International Journal of New Developments in Engineering and Society, 2017, 1(2); doi: 10.25236/IJNDES.17201.
Liaoning Police College, Dalian, 116036, China
With the increase of population pressure in modern society, the problem of traffic congestion becomes more and more serious. Traffic guidance model is one of the main means to alleviate traffic problems. This paper analyzes basic functions the city traffic guidance model should have, including real-time monitoring, intelligent control and accurate prediction, and gives a method of model construction of city traffic guidance based on big data mining to provide some references for the relative researchers.
Guidance Model; Urban Transportation; Big Data Mining Technology
Liuren Wang. Research on Guidance Model of Urban Transportation Based on Big Data Mining Technology. International Journal of New Developments in Engineering and Society (2017) Vol.1, Num.2: 1-3.
Xu Jie, Zhang Xin, Guo Jianyuan and Du Tingting, Research on Passenger Guidance System of Urban Rail Transit Network Based on Timetable of Last Train, China Railway Science. Beijing, 2014, 35(2): 111-119.
Sun Zhiyuan, Lu Huapu, Zhang Xiaoli and Qu Wencong, Bi-level programming model for cooperation of urban traffic control and traffic flow guidance, Journal of Southeast University (Natural Science Edition). Nanjing, 2016, 46(2): 450-456.
Wang Shaofei, Zhang Weibing, Zhang Jixian and Chen Xinhai, Research on Framework of New Generation Guide System for Urban Traffic Flow, Technology of Highway and Transport. Chongqing, 2015(5): 90-95.
Li Xue, The Passenger Flow Guidance System for Urban Rail Transit Traffic Based on RFID, Wireless Internet Technology. Nanjing, 2016(2): 66-67+79.