BASTA: BDI-based architecture of simulated traffic agents

Abstract

It is expected that connected and autonomous vehicles (CAVs) will soon become a regular means of transportation. To fully leverage the potential of this new technology, it is necessary to equip such cars with efficient algorithms permitting them to drive in a safe and optimal manner. Thereby we aim to design and implement tools for convenient evaluation of strategies for driving and interactions in various settings. In this paper, we present the results of the first stage of our bigger research program on a simulation framework of CAVs. A search for a balance between complexity and comprehensibility of the solution led us to the field of multiagent systems. Beliefs-Desires-Intentions (BDI) systems offer useful abstractions for activities of a single self-driving car and collective intelligence of such vehicles. Indeed, the BDI framework helps to combine two distinct natures of a self-driving car: its reactiveness and proactiveness. Moreover, the modularity of the resulting architectures for an individual CAV and urban traffic induced by these cars makes the design intelligible and flexible. Our prototype verifies the feasibility of this concept.

Keywords

• bdi model
• connected and autonomous vehicles
• agent architecture
• multiagent simulation
• traffic simulation