基于浮动车数据的交通状态估计精度仿真评价

A Simulation based Evaluation of Traffic State Estimation Accuracy by Using Floating Car Data in Complex Road Networks

摘要:

针对大规模复杂路网条件下基于浮动车数据的交通状态估计精度评价，开发了基于交通仿真软件VISSIM的实时仿真分析方法.以上海市陆家嘴地区的微观仿真路网为例，通过30组仿真实验分析了浮动车比例和数据采样频率对路网覆盖率和平均行程车速估计精度的影响.结果表明：随浮动车比例和采样频率的增加，平均行程车速估计精度与路网覆盖率逐渐提高，当浮动车比例为8%和采样频率为1/10 s-1时达到最优.

Abstract:

This study developed a simulation based approach to comprehensively evaluate the joint effects of penetration rate and uploading frequency of floating car data on traffic state estimation accuracy for the large scale complex road networks. A case study based on the simulation model of Lujiazui Region in Shanghai was conducted to demonstrate the applicability of the developed approach and explore the optimal penetration rate and uploading frequency in terms of travel speed estimation accuracy and network coverage. Totally, 30 combinations of the two parameters were tested in the calibrated simulation model. Results show that the accuracy of travel speed estimation and network coverage rise as the penetration rate and uploading frequency increase. The optimal penetration rate and uploading frequency are found to be 8% and 1/10 s-1 respectively.