面向交通流信号分析的小波阈值去噪方法

为了提高交通流信号的去噪效果,提出了一种自适应逐层调整阈值和改进阈值函数的去噪算法。该算法结合自然对数函数的特性,使阈值随小波系数分解层数自适应的改变;加入了指数函数,构造一种介于硬、软阈值之间变化的新阈值函数,使去噪信号和原信号之间的误差减小。实验结果表明:相较于传统硬软阈值去噪,采用改进算法处理的信号直观效果好,且信噪比高和均方根误差小,运行效率高。改进后去噪算法各方面性能都得到了提升,具有较高的应用价值。

Vehicle actuation based short-term traffic flow prediction model for signalized intersections

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.

A novel conditional cell transmission model for oversaturated arterials

The objective of this work is to develop a novel feature for traffic flow models, when traffic queues on two-way arterials periodically extend until then they block an upstream signal in oversaturated conditions. The new model, proposed as conditional cell transmission model （CCTM） has been developed with two improvements. First, cell transmission model （CTM） is expanded for two-way arterials by taking account of all diverging and merging activities at intersections. Second, a conditional cell is added to simulate periodic spillback and blockages at an intersection. The results of experiments for a multilane, two-way, three-signal sample network demonstrate that CCTM can accommodate various traffic demands and accurate representation of blockages at intersections. The delay of left turns is underestimated by 40 % in moderate conditions and by 58% in oversamrated condition when using the CTM rather than CCTM. Finally, the consistency between HCS 2000 and CCTM shows that CCTM is a reliable methodology of modeling traffic flow in oversaturated condition.

Mixed Traffic Flow Capacity of More Major Lanes Unsignalized Intersection

Highway capacity is defined as maximum volume of traffic flow through the particular highway section under given traffic conditions, road conditions and so on. Highway construction and management is judged by capacity standard. The reasonable scale and time of highway construction, rational network structure and optimal management mode of highway network can be determined by analyzing the fitness between capacity and traffic volume. All over the world, highway capacity is studied to different extent in different country. Based on the gap acceptance theory, the mixed traffic flow composed of two representative vehicle types heavy and light vehicles is analyzed with probability theory. Capacity model of the minor mixed traffic flows crossing m major lanes, on which the traffic flows fix in with M3 distributed headway, on the unsignalized intersection is set up, and it is an extension of minor lane capacity theory for one vehicle-type and one major-lane traffic flow.

Tri-level programming model for combined urban traffic signal control and traffic flow guidance

In order to balance the temporal-spatial distribution of urban traffic flow, a model is established for combined urban traffic signal control and traffic flow guidance. With consideration of the wide use of fixed signal control at intersections, traffic assignment under traffic flow guidance, and dynamic characteristics of urban traffic management, a tri-level programming model is presented. To reflect the impact of intersection delay on traffic assignment, the lower level model is set as a modified user equilibrium model. The middle level model, which contains several definitional constraints for different phase modes, is built for the traffic signal control optimization. To solve the problem of tide lane management, the upper level model is built up based on nonlinear 0-1 integer programming. A heuristic iterative optimization algorithm(HIOA) is set up to solve the tri-level programming model. The lower level model is solved by method of successive averages(MSA), the middle level model is solved by non-dominated sorting genetic algorithm II(NSGA II), and the upper level model is solved by genetic algorithm(GA). A case study is raised to show the efficiency and applicability of the proposed modelling and computing method.