How big data applications each captured Intelligent Transportation

How big data applications each captured Intelligent Transportation

2014-07-07 11:03:38 Source: Zhongguancun Online

In recent years, the domestic large and medium cities have started or was planning to project construction and transport large data-related, such as urban transit, urban traffic data centers, intelligent traffic, traffic operations coordination and command centers, launched a large number of projects for big data technology demand is also increasing. Industry for the popularization of large data technology began in 2011, after three years of development, big data technology has been firmly established in the field of intelligent transportation.

Pok Intelligence: Five-platform applications to solve difficult technical applications

Big data applications in the field of intelligent transportation problems are mainly concentrated in the face of diversity, a closed operating environment, traffic data collection management, quality assurance, and rapid application of the above data. Application of intelligent transportation management platform for big data will effectively address these issues. Intelligent Transportation Big Data platform mainly includes five areas: urban traffic information data systems, urban transport integrated monitoring and early warning systems, urban traffic monitoring system for carbon emissions, urban public transportation management systems, public travel information service system.

Urban traffic information data system is based on large data applications technology industry information sharing traffic exchange center, after the establishment of the data center, will become the hub of the city traffic information.

Integrated urban traffic monitoring and early warning systems can be achieved on the entire urban traffic conditions in real time. Traffic management department of a large area can be traffic gridlock may occur in urban traffic to effectively predict. Meanwhile, the system can also guide the public to travel, to provide comprehensive and timely travel information to the public, to really travel requirements of green transport.

Urban transport carbon emissions is a real-time monitoring system of carbon emission monitoring system that can achieve real-time monitoring of the city. In the period of time a vehicle carbon emissions, at a glance. In order to improve urban air environment, governance, provide data to support vehicle emissions.

Urban public transport management systems including monitoring, monitoring of transit corridors, transit safety monitoring and evaluation system, and the effectiveness of the passenger area of ​​investment analysis. Application of the system to help improve operational efficiency within the city buses. Traffic management department can adjust bus capacity, traffic, transit rational allocation of resources to make bus travel more convenient and smooth.

Public travel information service system of traffic information publishing platform. Government and relevant authorities can, in many forms of media to disseminate information through the system. People rely on this information to adjust their travel paths and ways to avoid congested roads, more quickly reach their destinations, and effectively saving time and resources, effectively increasing the service levels of urban traffic.

Tencent Map: digging behind the law disorderly conduct traffic

Users travel data, has become the cornerstone of a variety of intelligent transportation services. More common is the real-time traffic and traffic forecasts, many cities already provide such services.

In real-time traffic data basis, through certain mathematical model that can predict traffic specific time period, a particular region. Before the Dragon Boat Festival this year, we performed simulations based on existing data and operations, the Dragon Boat Festival congestion prediction made, the results have come out and the final match was a high degree of occurrence probably be able to fit into the 70-80%. This suggests that by accumulating and analyzing existing data, the reference to the public daily traffic, divert traffic management department in advance, have a great significance.

In fact, the value of these data is also worth digging. Massive user traffic behavior and choice of data through detailed analysis, you can generate greater value in various segments.

After 1,800 users of our driving behavior analysis found that on average, each traffic violation, are generally accompanied by seven speeding, brakes five times, four times acceleration or sharp turn. This is where the data can reflect many issues. Such as speeding, is not particularly prone to some sections speeding? This may reflect road design flaws. In addition, it can reflect the user's driving behavior does have impropriety. With this assessment, we can optimize the network, proper guidance and education of users driving behavior, so that the entire traffic safety and efficiency are very significant improvement.

There are a lot of urban transport traffic data, urban roads, highways, parking lots, subways and buses have a lot of camera data, card data transit subway, taxi taxi data, maps, navigation data, parking information data.

These are very valuable data, but most are in a deep sleep state. If the real-time congestion information released to the subway upcoming metro man, a lot of people's travel behavior will change. These people can go to work a little earlier or a little later work, he would make choices. In addition, the frequent occurrence of a massive traffic jam on the highway, especially in the face of winter fog, icing and other unexpected weather, traffic jam may be stretching several kilometers on the highway. If at this time the highway Camera can capture this information in a timely manner by the appropriate platform released to the owners, the owners will be able to adjust their travel times and routes. If the information is sufficiently transparent, timely, and this time the passengers will have another kind of orderly traffic behavior.

These valuable data currently scattered in different administrative departments and enterprises, and fragmentation, was "tight" protected. Evolving in the future, these data should be like water, electric, as there is a good market-oriented pricing mechanism and the appropriate security protection mode, in the corresponding business model, generate the majority of social benefits.

ZTE: the planning of bus lines, "according to" Ke Yi

With the deepening development of mobile Internet technology, the application of big data technology will greatly enhance the distribution of transit passenger traffic forecast accuracy and make public transport capacity, volume configuration is more efficient, more rational planning of bus lines.

Passenger traffic starting and ending point survey (also known as passenger OD survey) is the distribution of transit traffic and traffic forecasts on the basis of the investigation. OD survey current urban passenger travel survey residents to get through, according to the source data to obtain conventional means of investigation include: resident questionnaire, investigators lorry observation survey, bus card statistical method.

These methods require people to actively cooperate with the investigation, there are limitations of survey instruments, not fully, accurately grasp the travel needs of the city's residents. If the survey (questionnaire and survey vehicle) can only be done manually sample survey, the validity of the information, timeliness there are deviations, does not reflect the travel needs of the public. Passengers who use public transportation IC card automatic counting statistics only way to drive behavior is actually happening, the passenger does not reflect the true wishes of the trip. By applying Big Data technology can be effective in changing this situation.

Our current mobile phone penetration rate is relatively high, most of the city has reached more than 80%. The big advantage of mobile signaling data mining techniques to obtain timely data flow of people, the flow direction and the dwell time statistics to realize the bus passenger comprehensive and accurate grasp of basic data can be used as the city's comprehensive transportation system planning and evaluation, and reduce urban passenger OD survey of human and material resources, a substantial increase in accuracy.

Large data on mobile communications signaling data mining, you can easily get the information you need OD survey, based on the historical distribution of the flow of people and traffic movement law planning bus lines, dense point set in high traffic bus stops.

Big data applications, not only can improve the accuracy of transit traffic survey, for the design and planning of bus lines also plays a vital role.