Big data technology is the foundation of promoting intelligent transportation!

but also is it the precondition of the intelligent transportation to obtain traffic big data accurately and timely and build traffic data processing model, and such problem can be solved through big data technology!

Solutions for Traffic Industry

With the acceleration of China's urbanization development, urban traffic congestion and traffic pollution are increasingly severe, and traffic accidents occur frequently, which is the problem needs to be solved in major cities. As is known to all, intelligent transportation becomes the key strategy to improve urban traffic. Therefore, it is a prerequisite for building intelligent transportation to obtain traffic big data and construct traffic data processing model in a timely and accurate way, which can be solved through big data technology.
1.1Current Status of Industry

The development of intelligent transportation technology in China dates from the 1990s when PRC Ministry of Communications has further defined development goals of the future intelligent transportation in the 12th five-year plan, pointing out to focus on research and application of new technologies such as perceptual recognition, network transmission and intelligent processing and data mining, etc. The 13th five-year plan shows that rail traffic in China will play an important role of urban traffic function in Chinese comprehensive transportation system and new-type urbanization construction, play dual roles of both supporting improvement of structure adjustment and leading inter-city communication, and become the most important development field of urban traffic.

The new type of urbanization in China will need to form the rail traffic system among or within cities of urban agglomeration, and the environment of transportation will be further improved. China will launch 10 major projects, including high speed railway, highway, “four-edge” channel, civil airport, port and shipping facilities, urban agglomeration traffic, urban transport, rural transportation, transportation hubs, intelligent transportation, etc., and modernization paces of Chinese transportation will be further accelerated.

The use of modern advanced technology, such as big data, is in the purpose to improve the development level, quality and management as well as service level of the whole transportation system, and realize increases of capability-supplying and improvement of safety protection, economy and environmental protection, etc. Moreover, the value of big data applicable under the normal operation of subway network and large passenger flow has become more and more important in aspects of subway safety, efficient operation and passenger service.

1.2Current Problems

1. Mass Data

In every moment, the rail traffic system produces large amounts of data coming from breakdown maintenance system, real-time monitoring and control system, project implementation progress, supplies and materials statistics system, etc., and the data growth speed becomes faster and faster, is the data garbage or value? How to improve the efficiency of subway operation to ensure timely monitoring of project delivery.

2. Data Cognition

Available in most of traditional systems, breakdown maintenance system, real-time monitoring and control system, supplies and materials statistics system, the simple analytic statistics charts are in sole data format, with poor flexibility and low interactivity, so that managers hardly make proper cognition of data.

3.Management Decision

The roles of big data under the normal operation of subway network and large passenger flow has become more and more important in aspects of subway safety, efficient operation and passenger service, which can help to quickly extract key data from the underlying data to drive operation direction by data and provide scientific support for decision-making.


2.1Overall Architecture Diagram

·The Overall Architecture Diagram is as follows:


The whole system covers 4 layers:

1. Data layer: integrate various information systems of traffic industry and break information isolated islands to realize data sharing.

2. Modeling layer: set up different analysis topic marts according to concerns about indicators in aspects of data decision-making, sales, and operations

3. Business layer: tease out indicators of traffic industry and push the analysis results to the display layer.

Around the aspect of passenger flow volume, monitor passenger flow volume of each traffic line and station, reasonably regulate flow volume through flow prediction mechanism, and improve load of passenger flow while effectively guaranteeing traffic safety.

Analysis of health degree of train operation. To monitor the train information/train driving indicators: analyze and display advancing direction, parking condition, on-schedule rate and error of time when arrival at and departure from each station, etc.

Around the aspect of fault, real-time online monitoring of faulty line, station, systems and equipment numbers to ensure timely reporting failure. At the same time, KPI statistical analysis is made on the efficiency of fault processing, e.g.: the working hours and the per capita time for trouble-shooting, etc., to improve ability of quick failure response.

Around the aspect of material consumption, data analysis is carried out from the views of material consumption in rail traffic, etc., to provide data strategy support for material inventory management and procurement management.

Risk management around progress, progress management on various projects under construction and statistics of implementation time of each project section, ratio of problem phase should be made, to provide the basis for reasonably arranging project resources.


4. Display layer: in rich and perfect charts, by flexible method of interaction, analysis results are presented to all administrative staff playing various roles .



3.1Value of Yonghong

1. Basing on rail traffic data analysis platform provided by Yonghong, the decision-makers and management may have insight into the operational state of rail traffic.

2. Yonghong helps users to easily cope with the rapidly growing data of e-commerce platform and realize a second response to the calculation and presentation of any business on the basis of specific data.

3.All operating departments can carry out partial self-service analysis so as to meet their demand for real-time exploration and analysis.

4. Capability to quickly respond to new analysis needs and changes, so as to improve work efficiency.

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