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How to solve the modern traffic dilemma with the help of big data, I believe that many inexperienced people are at a loss about it. Therefore, this paper summarizes the causes and solutions of the problem. Through this article, I hope you can solve this problem.

With the increasing traffic "big data", the new challenges to the innovation of traffic management and the new requirements for traffic management, the construction of traffic informatization is bound to enter the intelligent application stage brought by big data. Using big data to solve many current traffic bottlenecks has become the only way for the transportation industry in the future. So how does big data solve the difficulties faced by the transportation industry? This is what this article focuses on.

Background

The problem of urban traffic has been perplexed by the industrial developed countries since the last century. Since China entered the reform and opening up, the construction process of various undertakings has been accelerated rapidly. With the development of economy, the traffic in our country has changed greatly. The industry is also facing challenges. According to incomplete statistics, the number of motor vehicles in the country has reached 285 million, and there are 56 cities with an urban traffic congestion index of more than 1.5. among them, 1/3 of the urban congestion index is on the rise. the normal rate of civil aviation flights is less than 70%, and traffic difficulties have become a livelihood issue that has been paid close attention to by the general public and government leaders. Since the 13th five-year Plan, with the development and application of cloud computing, Internet of things, big data and other advanced technology, relying on big data and other advanced technology to solve increasingly urgent traffic problems has become the focus of government and social institutions.

The "sleepiness" of Modern Traffic

If you want to understand the difficulties faced by traffic, you must understand the overall ecology of traffic, understand what data is available and what can be done with it.

As shown in the picture, the core of transportation is man-car-road, while the core involves many departments and related to many industries and fields, which is a comprehensive system science. At present, there are several main problems hindering the application of big data in traffic.

1. It is said that because across a number of government departments and enterprises and institutions, the information level of different units and departments is uneven, so the isolated island of information is still widespread in the field of transportation.

two。 Due to the influence of historical evolution and the closure of technological renewal channels and other factors, there is a lack of effective means of data collection in the face of more and more diversified data.

3. With the in-depth application of Internet of things technology in the field of transportation, massive equipment / sensor information has been recorded, but due to cost, concept, security and many other reasons, this part of the data is lack of effective storage media.

4. In addition to the characteristics of many departments, many formats and a large amount of data, there is also a problem that when massive and diversified traffic data are concentrated, there is a lack of effective control and transportation.

5. * is also the most important difficulty. At present, the ways and methods of data analysis in the industry are still relatively simple, statistical reports and integrated command demonstration systems are widely used, and everyone's analysis and application methods are still focused on post-processing. However, there is a lack of effective means and methods for prevention and monitoring in advance.

Big data's "Wisdom"

In the face of many problems, the traditional management and disposal methods, which are based on experience, immutable and separated from theory and practice, are obviously unable to cope with, and with the continuous advance of the degree of traffic modernization, massive traffic-related data are recorded and stored to form "Traffic big data", and how to make full use of "Traffic big data" to solve practical traffic problems has become a challenge and opportunity for the transportation industry. What was the traffic big data in Internet + 's time? What problems can they help us solve? So let's meet "Traffic big data" first.

Road traffic: typical data are urban road traffic index, elevated ramp operation data, bus real-time data, operating vehicle data, logistics vehicle and cargo data, etc., its main application value is reflected in congestion control, road network planning, travel guidance, intelligent public transportation, real-time road conditions, vehicle monitoring, crisis protection and so on.

Rail transit: typical data are subway operation data, rail transit operation data, all-in-one card passenger card data, liquidation data, etc., its main application value is reflected in passenger flow analysis, station analysis, policy-assisted decision-making, command and dispatching, anomaly detection, advertising, equipment monitoring and early warning, etc.

Urban static traffic: typical data are parking data, road network information, vehicle ownership information, urban basic geographic information, traffic management information, meteorological information and so on. Its main application value is reflected in congestion control, traffic infrastructure planning and construction, travel guidance, parking guidance, traffic management optimization and so on.

Air / shipping: typical data are port container data, airport flight data, ocean and inland waterway ship data, route information, meteorological data, regulatory data, etc., its main application value is reflected in route planning, capacity matching, stowage optimization, intelligent ship, cargo tracking, emergency early warning, etc.

Traffic derivative information: typical data are road accident data, vehicle violation information, traffic monitoring information, traffic control information, etc., its main application value is reflected in public security protection, emergency disposal, traffic management, criminal investigation analysis, cooperative command, value-added information sharing and so on.

Similarly, through the integration of Shanghai data and the methods of big data mining and modeling, we can effectively realize the self-optimizing ecological closed loop of prevention in advance, supervision in the event, evaluation after the event, and solve the dilemma faced by traffic with the help of the wisdom brought by big data.

How to solve the difficulties in traffic operation with the help of big data

Since the traffic big data contains rich value and has a broad application imagination space, how to apply it in practice? Lenovo has been committed to solving the actual society and promoting the development of the whole industry through the exploration and application of new technologies and new models. Big data, as a new technology, how to apply it in the old field and give full play to its advantages is the main object that Lenovo has been trying to study.

As shown in the figure, the massive data storage and computing problems faced by big data are solved through the distributed storage (hdfs) and high-performance computing provided by big data; with the help of software tools and consulting services, assist enterprises and institutions in the transportation industry to control and manage the massive data Rely on professional data scientists to carry out relevant analysis and application based on traffic big data to restore the real value of traffic big data.

As shown in the figure, massive traffic information is identified and recorded through the perception layer, and then the information is centralized to the big data analysis platform for storage and calculation through the network layer with the help of the Internet of things, Internet, communication network and other technologies. * big data is analyzed and applied through the business application layer, and through mobile devices, APP, vehicle devices. Traffic control equipment and other channels and means apply the "wisdom" generated by traffic big data to the actual traffic operation, and then feedback the operation data back to big data analysis platform to further optimize big data-related applications, forming a continuously optimized closed-loop of traffic big data value.

The massive traffic big data not only covers all traffic-related fields, but also the value generated by centralizing these data is inestimable. It is estimated that the market size of Traffic big data will exceed 20 billion in 2020. With the maturity of new business models (data operation, data realization, etc.) and the continuous investment of enterprises such as Lenovo, Yi Hualu, Softong, etc., in the future, Traffic big data will bring us a new way of traffic management and travel.

Relying on big data as the core, the overall solution of the transportation industry will be data-driven, big data technology platform as the carrier, constantly tap data value internally through scientific data analysis methods, optimize management decisions, and constantly improve service quality externally to solve traffic problems.

In the future, we will discuss big data's wisdom in solving traffic dilemmas from the aspects of data perception, technology platform, business application and so on.

After reading the above, have you mastered the method of how to solve the modern traffic dilemma with the help of big data? If you want to learn more skills or want to know more about it, you are welcome to follow the industry information channel, thank you for reading!

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