论文标题
使用MFD使用有限的交通数据来估算城市交通状态
Estimating the urban traffic state with limited traffic data using the MFD
论文作者
论文摘要
城市化导致城市交通的增加。宏观基本图(MFD)建议在层面上描述城市交通,以衡量和控制流量。但是,为了进行适当的估计,所有数据都需要可用。本文讨论的主要问题是:如何得出全网络范围的交通状态估计?我们跟进文献,建议以有限的样品共享浮动汽车数据(FCD)的速度进行操作估算。我们通过基于FCD构建MFD提出了一个第一步,然后在步骤2(操作交通状态估计)中使用该步骤。对于操作交通状态估计,即实时交通状态估计,渗透率尚不清楚。对于这两个步骤,我们评估估计中错误的影响。鉴于错误,我们还制定了一个指标,该指标表明该方法何时会产生无意义的结果,例如出现事件。该方法已使用微仿真测试。发现FCD渗透率为1%的估计平均密度误差为26%;将渗透率提高到30 \%可将估计平均密度的误差降低到7%。
Urbanization leads to an increase of traffic in cities. The Macroscopic Fundamental Diagram (MFD) suggests to describe urban traffic at a zonal level, in order to measure and control traffic. However, for a proper estimation, all data needs to be available. The main question discussed in this paper is: How to derive a network-wide traffic state estimate? We follow up on literature suggesting to base the operational estimate on the speed of limited sample cars sharing floating car data (FCD). We propose an initial step by constructing an MFD based on FCD, which is then used in step 2, the operational traffic state estimation. For operational traffic state estimation, i.e., the real-time traffic state estimation, the penetration rate is unknown. For both steps, we assess the impact of errors in the estimation. In light of the errors, we also formulate an indicator which shows when the method would yield insensible results, for instance in case of an incident. The method has been tested using microsimulation. A 26% error in the estimated average density is found for a FCD penetration rate of 1%; increasing the penetration rate to 30\% reduces the error in estimated average density to 7%.