中文摘要：

交通流动预言是为在城市的动脉的网络的即时交通适应的信号控制的一个重要部件。由从附近的交叉探索可得到的察觉者和信号控制器信息，一个动态数据驱动的流动预言模型被开发。模型在在上游的交叉为每个运动由在信号状态(红或绿色) 上基于部件的二预言组成。每个信号状态的特征小心地被检验，在在下游的交叉的问题的途径的从在上游的交叉的相应旅行时间被预言。与一个联机拐弯处比例评价方法，与预言的旅行时间一起，期望的车辆到达能在下游的交叉被预报。模型表演在一套二点被测试位于 Gainesville 的城市的庆祝交叉，佛罗里达，美国，用 CORSIM 显微镜的模拟包裹。分析结果证明模型同意很好，实验到达数据在 10%20% 的一个可接受的范围以内在 10 s 间隔测量了，并且显示出正常分布。模型在真正积极的即时交通适应信号控制系统为使用有潜在的适用性，这相当被相信。

英文摘要：

Traffic flow prediction is an important component for real-time traffic-adaptive signal control in urban arterial networks. By exploring available detector and signal controller information from neighboring intersections, a dynamic data-driven flow prediction model was developed. The model consists of two prediction components based on the signal states （red or green） for each movement at an upstream intersection. The characteristics of each signal state were carefully examined and the corresponding travel time from the upstream intersection to the approach in question at the downstream intersection was predicted. With an online turning proportion estimation method, along with the predicted travel times, the anticipated vehicle arrivals can be forecasted at the downstream intersection. The model performance was tested at a set of two signalized intersections located in the city of Gainesville, Florida, USA, using the CORSIM microscopic simulation package. Analysis results show that the model agrees well with empirical arrival data measured at 10 s intervals within an acceptable range of 10%-20%, and show a normal distribution. It is reasonably believed that the model has potential applicability for use in truly proactive real-time traffic adaptive signal control systems.