Big Data Technology Applied in Intelligent Transportation

The age of big data has begun, which brings both opportunities and challenges for urban transportation. This is a great issue to work out the way of coping with or taking advantage of it. Urban transportation that functions as a mainstay is fundamental in traditional transportation. Four words starting with letter “V” are used to describe the age of big data, and they are Velocity, Variety, Volume, and Value. In the age of big data, urban transportation, and big data are inevitably related to each other. Technology breakthroughs based on big data are promoting urban transportation into the all-around information age while fast development of urban transportation improves big data’s utility. Therefore, integrated effective urban transportation big data and mining applications in future will play an important role in developing modern rails. It is required that any traditional industry who have demanded big data should know technology and deeply understand the facts. Those who can master big data in an industry should own more knowledge than others about economics, telecommunications, and transportation. Besides, they should thoroughly investigate passengers’ actual demand and comprehensively understand the peaks.

The changes, merits, and demerits that the age of big data brings to intelligent transportation Now people have unconsciously entered into an age of “big data” due to the rapid growth of network information technology and relevant matching technologies. At present, the “big data” has not been given an infinite and authoritative definition internationally; however, each country holds similar views on its basic knowledge. Some researchers argue that “big data” is a large amount of data with strong effects on briefly predicting as to its application fields. In addition, some researchers claim that “big data” is a large data set, which is extraordinarily complicated as well. Whatever, we have to accept the fact that the age of big data has approached and to make full use of its applications in each field. Therefore applying big data technology is an inevitable choice in the current intelligent transportation field, as a result of the great changes it can bring to modern intelligent transportation.

The ways in which big data changes traditional public transportation

Big data can overcome the limitations by administrative regions. The government divides the country into different administrative regions in order to efficiently rule and manage it. The division can help facilitate local autonomy of each region. Meanwhile, it promotes the local governments to integrate all the transportation data that probably be utilized into the system, as they expect to acquire maximum benefits in their own region. Besides, integrated public transportation information utility models are constructed to function as an overall transportation. The governments also handle real-time traffic barriers by applying aggregated search, utilization and analysis from big data to acquire relevant information and to meet various transport demands.

The advantages of intelligent transportation under big data

Generally, intelligent transportation processing system consists of transportation data input (static and dynamic data), data processing (real-time data processing), data storage (big data), data checking, searching or planning and users. Big data can well allocate public transportation information sources. Traditional transportation departments with obscure responsibility divisions are wasting a large amount of manpower and materials since refined specialization caused overlapping functions among these departments. Moreover, big data helps to work out fine coherence and coordination solutions, to reasonably allocate transportation functions among the departments and information resources according to relevant traffic issues. Big data has advantages of handling public transportation problems as follows. 1. In the process of allocating vehicles in public transportation, the costs will become fewer with the integration of big data. The allocation with high efficiency can increase vehicles’ valid road mileages so that it can improve transportation efficiency. It will immediately find out useful information and ensure the coherence and sustainability of the transportation once problems occur on certain roads. 3. Based on good predicting ability, it can reduce the possibility of misinformation or omission and can carry out real-time monitoring on dynamic public transportation. A certain amount of money will be spent on purchasing super computers and the maintenance for processing big data under intelligent transportation management; however, it will bring larger economic benefits in the long term, which can reduce traffic jams. It analyzes the users and converts to a complete map of traffic with operating conditions of each road indicated in same colors. In this way, it verifies the location of traffic jam and applies big data to process road conditions under bad weather. Besides, according to information from the weather station and high-speed transportation statistics, it estimates the time for cleaning up critical paths and thus improve the efficiency of handling road conditions. The big data can be applied to estimate the road conditions, which evaluates the driving reliability of critical paths based on high-speed transportation statistics and analysis. In addition, it can verify the position of crowded paths and guide drivers there to dredged paths.

Difficulties that intelligent transportation has under big data

According to statistics by relevant departments, the amount of information generated during three years now equals to that during forty thousand years in last age due to the internet information age’s arrival. What’s more, the amount of information will keep increasing with the development of the age. There is no doubt that a large amount of information and statistics have emerged, which origin from various aspects. These aspects include Internet e-business shopping in daily life, manufacturing of each production line in industrial enterprises, communications of medium information in social networks, and online videos that are affecting materials’ production and transmission. With the development of this age, a large amount of information and statistics are generated from automatic information management systems of industrial enterprises, electronic window administration of service departments such as government agencies, and Internet information entertainments or services used by citizens. Modern transportation fields are also no exception. Currently, the information and statistics such as floating car data and those of intelligent transportation card are distributed in each region. As to GPS data of floating cars, it is estimated that the tracks’ real-time records can generate data with an average length of 50~200 B based on only 20,000 units of CPU. For instance, if one car’s return frequency is 15 to 60s each time, this data will produce 4.75 GB every day and 1.75TB annually (Kitchin, 13). There will exist extremely complicated relations in the entire data system if a variety of data flows such as the videos, images, audios are involved. Besides, the correlative relationships change dynamically and uncertainty, and consequently, the data correlation models are becoming too complex to deal with.

Disadvantages of intelligent transportation under big data

Big data is expanding in its surroundings, and speeding up information transmission as well as sharing, in which the business or private information might be divulged without strict control, including one’s location, personal travel habits or the users’ favorite major routes. Once one is aware that this private information is divulged, he will reject the wide applications of big data management systems. In addition, a lot of vehicles calculating traffic data is stored in static formats, although the transportation data of each local agency is available for big data management system. Therefore, the system’s counting features can hardly be searched except by people. This traditional “people-to-things” internet connection does not conform to the feature “things-to-things” of the Internet of Things. Transportation data connected by things ceaselessly accumulates, communicates and processes mobile data such as traffic and weather conditions through hardware including smartphones, sensors, and airborne vehicles.

Modern intelligent transportation has been an essential part in urban construction along with changes in the age and social demand. Meanwhile a large amount of information and data is supposed to be processed effectively, quickly and safely, as the information age has begun. The main aim of constructing intelligent transportation in the age of big data is to elevate the level of urban transportation development and management. Big data processing technologies such as cloud computation should be applied in the applications of intelligent transportation from present to future, whereas platforms for mass information need to be established to apply the technology. The problems of mass information explosion can be solved only if the platforms can be fully used. In conclusion, in order to accomplish the construction of mass information platforms and maintain sustainable development, it is necessary to start from verifying the system framework, data transferring scheme, data storage scheme and data processing scheme, and further construct an intelligent transportation system with intelligence, safety, low costs and high efficiency and convenience.

Conclusion

There’s a famous joke that big data is like teenage sex that everyone talks about is claiming they know about it, but rarely few people have actually performed it. Aside from the laughter, it’s true that we are still at a very early age of mastering the massive data and the usage behind it. It is also quite true to the state of the application from Big Data on public transportation. It’s amazing what people are doing to the HongKong transportation industry that satisfies the need of the large population with so many narrow streets, and it wouldn’t be surprising to see some revolutionary change in HongKong.