts to produce a transportation
system model that precisely captures the knowledge of an organization so that
an agent-oriented requirements specification of the system-to-be and its
operational corporate environment can be derived from it. To this end, we
extend and adapt an existing meta-model, Extended Gaia, to build a meta-model
and an adequate model for transportation problems. Our new agent-oriented
meta-model aims to allow the analyst to model and specify any transportation
system as a multi-agent system. Based on the proposed meta-model, we proposes
an approach for modeling and evaluating the Transportation System based on
Stochastic Activity Network (SAN) components. The proposed process is based on
seven steps from Recognition phase to Quantitative Analysis phase. These
analyzes are based on the Dependability models which are built using the
formalism Stochastic Activity Network. A real case study of Urban Public
Transportation System has been conducted to show the benefits of the approach.
