Modern traffic control and management systems in urban networks require real-time estimation of the traffic states. In this paper, a novel approach for modeling traffic flow in urban networks that is especially suitable for state estimation is proposed. The complexity of the urban traffic model is reduced by assuming availability of connected vehicle data. We first investigate the observability issue in urban traffic networks using a graphical approach. Then, the proposed model for the evolution of the traffic flow in urban traffic networks is developed and used in two layers, i.e., link layer and network layer, to estimate, in high-resolution (second-by-second), the traffic states in the whole network. Traffic states in the link layer include queue tail location and the number of vehicles in the queue, while in the network layer, estimation of the total number of vehicles per link and turning rates at the intersections is carried out. In a first step, it is shown that the estimation approach only requires the detectors at the borders of the network. We further demonstrate that in the proposed scheme, one may reduce or drop the need for spot detectors for the price of reduced, but still reasonable estimation accuracy. The validation of the approach has been undertaken by comparing the produced estimates with realistic micro-simulation results as ground truth, and the achieved simulation results are promising.

城市网络中的现代交通控制和管理系统需要实时估计交通状况。本文提出了一种特别适合于状态估计的新颖的城市网络交通流量建模方法。通过假设连接的车辆数据的可用性，降低了城市交通模型的复杂性。我们首先使用图形方法研究城市交通网络中的可观察性问题。然后，开发了建议的城市交通网络交通流量演化模型，并将其用于链路层和网络层两层，以高分辨率（每秒）估算交通状态。在整个网络中。链路层的流量状态包括队列尾部位置和队列中的车辆数量，而在网络层中，估计每个路段的车辆总数和十字路口的转弯速率。在第一步中，示出了估计方法仅需要在网络边界处的检测器。我们进一步证明，在提出的方案中，可以以降低的价格但仍然合理的估计精度来减少或减少对点检测器的需求。通过将产生的估计值与实际的微观模拟结果作为基本事实进行比较，对方法进行了验证，所获得的模拟结果很有希望。人们可以减少或减少对点检测器的需求，以降低价格，但仍要保持合理的估计精度。通过将产生的估计值与实际的微观模拟结果（作为基础事实）进行比较，对方法进行了验证，所获得的模拟结果很有希望。人们可以减少或减少对点检测器的需求，以降低价格，但仍要保持合理的估计精度。通过将产生的估计值与实际的微观模拟结果作为基本事实进行比较，对方法进行了验证，所获得的模拟结果很有希望。