微观交通仿真系统的近邻查询算法

doi:10.11772/j.issn.1001-9081.2015.02.0572

计算机应用 ›› 2015, Vol. 35 ›› Issue (2): 572-577.DOI: 10.11772/j.issn.1001-9081.2015.02.0572

微观交通仿真系统的近邻查询算法

宋竹, 秦志光, 邓伟伟, 赵玉平

电子科技大学计算机科学与工程学院, 成都 611731

收稿日期:2014-09-03 修回日期:2014-10-28 发布日期:2015-02-12 出版日期:2015-02-10
通讯作者: 宋竹
作者简介:宋竹(1983-),男,四川成都人,博士研究生,CCF会员,主要研究方向:数据挖掘、交通仿真; 秦志光(1956-),男,四川隆昌人,教授,博士生导师,博士,主要研究方向:信息安全; 邓伟伟(1990-),男,安徽芜湖人,硕士研究生,主要研究方向:数据挖掘; 赵玉平(1987-),男,四川广元人,硕士,主要研究方向:交通仿真。
基金资助:
国家863计划项目(2011AA010706);国家自然科学基金资助项目(61170041)。

Nearest neighbor query algorithm in microscopic traffic simulation system

SONG Zhu, QIN Zhiguang, DENG Weiwei, ZHAO Yuping

School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu Sichuan 611731, China

Received:2014-09-03 Revised:2014-10-28 Online:2015-02-12 Published:2015-02-10

摘要/Abstract

摘要：

为解决现有微观交通仿真系统中,由于采用基于链表的方法处理近邻查询导致的查询效率和可扩展性不高的问题,提出了一种基于B+树的近邻查询算法。该算法借鉴了数据库中近邻查询算法的思想并结合了链表结构的优点,在叶子节点维护了其存储的数据单元(即车辆)关系的索引结构,以达到快速查询车辆所在车道的前后车的目的。同时,在假设车辆随机分布的前提下,构建了一个数学模型,根据道路的属性和道路中车辆的数量,计算查询目标车辆的邻近车辆所需的最短平均查询长度,并通过此最短查询长度推导算法参数的最优值。理论分析和对比仿真实验显示,衡量该算法的主要指标:即仿真每个车辆的平均时间消耗,在三类常见的交通参数设置(正常的、较拥堵的和拥堵的)下较链表和B+树分别降低了64.2%和12.8%。仿真结果表明该算法具有良好的可扩展性,更适用于大规模微观交通仿真系统。

关键词: 微观交通仿真, B+树, 链表, 近邻查询, 参数优化

Abstract:

Since methods based on linked list in existing microscopic traffic simulation systems are not efficient and scalable to process Nearest Neighbor (NN) queries, a variation of B+ tree based method was proposed to resolve these problems. This method combined ideas from NN queries in database with advantages of linked list. By maintaining indices of nearby vehicles of each vehicle in the local lane, the performance of NN queries in that lane could be largely improved. Under the assumption of randomly distribution of vehicles, a mathematical model was also proposed to optimize the parameter setting according to multiple parameters for lanes and the amount of vehicles. This model calculated the minimized average query length of each NN query to optimize the parameter setting. The results of theoretical analysis and simulations showed that in common traffic conditions including sparse, normal and congestion, the main indicator, namely the average simulation time cost of each vehicle, could be reduced by 64.2% and 12.8% compared with linked list and B+ tree respectively. The results prove that the proposed method is suitable for larges-cale microscopic traffic simulation systems.

Key words: microscopic traffic simulation system, B+ tree, linked list, nearest neighbor query, parameter optimization

中图分类号:

TP391.9

宋竹, 秦志光, 邓伟伟, 赵玉平. 微观交通仿真系统的近邻查询算法[J]. 计算机应用, 2015, 35(2): 572-577.

SONG Zhu, QIN Zhiguang, DENG Weiwei, ZHAO Yuping. Nearest neighbor query algorithm in microscopic traffic simulation system[J]. Journal of Computer Applications, 2015, 35(2): 572-577.

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微观交通仿真系统的近邻查询算法

Nearest neighbor query algorithm in microscopic traffic simulation system

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