NDLI: Prediction of road resistance based on historical/real-time information and road quality

Content Provider	IEEE Xplore Digital Library
Author	Qihui Qin Meiling Feng Junqing Sun Bin Sun
Copyright Year	2015
Description	Author affiliation: Tianjin Key Lab. of Intell. Comput. & Novel Software Technol., Tianjin Univ. of Technol., Tianjin, China (Qihui Qin; Meiling Feng; Junqing Sun; Bin Sun)
Abstract	Due to the serious problem of urban traffic congestion, the real-time road situation and the possibility of road conditions in the next time period should be taken into accounts through the vehicle navigation system, in order to provide the optimal routing plans for vehicles in routing optimization. To solve the ignoring of real-time travel information and historical travel information in the existing navigation systems during routing optimization, this paper designs a comprehensive resistance prediction model based on the number of time periods that the vehicle has to take when it travels from the origin to the specified road. Through computing the weighted sum of the road quality, real-time travel information and historical travel information for a road segment, the required time that a vehicle passes the road segment can be predicted. The vehicle navigation system can use the information predicted by the resistance prediction model to plan the travel route for each vehicle, avoiding the congested road and saving travel time. The experimental results show that the prediction model has a good predictive effect and can provide reference for vehicle navigation systems or other mobile navigation devices in the planning period.
Starting Page	1073
Ending Page	1077
File Size	667713
Page Count	5
File Format	PDF
e-ISBN	9781467376822
DOI	10.1109/FSKD.2015.7382091
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-08-15
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Resistance Navigation Roads historical travel information road resistance prediction real-time navigation Predictive models Real-time systems Vehicles Autoregressive processes
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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