基于反向最近邻查询的智能交通调度模型  

Intelligent Transportation Scheduling Model Based on Reverse Nearest Neighbor Query Method

作　　者：尚晓丽[1] 包向辉[2] 

机构地区：[1]绥化学院信息工程学院,黑龙江绥化152061 [2]绥化学院网络信息中心,黑龙江绥化152061

出　　处：《科技通报》2015年第6期124-126,共3页Bulletin of Science and Technology

基　　金：绥化学院2014年科学技术研究资助项目项目编号:K1402006

摘　　要：智能交通调度模型设计是保障交通网络畅通的关键。传统的基于PID控制律的智能交通调度模型存在抗毁性和鲁棒性不好的问题。提出基于反向最近邻查询改进方法的智能交通调度模型,引入跟随蜂搜索蜜源算子,基于反向最近邻查询改进方法,建立一种基于粗糙集理论的前馈补偿动态博弈数学模型,提取制约交通拥堵的车辆密度、不同车道内的车辆加权平局速度等信息特征,作为PID路网系统的输出,克服实体无规则增长导致调度控制精度不高的问题。采用基于蜂群算法的反向最近邻查询改进方法交通信息特征提取,实现智能调度算法和控制模型的改进。仿真实验得出,采用该智能交通调度模型,可以有效提高车辆通行吞吐量,缩短路阻时间,保证了车辆畅通运行。The intelligent transportation scheduling model design is the key to ensure the smooth flow of traffic network. In?telligent transportation scheduling model PID control law in the presence of survivability and robustness of the problem based on the traditional. Reverse nearest neighbor query intelligent transportation scheduling model based on the improved method, the introduction of follow bee search nectar operator, reverse nearest neighbor queries based on the improved meth?od, the establishment of a feed forward compensation of dynamic game mathematical model based on rough set theory, fea?ture extraction of control traffic congestion, vehicle density of different lanes within the vehicle weighted draw speed and other information. As the output of PID network system, overcome the entity irregular growth leading to scheduling control problem of high precision. Artificial bee colony algorithm using reverse nearest neighbor query improved extraction method based on the characteristics of traffic information, improve the realization of intelligent scheduling algorithm and control model. The simulation experiments, using the intelligent transportation scheduling model, can effectively improve the traffic throughput, shorten the road resistance time, it ensures the smooth operation of the vehicle.

关 键 词：交通调度 控制模型 智能 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]