An Adaptive System Architecture for Multimodal Intelligent Transportation Systems
CoRR(2024)
摘要
Multimodal intelligent transportation systems (M-ITS) encompass a range of
transportation services that utilise various modes of transport and incorporate
intelligent technologies for enhanced efficiency and user experience. There are
several challenges in M-ITS including data integration, Interoperability,
scalability, user experience, etc. To address these challenges, such a system
requires an adaptive system architecture that enables M-ITS to operate as an
integrated ecosystem. In this paper, we provide an adaptive, user-centric, and
layered architecture for multimodal transportation systems. The proposed
architecture ensures scalability for seamless interactions of various
subcomponents, that are often managed by different stakeholders. Concurrently,
the data architecture is detailed, covering diverse data sources, advanced
analytics, and stringent governance, providing a robust basis for intelligent
decision-making. We provide two example use cases of the proposed architecture,
showing how the data architecture and the system architecture can be fused and
serve multimodal intelligent transport services.
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