Two Statistical Methods for Grouping Vehicles in Traffic Flow Based on Probabilistic Cellular Automata

被引:0
作者
Nakamura, Fumito [1 ]
Yamazaki, Keisuke [1 ]
机构
[1] Tokyo Inst Technol, Dept Computat Intelligence & Syst Sci, Midori Ku, G5-19,4259 Nagatsuta, Yokohama, Kanagawa, Japan
来源
2014 JOINT 7TH INTERNATIONAL CONFERENCE ON SOFT COMPUTING AND INTELLIGENT SYSTEMS (SCIS) AND 15TH INTERNATIONAL SYMPOSIUM ON ADVANCED INTELLIGENT SYSTEMS (ISIS) | 2014年
关键词
MODEL;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
There are many mathematical models of traffic flow that are used to analyze and simulate the phenomena of traffic jams. Specifically, a model based on the cellular automaton has been studied and used for traffic simulation systems. Recently, a method has been proposed that uses traffic flow data to estimate the parameter of the model; this enables us to objectively optimize and evaluate the model. However, model optimization has not been thoroughly considered for situations where the flow cannot be expressed by a single model, due to there being a variety of driving behaviors. In order to model a variety of behaviors, the present paper proposes two statistical methods that use mixture models with groups of vehicles that are distinguished by their average speeds.
引用
收藏
页码:956 / 960
页数:5
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