DocumentCode :
3352516
Title :
Deducing and forecasting expressway status based on toll collection data
Author :
Wu, Tianshu ; Wu, Jianying ; Hu, Bin ; Song, Guojie ; Li, Jian ; Xie, Kunqing
Author_Institution :
Key Lab. of Machine Perception, Peking Univ., Beijing, China
fYear :
2010
fDate :
26-28 June 2010
Firstpage :
2738
Lastpage :
2741
Abstract :
Expressway transportation is playing a more important roll in economic construction and social life. The expressway network status, including section flow and average speed, is important to the expressway management for analysis and decision making. Traditional ways of monitoring the road is using detectors which cost much to install and maintain. We propose speed constraint deducing model and similarity weighted forecasting model to calculate expressway network status based on toll collection data. The deducing model calculates all the cars´ movement in the network according to the time and stations they entered and exited the network, and then generates road status of the past time. The forecasting model forecasts the current and shot term future status based on weighted historical status, when toll collection data is not available. Experiments based on toll collection data of Beijing expressway showed that the deducing model and forecasting model had good accuracy. The models present network status without any cost, which have a broad application prospect.
Keywords :
automated highways; decision making; transportation; Beijing expressway status forecasting; decision making; economic construction; expressway management; expressway transportation; toll collection data; weighted historical status; Costs; Decision making; Detectors; Economic forecasting; Laboratories; Monitoring; Predictive models; Roads; Transportation; Vehicle detection; deducing model; expressway status; forecasting model; toll collection data;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Mechanic Automation and Control Engineering (MACE), 2010 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-7737-1
Type :
conf
DOI :
10.1109/MACE.2010.5535829
Filename :
5535829
Link To Document :
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