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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
