在这高度信息化的时代，手机和电脑作为信息的产物已经逐渐进入寻常百姓的家庭了；短信也成了人们生活中不可缺少的一部分，但是商旱的费用却让“指拇一族”犹豫不定，你想过每月只花5元钱就能发送1500条短信吗?想过用手机关闭你家中的...在这高度信息化的时代，手机和电脑作为信息的产物已经逐渐进入寻常百姓的家庭了；短信也成了人们生活中不可缺少的一部分，但是商旱的费用却让“指拇一族”犹豫不定，你想过每月只花5元钱就能发送1500条短信吗?想过用手机关闭你家中的电脑吗?想过用手机来调用你电脑上的程序吗?这一切的一切可以变为现实，都可以通过服务器平台和M2P(Mobile to PC)软件来实现手机和电脑的联姻！展开更多
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 intersectio...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.展开更多
文摘在这高度信息化的时代，手机和电脑作为信息的产物已经逐渐进入寻常百姓的家庭了；短信也成了人们生活中不可缺少的一部分，但是商旱的费用却让“指拇一族”犹豫不定，你想过每月只花5元钱就能发送1500条短信吗?想过用手机关闭你家中的电脑吗?想过用手机来调用你电脑上的程序吗?这一切的一切可以变为现实，都可以通过服务器平台和M2P(Mobile to PC)软件来实现手机和电脑的联姻！
基金Project(71101109) supported by the National Natural Science Foundation of China
文摘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.
