Open AccessShort-term traffic flow prediction for multi traffic states on urban expressway network
Author(s) -
Chunjiao Dong,
Chunfu Shao,
Chengxiang Zhuge
Publication year - 2012
Publication title -
wuli xuebao
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.199
H-Index - 47
ISSN - 1000-3290
DOI - 10.7498/aps.61.010501
Subject(s) - traffic flow (computer networking) , traffic generation model , traffic congestion reconstruction with kerner's three phase theory , computer science , term (time) , traffic wave , network traffic simulation , traffic congestion , flow (mathematics) , traffic equations , transport engineering , real time computing , simulation , network traffic control , computer network , mathematics , engineering , physics , quantum mechanics , geometry , network packet
Short-term traffic flow prediction for multi traffic states on urban expressway network is carried out in this paper. The model for multi traffic states is proposed by integrating the spatial and the temporal distribution characteristics of traffic flow parameters under free traffic, congested traffic and jam traffic respectively. Based on the classical traffic flow conservation equation, the ideology of spatial and temporal dispersions in partial differential equations is adopted to establish short-time traffic flow prediction model. Meanwhile, the impact factors, such as on and off ramp, lane change and road slope are considered, which convertes short-term traffic flow prediction model into short-time traffic flow prediction state space model. Finally, the short-term traffic flow prediction for multi traffic states on urban expressway network is realized. The empirical research shows that compared with the classic ARMA model, the proposed method can not only realize short-term traffic flow prediction for multi traffic states on urban expressway network but also achieve an accuracy of 90.23%. In the same condition, the accuracy of ARMA model is 81%.