摘要
恶劣天气的公路交通极易瘫痪,设计公路交通优化调度模型,提高公路交通网络的稳定性和抗毁坏性。传统的公路交通调度模型采用并行微观矢量等价加权结构,各重点路段和路口节点不能有效区别评价,调度效果不好。提出一种基于多维矢量线性规划的恶劣天气下的公路交通有效调度模型。进行恶劣天气下的交通路网信息采集,构建PID神经网络路网模型,路网模型采用一个5元组表示,提取制约交通拥堵的关键信息。设计恶劣天气下的交通拥塞检测算法,根据多维矢量线性规划可得单位路径行程时间下的拥塞状态联合分布,计算最佳适应度值,实现交通优化调度。仿真结果表明,采用该模型进行公路交通拥塞程度检测和调度,检测精度较高,能准确反映公路交通的实时状态信息,通过有效调度能大幅度提供公路交通的通行效率,应用价值较高。
Highway Traffic bad weather is easily paralyzed, and design of highway traffic scheduling optimization model, to improve the highway traffic network stability and robustness. Highway traffic scheduling model using the traditional equiva-lent weighted vector parallel micro structure, the key sections and intersection node cannot effectively distinguish evalua-tion, scheduling the effect is not good. A road traffic effective scheduling model of multi-dimensional vector linear program-ming based on the bad weather. Road traffic information collection of inclement weather, building a PID neural network model of road network, road network model is represented by a 5 tuple, extract the key information to control traffic conges-tion. Traffic congestion detection algorithm design under bad weather conditions, according to the congestion state of multi-dimensional vector linear programming can be unit of travel time under the joint distribution, calculation of the best fitness value, the realization of traffic scheduling optimization. The simulation results show that, using this model to the traffic con-gestion degree detection and scheduling, high detection precision, can accurately reflect the real time status information of road traffic, through the effective scheduling can greatly the traffic efficiency of road traffic, higher application value.
出处
《科技通报》
北大核心
2015年第10期232-234,共3页
Bulletin of Science and Technology
关键词
公路交通
调度
网络
恶劣天气
highway transportation
scheduling
network
bad weather
