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浙江大学学报(工学版)
浙江大学学报(工学版)  2019, Vol. 53 Issue (5): 950-956    DOI: 10.3785/j.issn.1008-973X.2019.05.016
交通工程     
基于改进Newman算法的动态控制子区划分
田秀娟1,2(),于德新1,3,4,周户星1,3,4,*(),邢雪1,王世广1
1. 吉林大学 交通学院，吉林 长春 130022
2. 吉林建筑大学 交通科学与工程学院，吉林 长春 130118
3. 吉林省智能交通工程研究中心，吉林 长春 130022
4. 吉林省道路交通重点实验室，吉林 长春 130022
Dynamic control subdivision based on improved Newman algorithm
Xiu-juan TIAN1,2(),De-xin YU1,3,4,Hu-xing ZHOU1,3,4,*(),Xue XING1,Shi-guang WANG1
1. College of Transportation, Jilin University, Changchun 130022, China
2. School of Transportation Science and Engineering, Jilin Jianzhu University, Changchun 130118, China
3. Jilin Engineering Research Center for Intelligent Transportation System, Changchun 130022, China
4. Jilin Province Key Laboratory of Road Traffic, Changchun 130022, China
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摘要：

为了优化现有控制子区划分方法，以区域协调控制为目标，提出基于改进的Newman社团快速划分的动态子区划分方法. 综合考虑路网中相邻交叉口之间的距离、交通流量、行程时间、车流离散特性、信号周期和路段交通流密度等因素，定量分析交叉口关联性；分别计算相邻交叉口的流量关联系数、信号周期关联系数和路段交通流密度关联系数，建立相邻交叉口的总关联度模型；对传统Newman算法进行改进，引入交叉口关联度，依据不同交通特性对区域路网进行动态子区划分；选取实际区域路网，进行模型验证分析. 结果表明：Newman算法子区划分结果不能随着交通特性的改变而改变；与之相比，所提出模型的子区划分结果更加细致，更加符合实际交通流特性，且可以依据不同时段交通特性实现动态子区划分，可以为信号控制方案制定提供良好基础.
关键词： 信号控制;  改进Newman算法;  子区划分;  交叉口关联性;  区域控制    
Abstract:

A dynamic subdivision method based on the improved Newman community fast division algorithm was proposed with the goal of regional coordinated control, in order to optimize the existing control subdivision method. The relevance of intersections was analyzed quantitatively by taking the factors including the distance between adjacent intersections, traffic volume, travel time, traffic flow discrete characteristic, signal cycle and road traffic flow density into consideration synthetically. The traffic flow correlation coefficient, signal cycle correlation coefficient and traffic flow density correlation coefficient of adjacent intersections were calculated respectively, and the total correlation degree model of adjacent intersections was established. The traditional Newman algorithm was improved and the correlation degree of intersections was brought in to divide the regional network into dynamic sub-regions according to different traffic characteristics. An actual regional road network was selected to verify the effect and performance of the proposed model. Results showed that control subdivision by Newman algorithm could not change with traffic characteristics. By contrast, the control subdivision result of the proposed model was more elaborate and more in line with the actual traffic flow characteristics. Moreover, dynamic subdivision could be realized according to the traffic characteristics of different time periods, which could provide a good basis for the formulation of the signal control scheme.
Key words: signal control    improved Newman algorithm    subdivision    relevance of intersections    regional control
收稿日期: 2018-04-25 出版日期: 2019-05-17
CLC:  U 491  
通讯作者: 周户星     E-mail: jidatianxj@126.com;zhouhx@jlu.edu.cn
作者简介: 田秀娟（1990—），女，讲师，从事智能交通系统及交通信号控制研究. orcid.org/0000-0001-7697-7481. E-mail： jidatianxj@126.com
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引用本文:

田秀娟,于德新,周户星,邢雪,王世广. 基于改进Newman算法的动态控制子区划分[J]. 浙江大学学报(工学版), 2019, 53(5): 950-956.

Xiu-juan TIAN,De-xin YU,Hu-xing ZHOU,Xue XING,Shi-guang WANG. Dynamic control subdivision based on improved Newman algorithm. Journal of ZheJiang University (Engineering Science), 2019, 53(5): 950-956.

链接本文:

http://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2019.05.016    或    http://www.zjujournals.com/eng/CN/Y2019/V53/I5/950

图 1  子区划分验证区域路网
图 2  区域路网简化图
i?j Ii?j i?j Ii?j
1?2 0.012 9?10 0.126
1?5 0.002 10?11 0.055
2?3 0.009 10?17 0.037
3?4 0.093 11?12 0.004
4?5 0.011 11?16 0.076
4?7 0.005 12?15 0.022
5?6 0.020 14?15 0.030
6?7 0.046 14?19 0.030
6?13 0.042 15?16 0.081
7?8 0.007 16?17 0.078
7?12 0.053 16?19 0.005
8?9 0.014 18?19 0.011
8?11 0.008 — —
表 1  交叉口总关联度
图 3  Newman算法交通子区划分结果
图 4  Newman算法子区划分模块度
图 5  改进Newman算法交通子区划分结果
图 6  改进Newman算法子区划分模块度
图 7  Newman算法交通控制子区组成
图 8  改进Newman算法交通控制子区组成
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