考虑人口效益的城市路网OD 矩阵推算模型

交通分布数据获取难度大、成本高，是制约交通工程师开展交通预测的主要因素. 为提高效率、降低工程实践中的预测成本，对城市路网OD矩阵可预测性展开研究. 描述3 种交通分布推算模型并以广州为例，给出交通流概率分布及发生量概率分布. 通过回归分析及残差分析探究发生量与人口、经济的关系，提出考虑人口效益的靶向双联模型(称为TDM模型). 根据误差分析验证4 种模型准确度，并将模型应用于深圳市. 结果表明：交通流及发生量概率分布具有高度异质性，遵循Zipf 定律；发生量与人口、经济相关性强，拟合优度为0.87； TDM模型精度略低于重力模型，但高于其他两种模型，且在深圳市推算效果良好. 综合预测精度、成本和效率，TDM模型更适合预测城市道路交通分布.

OD Matrix Estimation Model of Urban Road Network Considering Population Benefit

Traffic distribution data is difficult to obtain and cost high, which is the main factor restrict traffic engineers to carry out traffic prediction. In order to improve the efficiency and reduce the forecasting cost in engineering practice, we studied the predictability of OD matrix in urban road network. In this paper, three kinds of traffic distribution models are described. Taking Guangzhou as an example, the probability distribution of traffic flow and the probability distribution of production are given. By means of regression analysis and residual analysis, the relationship among production, population and economy is explored. We proposed a target dual-factor model considering population benefits (called TDM model). The error analysis is used to verify the accuracy of the four models and then the TDM model is applied in Shenzhen. The results show that the probability distribution of traffic flow and the probability distribution of production are highly heterogeneous and follow Zipf 's law. There is a strong correlation among the production, population and economy, and goodness of fit test is 0.87. The accuracy of the TDM model is slightly lower than that of the gravity model, but higher than that of the other two models. In addition, the result of forecast in Shenzhen is good. Considering prediction accuracy, cost and efficiency, the TDM model is more suitable for predicting urban road traffic distribution.