DocumentCode :
2363196
Title :
Vehicle Travel Time Prediction Algorithm Based on Historical Data and Shared Location
Author :
Chen, Peng ; Lu, Zhao ; Gu, Junzhong
Author_Institution :
Dept. of Comput. Sci. & Technol., East China Normal Univ., Shanghai, China
fYear :
2009
fDate :
25-27 Aug. 2009
Firstpage :
1632
Lastpage :
1637
Abstract :
In recent years, the travel time predictions have become a popular research topic. In this paper, we present a new algorithm of the travel time predictions based on the idea of using the shared traveler´s positions to collect traffic conditions. Several experiments show that our algorithm has a broader applied area than existing algorithms and can provide real-time and the accurate predictions for the travelers. And when there are more travelers and more positions shared among them, the more accurate predictions of our algorithm will be.
Keywords :
learning (artificial intelligence); neural nets; road traffic; historical data; shared location; shared traveler position; traffic condition collection; travel time prediction; vehicle travel time; Application software; Collaboration; Computer science; Neural networks; Prediction algorithms; Predictive models; Recurrent neural networks; Telecommunication traffic; Traffic control; Vehicles; ATIS; TP-HDSL; neural network; route guidance; shared position;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
INC, IMS and IDC, 2009. NCM '09. Fifth International Joint Conference on
Conference_Location :
Seoul
Print_ISBN :
978-1-4244-5209-5
Electronic_ISBN :
978-0-7695-3769-6
Type :
conf
DOI :
10.1109/NCM.2009.138
Filename :
5331594
Link To Document :
بازگشت