基于路口转弯流量的OD估计方法研究

OD Estimation Based on Turning Movement

机动车起终点矩阵(Origin-Destination Matrix,OD矩阵)的估计是交通规划和交通管理等工作的重要基础.本文主要研究在采集数据日渐精细情况下的机动车OD估计方法.基于车牌识别数据提取出路口转弯流量和路段断面流量,在此基础上建立应用广义最小二乘模型进行机动车OD估计的模型及方法.利用S-Paramics仿真平台及实测数据,应用Nguyen–Dupuis网络和实际城市路网对本文研究的方法进行了对比验证,分析对比验证了是否已知真实OD、不同的数据输入类型、不同的已知检测量的比例等.结果显示,与使用路段流量相比,使用转弯流量可以提高OD估计的准确性.

Origin- Destination Matrices, also called OD Matrix, is an important basic for the transport planning and traffic management. A procedure is proposed to estimate the OD matrix based on the abundant precise vehicle trajectory data. The turning movement and link count are provided by the automatic number plate recognition（ANPR） data. An OD estimation method is proposed based on the General Least Squared Model（GLS）. Using S-Paramics simulation platform, Nguyen-Dupuis Network and a real city road network are used to compare the estimation results of different circumstances： real OD known or unknown, two different inputs（the turning movement and the link count）, and different rates of measurements. The results show that the turning movement can improve the accuracy of OD estimation.