Methods for the continuous network-wide quality analysis of road traffic flow

对路网内汽车交通的服务水平进行全网分析应该是交通管理的常规任务之一，以便维持稳定的交通流量或识别和解决瓶颈。考虑到目前严格有限的资源，负责道路的当局无法实现这一重要目标，因为传统的传感器技术(即环路探测器)和分析LOS方程仅允许对道路网络进行非常有限的观察。近年来，由于智能手机导航软件和现代车载导航系统的普及，浮动车数据(FCD)的可用性不断提高，为克服这一实际情况提供了很大的潜力。对匿名FCD轨迹的数据分析使交通规划者能够直接测量具有高成本效益的重要LOS指标，如延误时间、尾随长度和链接或路线行驶时间。在过去的几十年里，文献中已经提出了一些关于基于FCD的不同LOS检测技术的研究，并在现实中进行了测试。这些方法最重要和最关键的方面可以在数据提供和模型验证中看到，因为大多数方法需要非常密集的采样分辨率和高FCD渗透率，才能计算具有代表性的LOS估计。只有少数研究适合于典型的低频数据，这些数据目前可以由FCD提供商提供。FCD普及率在城市内和城市外地区之间差异很大，这意味着不同的数据分析方法，允许智能地适应可用的数据供应。因此，本研究方案的主要目标是基于Garmin/Navigon提供的真实低频FCD，开发有效的视线估计技术。此外，对非常大的FCD档案的完整处理需要一套非常复杂的数据处理方法，涵盖图论、数据过滤、路径推理和地图匹配的各个方面，因此，应用的处理方法本身就会影响数据输出，从而影响估计的LOS指标的代表性。为了能够简化FCD的工作并确保指标具有可比性，本研究项目还旨在开发一个经过验证的FCD处理堆栈，为进一步研究FCD分析提供一个更容易的切入点。

The network-wide analysis of the level of service (LOS) of car traffic within a road network should be one of the regular tasks of traffic management in order to either maintain a stable traffic flow or to identify and cure bottlenecks. With respect to nowadays strictly limited resources, road authorities in charge are not able to pursue this important goals, as traditional sensor techniques (i.e. loop detectors) and analytical LOS equations only allow a very limited view on the road network. During the recent years the increasing availability of floating car data (FCD) caused by the popular use of smartphone navigation software and modern on-board-navigation systems offer a high potential to overcome the actual situation. The data analysis of anonymized FCD trajectories enables traffic planners to measure directly and highly cost efficient important LOS indicators, like delay times, tailback lengths and link or route travel times. During the last decades several research regarding different FCD-based LOS detection techniques has been proposed in literature and were tested in reality. The most important and critical aspect of these methods could be seen in the data provisioning and model validation, as most methodologies require a very dense sampling resolution and high FCD penetration rates, to be able to calculate representative LOS estimates. Only the minority of research fits to typical low-frequency data, which could be supplied by FCD providers nowadays. FCD penetration rate varies highly between intra and extra urban areas, which implies different data analysis methodologies, that allow an intelligent adaptation to available data provisioning. The main target of this research proposal is therefore, the development of validated LOS estimation techniques, based on realistic low-frequency FCD provided by GARMIN/Navigon. Furthermore, the complete processing of very large FCD archives requires a very complex stack of data processing methodologies, that cover aspects of graph theory, data filtering, path inference and map-matching, whereby the applied processing approaches by itself influence the data output and therefore the representativity of estimated LOS indicators. To be able to simplify the work on FCD and to guarantee comparable indicators, this research project additionally aims on the development of a validated FCD processing stack, to give further research on FCD analysis an easier entry point.