摘要
为改进传统交通方式划分模型,体现历史街区的特点以及提高预测精度,综合考虑历史街区的交通特性、出行特性及出行者特性3方面因素对交通方式选择的影响,以西安、洛阳、开封及郑州4个历史街区的居民出行调查数据为例进行实证分析,建立了基于BP神经网络算法的交通方式选择模型。结果表明:预测值与实际调查值基本吻合,模型具有一定的实用价值,可作为交通需求预测及交通规划的一种有效模型工具。
To improve the traditional travel mode choice model and reflect the features of the historic blocks as well as enhance the prediction model accuracy, this paper consider the influence of three aspects including traffic characteristics, travel characteristics and the trip self property for travel mode choice model firstly. Then, it take the travel data of investigation of inhabitants of four historic blocks including Xi＇an, Zhengzhou, Kaifeng and Luoyang as the examples to analyze model. Finally, the option model of traffic mode of historic blocks based on BP neural network is built. The results show that the proposed model accords well with real values and the model has practical value, so that it will be an effective tool to provide the basis for traffic demand forecasting and traffic planning.
出处
《建筑技术》
2018年第2期134-137,共4页
Architecture Technology
基金
国家自然科学基金项目(51278396)
关键词
历史街区
交通方式选择
BP神经网络
交通规划
historic blocks
travel mode choice model
BP neural network
traffic planning
