A multi-agent approach to Intelligent Transportation Systems modeling with combinatorial auctions

Challenges of urbanization require new, more flexible approaches to design of public transportation systems. Demand Responsive Transport systems (DRT) that provide a share transportation services with flexible routes and focus on optimizing of economic and environmental value are becoming an important part of public transportation. In this paper we propose a new approach to design of DRT models which considers DRT as a multi-agent system (MAS) where various autonomous agents represent interests of system’s stakeholders. The distributed nature of the MAS facilitates design of scalable implementations in modern cloud environments. We also propose a planning algorithm based on combinatorial auctions (CA) that allows to express commodity of multiple transportation scenarios by evident means of the bids. Using the mechanism of CA we may fully take into account the presence of complementariness and substitutability among the items that differ across bidders. Further, we describe design principles of our proposed software with a prototype implementation. We believe that our approach to multi-agent modeling is general enough to provide the flexibility necessary for adoption of DRT-services modeling into real-world scenarios. The results of modeling have been compared against several cases of a local bus provider and validated in a set of computational experiments.