Presentation 2014-01-22
Control of Vehicles by Updating Optimal Velocity Function based on Local Information
Yuta MINOSHIMA, Hiroya NAKAO,
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Abstract(in English) Traffic congestion of vehicles is considered to be a social problem, leading to waste of transportation time. To suppress traffic congestion, various methods for controlling vehicles have been proposed. In this report, within the framework of the optimal velocity model of traffic flows, we propose a control method for suppressing traffic congestion by using the information of local vehicle density. In the original optimal velocity model, the velocity of each vehicle is determined by the optimal velocity function, which specifies the target velocity as a function of the distance between the vehicle and its preceding vehicle just ahead of it. In our proposed method, the parameter of the optimal velocity function is moreover updated depending on the local density of the vehicles. By numerical simulations, we analyze how the traffic state depends on the number of the vehicles used to estimate the local vehicle density and on the global vehicle density. It is found that the proposed method can lead to formation of vehicle groups, thereby suppressing congestion and increasing total traffic flow.
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Keyword(in English) traffic flow / jam / optimal velocity model / control of vehicles
Paper # NLP2013-157
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Conference Information
Committee NLP
Conference Date 2014/1/14(1days)
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Paper Information
Registration To Nonlinear Problems (NLP)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Control of Vehicles by Updating Optimal Velocity Function based on Local Information
Sub Title (in English)
Keyword(1) traffic flow
Keyword(2) jam
Keyword(3) optimal velocity model
Keyword(4) control of vehicles
1st Author's Name Yuta MINOSHIMA
1st Author's Affiliation Department of Mechanical and Environmental Informatics, Graduate School of Information Science and Engineering, Tokyo Institute of Technology()
2nd Author's Name Hiroya NAKAO
2nd Author's Affiliation Department of Mechanical and Environmental Informatics, Graduate School of Information Science and Engineering, Tokyo Institute of Technology
Date 2014-01-22
Paper # NLP2013-157
Volume (vol) vol.113
Number (no) 383
Page pp.pp.-
#Pages 5
Date of Issue