摘要
对快速路交通流运行状态可靠性的概念进行了界定,分析了快速路可靠性的影响因素为饱和度、出入口密度、交通需求的波动和相连辅路的交通状况,提出运用神经网络建立快速路可靠度与其影响因素之间的关系.在对不同的输入变量进行归一化处理的基础上,构建了BP神经网络可靠性计算模型.最后通过实例对模型进行了验证,计算结果表明,实际输出与目标输出值的最大相对误差不超过3.5%.
The increase of traffic demand leads to the instability of urban expressways, which requires a probability measure parameter such as reliability to evaluate the dynamic performance of expressways. First, the concept of expressway performance reliability was defined and the influence factors such as saturation, density of on-ramp and off-ramp, fluctuation of traffic demand, traffic condition of corresponding side roads were analyzed. And then the construction of the functional relations between reliability and its factors by neural network was proposed. On the basis of different input variables normalization, the reliability model of BP neural network was built. Finally, the proposed model was testified by a numerical example, and the result indicated that the maximum relative error between factual output and target output was less than 3.5%
出处
《北京工业大学学报》
EI
CAS
CSCD
北大核心
2010年第3期348-352,共5页
Journal of Beijing University of Technology
基金
'十一五'国家科技支撑计划重点资助项目(2006BAJ18B01-06)
关键词
神经网络
快速路
可靠性
artificial neural network
expressway
reliability
