Parallel Control and Management for Intelligent Transportation Systems: Concepts, Architectures, and Applications

TLDR

Parallel control and management is a data‑driven approach for modeling, analysis, and decision‑making in complex systems, especially transportation, that addresses both engineering and social complexity. The paper provides an overview of the background, concepts, basic methods, major issues, and current applications of Parallel transportation Management Systems (PtMS). PtMS comprises system architectures, processes, and components such as OTSt, Dyna CAS, aDAPTS, iTOP, and TransWorld, and the paper discusses their basic methods and major issues. The paper demonstrates that PtMS is effective in networked complex traffic systems, aligns with emerging cloud, social, and cyber‑physical‑social technologies, and presents experiments and real‑world application examples.

Abstract

Parallel control and management have been proposed as a new mechanism for conducting operations of complex systems, especially those that involved complexity issues of both engineering and social dimensions, such as transportation systems. This paper presents an overview of the background, concepts, basic methods, major issues, and current applications of Parallel transportation Management Systems (PtMS). In essence, parallel control and management is a data-driven approach for modeling, analysis, and decision-making that considers both the engineering and social complexity in its processes. The developments and applications described here clearly indicate that PtMS is effective for use in networked complex traffic systems and is closely related to emerging technologies in cloud computing, social computing, and cyberphysical-social systems. A description of PtMS system architectures, processes, and components, including OTSt, Dyna CAS, aDAPTS, iTOP, and TransWorld is presented and discussed. Finally, the experiments and examples of real-world applications are illustrated and analyzed.