Home           Contact us           FAQs           
     Journal Home     |     Aim & Scope    |    Author(s) Information      |     Editorial Board     |     MSP Download Statistics
2013 (Vol. 5, Issue: 04)
Article Information:

The Method of Traffic State Identification and Travel Time Prediction on Urban Expressway

Yanguo Huang, Lunhui Xu and Qiang Luo
Corresponding Author:  Yanguo Huang 

Key words:  Fuzzy C-means clustering, fuzzy regression, traffic flow state, travel time prediction, urban expressway, ,
Vol. 5 , (04): 1271-1277
Submitted Accepted Published
June 28, 2012 August 17, 2012 February 01, 2013

This study presented a method of real-time traffic condition identification based on the fuzzy c-means clustering and travel time prediction on urban expressway. The traffic flow characteristics of expressway were analyzed and the traffic flow states were divided into four classes. Then the fuzzy c-means clustering technique was used to classify the sampled historical data and the clustering center of different traffic condition was gotten. In the test module, the real-time traffic data were used to identify which state the traffic data belong to. Based on the analysis, a travel time prediction model of urban expressway was given by using fuzzy regression. According to the collecting real-time traffic dada and the result of traffic state identification, a method of predicting travel time was introduced. Finally, an urban expressway in Guanzhou was as an example and the result of traffic state identification was same with the results of actual measurement data and questionnaire survey through drivers. The result of travel time prediction show that the predicted results had better fitting degree and precision and the feasibility of this method was verified. It can provide the basis for urban expressway traffic control and traffic induction.
Abstract PDF HTML
  Cite this Reference:
Yanguo Huang, Lunhui Xu and Qiang Luo, 2013. The Method of Traffic State Identification and Travel Time Prediction on Urban Expressway.  Research Journal of Applied Sciences, Engineering and Technology, 5(04): 1271-1277.
    Advertise with us
ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
Submit Manuscript
   Current Information
   Sales & Services
Home  |  Contact us  |  About us  |  Privacy Policy
Copyright © 2015. MAXWELL Scientific Publication Corp., All rights reserved