基于樸素貝葉斯分類的高速公路交通事件檢測
發(fā)布時間：2018-11-26 06:53
【摘要】：提出一種基于樸素貝葉斯分類的高速公路非重現(xiàn)交通事件檢測算法.將交通事件的檢測看作是0-1分類問題,采用交通波動理論建立交通事件的特征屬性概念模型,并利用分段離散化的方法將連續(xù)特征變量轉(zhuǎn)換為離散特征變量,設(shè)計基于樸素貝葉斯算法的交通事件分類器.以典型高速公路的一條路段進行VISSIM仿真試驗.結(jié)果表明:該算法的檢測率高,且在高強度狀況下,算法魯棒性良好,適用于高速公路交通事件檢測系統(tǒng).
[Abstract]:Based on naive Bayes classification, an algorithm for detecting non-recurrence traffic events in freeway is proposed. The traffic event detection is regarded as a 0-1 classification problem. The traffic fluctuation theory is used to establish the concept model of the characteristic attribute of the traffic event, and the continuous characteristic variable is transformed into the discrete characteristic variable by the method of piecewise discretization. A traffic event classifier based on naive Bayes algorithm is designed. The VISSIM simulation test was carried out on a section of a typical expressway. The results show that the algorithm has high detection rate and good robustness under the condition of high intensity. It is suitable for highway traffic incident detection system.
【作者單位】： 同濟大學道路與交通工程教育部重點實驗室;
【基金】：國家自然科學基金(50408034) 上海市創(chuàng)新基金(11ZZ27)
【分類號】：U495
[Abstract]:Based on naive Bayes classification, an algorithm for detecting non-recurrence traffic events in freeway is proposed. The traffic event detection is regarded as a 0-1 classification problem. The traffic fluctuation theory is used to establish the concept model of the characteristic attribute of the traffic event, and the continuous characteristic variable is transformed into the discrete characteristic variable by the method of piecewise discretization. A traffic event classifier based on naive Bayes algorithm is designed. The VISSIM simulation test was carried out on a section of a typical expressway. The results show that the algorithm has high detection rate and good robustness under the condition of high intensity. It is suitable for highway traffic incident detection system.
【作者單位】： 同濟大學道路與交通工程教育部重點實驗室;
【基金】：國家自然科學基金(50408034) 上海市創(chuàng)新基金(11ZZ27)
【分類號】：U495
【參考文獻】
相關(guān)期刊論文 前3條
1 徐濤;楊曉光;徐愛功;張明月;;面向城市道路交通狀態(tài)估計的數(shù)據(jù)融合研究[J];計算機工程與應(yīng)用;2011年07期
2 邱世卉;王琪;;基于BP神經(jīng)網(wǎng)絡(luò)的高速公路交通事件檢測[J];中國測試;2009年02期
3 李娟;;相關(guān)系數(shù)法在通道交通需求預測中的應(yīng)用[J];中國公路學報;2006年05期
【共引文獻】
相關(guān)期刊論文 前10條
1 張迦南;趙鵬;;綜合運輸通道規(guī)劃方法研究[J];北京交通大學學報;2010年03期
2 孫峰華;陸大道;柳新華;顧九春;王振波;;中國物流發(fā)展對渤海海峽跨海通道建設(shè)的影響[J];地理學報;2010年12期
3 李娟;羅霞;陳方紅;;并行高速公路客貨運分線[J];系統(tǒng)工程;2007年08期
4 李瑞敏;陳熙怡;;多源數(shù)據(jù)融合的道路旅行時間估計方法研究[J];公路交通科技;2014年02期
5 劉擎超;陸建;陳淑燕;;基于隨機森林的交通事件檢測方法設(shè)計與分析(英文)[J];Journal of Southeast University(English Edition);2014年01期
6 郭t，
本文編號：2357663
本文鏈接：http://www.wukwdryxk.cn/kejilunwen/jiaotonggongchenglunwen/2357663.html
教材專著
