چکیده:
As a new paradigm in information technology, the Internet of Things (IoT) is attracting increasing attention from various industrial sectors. It can be predicted that IoT applications in public transportation systems will become widespread and bring changes to these systems in the near future. In this article, we analyze the impact of the IoT environment on public transportation systems, propose a new framework for an intelligent public transportation system based on IoT, and provide a detailed presentation of the deployment of elements, communication networks, and the three-layer architecture of the system. We also present the information flow, technical design, optimization model, and the algorithm of the main modules for the dynamic optimization of the system. The innovative points of this article are as follows: (1) A new framework for an IoT-based public transportation system, which integrates the planning problems of metro, bus, and shared taxis, is proposed for better coordinated transit solutions. (2) Traffic flow prediction methods based on periodic data mining patterns are proposed for road flow analysis and passenger flow analysis. (3) A mathematical model and a DSS-based evolutionary computation algorithm are proposed to solve dynamic scheduling and control problems. The proposed IoT-based intelligent transportation system can help decision-makers increase the utilization of transportation resources, improve planning efficiency, and reduce passenger travel time.
خلاصه ماشینی:
In this article, we analyze the impact of the IoT environment on public transportation systems, propose a new framework for an intelligent public transportation system based on IoT, and provide a detailed presentation of the deployment of elements, communication network, and the three-layer architecture of the system.
The innovative points of this article are as follows: (1) A new framework for an IoT-based public transportation system, which integrates the scheduling problems of metro, bus, and shared taxis, is proposed for better coordinated transit solutions.
For example, many uncontrollable events or changes such as extreme weather, fluctuations in passenger flow, vehicle breakdowns, and dynamic changes in traffic conditions may cause discrepancies and problems in controlling and managing the system process, leading to the failure of pre-determined scheduling plans and resource allocation programs.
Zhang and Chen proposed an IoT-based real-time dissemination system regarding the congestion index in public transportation, and their system can be used to evaluate the congestion status of public vehicles based on wireless sensor network nodes, sink nodes, and terminal analysis modules [9].
The control and planning center receives data from the taxi, bus, and shared metro subsystems, obtains information from passengers or potential users for further analysis of origin-destination travel flow, provides coordinated solutions, and sends instructions to the vehicles.
Dynamic Scheduling and Control System In the proposed Internet of Things (IoT) based public transportation system framework, the implementation of dynamic vehicle planning and control is its core.
Real-time public transportation system information collected by IoT devices, including passenger waiting queues at stops, vehicle GPS tracking, traffic light status, and vehicle density on roads, etc.
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