Affiliations: [a] School of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou, Gansu, China | [b] School of Computer and Communication, Lanzhou University of Technology, Lanzhou, Gansu, China
Correspondence:
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Corresponding author: Xijun Zhang, School of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou, Gansu, China. Tel.: +86 15593106088; Fax: +86 0931 2976016; E-mail:zhangxijun198079@sina.com
Abstract: At present, our country is facing the problems of
resource shortage, such as the air pollution, the traffic congestion and the
population aging, which have seriously affected the sustainable development
of the city. Human movement and the movement of vehicles are reflecting the
changes of urban environment. The analysis of moving objects historical
trajectory big data is the necessary means to build a smart city. Due to the
Global Positioning System (GPS) data recording the taxi's and the bus's
driving time and location, the GPS-equipped taxi can be regarded as the
detector of an urban transport system. The data acquisition in the traffic
system is a geometric trend growth, so it is urgent to build a platform that
can handle big data processing. The GPS trajectory big data has the
characteristic of strong real-time and great changes. The use of big data
cloud platform data storage can greatly reduce the cost of data storage, and
at the same time improve the security of data storage. This paper deeply
analyses the application requirements of the intelligent traffic trajectory
big data processing platform and studies the mining method to do with the
GPS trajectory big data. Through the simulation we can grasp the
distribution characteristic of GPS trajectory big data.
Keywords: Trajectory big data, smart city, intelligent traffic, data mining
