An Investigation on ATS from the Perspective of Complex Systems

Abstract

Artificial transportation systems (ATS) has been related to the study of complex systems and traffic simulation since its birth. Its relationship with complex systems and its connections, as well as differences from traditional traffic simulation systems pose an interesting problem. In this paper, according to two hypotheses about complex systems, we inferred three principles: synthesis, experimentation, and constant experimentation. We explored ATS from the perspective of complex systems, along with a diagram depicting the relationship between ATS-related concepts and methods. We then used the reasoning behind deploying agent-based modeling to explain why the principle of simple objects and relationships can be effective in ATS. We examined these principles from a complex adaptive systems perspective. Finally, essential differences between ATS and traditional traffic simulation systems are reported.