交叉口黄灯期间驾驶员行为的模糊决策树模型  

Fuzzy Decision Tree Model for Driver Behavior Confronting Yellow Signal at Signalized Intersection

作　　者：龙科军[1,2] 赵文秀 肖向良[1] 

机构地区：[1]长沙理工大学交通运输工程学院,长沙410114 [2]道路灾变防治及交通安全教育部工程研究中心,长沙410114 [3]广州市公路局,广州510420

出　　处：《计算机工程》2011年第11期16-18,共3页Computer Engineering

基　　金：国家"十一五"科技支撑计划基金资助项目(2009BAG13A02);湖南省科学技术厅科技计划基金资助重点项目(2010WK4001);广东省交通运输厅科技基金资助项目(2010-02-038)

摘　　要：采集黄灯期间驾驶员行为的相关数据,考虑车辆位置、车速、倒计时表3个影响因素,分别设定其隶属度函数,应用模糊决策树中的FID3算法,以模糊信息熵为启发信息,构建驾驶员选择的模糊决策树模型,生成决策规则。利用测试样本对模型进行检验,结果表明,基于模糊决策树的预测结果准确率总体达到84.8%。Drivers decision to go or stop during the yellow interval belongs to uncertain decision making.This paper collects drivers behavior data at four similar intersections.Fuzzy Decision Tree（FDT） is applied to model driver behavior at signalized intersection.Considering vehicle location,velocity and countdown timer as the influencing factors,the FDT model is constructed using FID3 algorithm,and decision rules are generated as well.Test sample is applied to test FDT model,and results indicate that FDT model can predict drivers＇ decision with overall accuracy of 84.8%.

关 键 词：数据挖掘 驾驶员行为 模糊决策树 不确定理论 模糊信息熵 

分 类 号：TP273.4[自动化与计算机技术—检测技术与自动化装置]