NDLI: Dynamic prediction method of route travel time based on interval velocity measurement system

Content Provider	IEEE Xplore Digital Library
Author	Min Wang Qing Ma
Copyright Year	2014
Description	Author affiliation: Traffic Manage. Res. Inst. of the Minist. of Public Security, Wuxi, China (Qing Ma) \|\| Sch. of Transp., Southeast Univ., Nanjing, China (Min Wang)
Abstract	Focusing on the dynamic travel time prediction for the intelligent transportation system (ITS), this paper proposes a new prediction method by introducing the particle filters algorithm. Based on the interval velocity measurement system, various traffic parameters of the highway are obtained, and a state model with these associated parameters is built for the travel time estimation. Then, the probability distribution of the system state is simulated by a set of particles according to Bayesian theory. The distribution of these particles is updated real-time based on the state transition model and re-sampling method at last. The estimated travel time is given based on the predicted system state distribution. The proposed method learns the system state transition model based on the history data derived from the interval velocity measurement system. And the introduction of the particle filters improves the proposed method greatly to handle the dynamic and uncertainty of the system. Simulation experiments are taken on the traffic data from the detection sensors on several road sections. The results show that the proposed method has much better prediction performance than some traditional methods, and validate this method can be applied on the route travel time prediction of a dynamic traffic flow.
Starting Page	172
Ending Page	176
File Size	1060689
Page Count	5
File Format	PDF
ISBN	9781479960583
DOI	10.1109/SOLI.2014.6960714
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-10-08
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Intelligent transportation Route travel time estimation Interval velocity measurement Estimation Dynamic prediction
Content Type	Text
Resource Type	Article

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