Unsupervised learning-based real-time public transportation dynamic scheduling method under cloud platform environment

Abstract

The invention discloses an unsupervised learning-based real-time public transportation dynamic scheduling method under a cloud platform environment. The method includes the following steps that: an intelligent public transportation integrated terminal or a public transportation cloud service scheduling system acquires vehicle positioning data according to the current position information of vehicle positioning; the intelligent public transportation integrated terminal or the public transportation cloud service scheduling system communicates with a data center; the public transportation cloud service scheduling system receives operating scheduling instructions of the data center, and the operating scheduling instructions are displayed at a vehicle-mounted driver information display screen; and notification information issued by the data center is received, and is transmitted to the intelligent public transportation integrated terminal, and the notification information, charging information are system fault information are displayed so as to be checked by a driver. The method can be constructed on a high-availability cloud calculation platform, so that the calculation platform can have online computing expansibility, high resource utility ratio and stable operation performance, and can be efficient, flexible, environmentally friendly and universal.

Description

technical field [0001] The invention relates to the field of public transport real-time dynamic public transport dispatching, in particular to a real-time public transport dynamic dispatching method for unsupervised learning in a cloud platform environment. Background technique [0002] With the rapid development of cloud computing, Internet of Things and communication technologies, the integration of intelligent bus dispatching and new technologies has entered a new stage. The intelligent transportation system based on information distributed processing and storage and automobile mobile Internet of Things will realize real-time, accurate and efficient comprehensive transportation management on a large scale, and can effectively alleviate traffic congestion, reduce energy consumption, and reduce environmental pollution. Intelligent public transportation products and applications based on cloud computing technology will gradually enter the lives of ordinary people in the futu...

AI Technical Summary

Problems solved by technology

[0003] Compared with traditional server technology, it is necessary to build a relatively independent processing platform in the face of massive real-time bus information processing, such as real-time bus-oriented data acquisition and processing, user-oriented information service processing, and decision-oriented data statistics and processing etc., due to the different nature of data format and algorithm processing, it is difficult to achieve integration on the same architecture, and the isolation of data and applications cannot be achieved in terms of network integrity, making it difficult for the platform to achieve an effective balance in terms of utility ratio and security