基于收费数据的高速公路交通拥挤自动判别方法

杨聚芬¹, 姜桂艳², 李琦³

(1.吉林大学 交通学院,130022 长春; 2.宁波大学 海运学院,315211 浙江 宁波; 3.青岛市城市规划设计研究院,266071 山东 青岛)



摘要:

针对高速公路交通拥挤日益严重的现象,通过对收费数据的深层挖掘和高效利用,提出了基于滚动时间序列的行程时间数据合成方法,以此为基础构建了交通拥挤指数,并基于交通拥挤指数的变化特征对拥挤持续时间进行了在线估计；结合收费站布局的时空特征,设计了基本路段和复合路段融合的高速公路交通拥挤自动判别方法. 实证分析表明,该方法在判别率提高到96.52%,误判率降低到0.43%的同时,判别时间减少了74%,而且收费数据的获取成本为零.

关键词:  交通工程  数据合成  交通拥挤  自动判别  收费数据

DOI：10.11918/j.issn.0367-6234.2014.12.018

分类号:U491.1

基金项目:国家自然科学基金(51278257);浙江省自然科学基金(LY12F01013); 高等学校博士学科点专项科研基金(20110061110034).



The automatic traffic congestion identification of freeway based on charging date

YANG Jufen¹, JIANG Guiyan², LI Qi³

(1. College of Transportation, Jilin University,130022 Changchun, China; 2. School of Maritime and Transportation, Ningbo University, 315211 Ningbo, Zhejiang,China;3. Qingdao Urban Planning and Design Institute, 266071 Qingdao, Shandong,China)

Abstract:

In view of increasingly serious traffic congestion on freeway, a synthesis method of travel time date was proposed based on the rolling time sequence and charging data, and on which this paper built a traffic congestion index and estimated the duration time according to the changing characteristics of the index. Moreover, taking the spatial and temporal characteristics of toll station layout into account, a method of automatic traffic congestion identification on freeway was designed by merging basic links with composite links. Empirical analysis shows that this method can improve the recognizing rate to 96.52% and reduce the false recognizing rate to 0.43%, at the same time, the recognizing time is declined by 74%, and the cost of charging date is zero.

Key words:  traffic engineering  data synthesis  traffic congestion  automatic identification  charging date