NDLI: Forecasting models for road-vehicle communication traffic in ITS

Content Provider	IEEE Xplore Digital Library
Author	Konishi, S. Fukuoka, H. Yasanaga, M.
Copyright Year	2000
Description	Author affiliation: KDD R&D Labs. Inc., Saitama, Japan (Konishi, S.)
Abstract	Since the telecommunication system will become one of important keys in an intelligent transport system (ITS), it is indispensable to consider and understand characteristics of the communication traffic to realize an efficient ITS communication network. In addition, forecasts of the communication traffic volume lead to efficient utilization of network equipment and frequency resources. Communication traffic characteristics in ITS networks are different from existing networks in that communication traffic is generated in vehicles. Therefore, we need to create suitable models for this purpose. This paper proposes effective and suitable forecasting models for ITS communication network planning. Since there is no available communication traffic data in ITS, models for generation of communication traffic are also described as well as the vehicle movement models. This paper also introduces a simulator developed based on these models. The proposed forcasting models are evaluated in terms of forecast error by the simulator. It is found from the simulation results that multiple linear regression models using traffic density data give more accurate forecast values than autoregressive models.
Starting Page	202
Ending Page	209
File Size	848515
Page Count	8
File Format	PDF
ISBN	0780359712
DOI	10.1109/ITSC.2000.881053
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2000-10-01
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Predictive models Traffic control Telecommunication traffic Communication networks Vehicles Intelligent systems Intelligent networks Frequency Character generation Linear regression
Content Type	Text
Resource Type	Article

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