融合改进关联度与Newman算法的区域交通划分研究

doi:10.3778/j.issn.1002-8331.2103-0251

摘要/Abstract

摘要： 针对区域路网复杂度高、现有子区动态划分方法的不足，以优化区域协调控制为目标，提出一种基于引入改进关联度模型的改进Newman算法的区域路网动态划分方法。综合分析车队离散性和车流密度两种因素，提出了一种改进关联度模型；以模块度[Q]为划分标准，将交叉口关联度作为边权，改进传统的无权社团凝聚算法，使其能够依据交通流特性将路网动态划分为不同子区。仿真实验结果表明，所提出的改进划分方法能够有效结合实际交通流特性，对路网子区进行更加准确的实时动态划分。

关键词: 区域交通, 关联度模型, Newman算法, 子区划分

Abstract: Aiming at the high complexity of regional road network and the shortcomings of the existing dynamic sub-division methods, it proposes a dynamic division method of regional road network based on the improved Newman algorithm, which introduces the improved relational model, in order to optimize regional coordination control. Firstly, an improved relational degree model is proposed based on the comprehensive analysis of the two factors of fleet dispersion and traffic density. Secondly, taking the modular degree [Q] as the division standard, and the intersection correlation degree as the edge weight, the traditional unentitled community aggregation algorithm is improved to dynamically divide the road network into different sub-areas according to the traffic flow characteristics. The simulation results show that the proposed method can effectively combine the characteristics of actual traffic flow and make more accurate real-time dynamic division of the sub-area of road network.

Key words: regional traffic, relational degree model, Newman algorithm, sub-area division

王磊, 罗杰. 融合改进关联度与Newman算法的区域交通划分研究[J]. 计算机工程与应用, 2022, 58(20): 270-276.

WANG Lei, LUO Jie. Research on Regional Traffic Division Based on Improved Relevance Degree and Newman Algorithm[J]. Computer Engineering and Applications, 2022, 58(20): 270-276.

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