Sensitivity analysis for correlation-based registration of digital images

Traffic management systems, which derive their measurements of vehicle counts, class, speed, and occupancy from TV sensors, are growing in popularity. The advantage of such systems is that, as new lanes are defined, the information of detection zones can be reprogrammed without having to physically move any embedded sensors. However, such TV cameras are frequently used in the dual roles of a traffic monitor, and of a traffic surveillance sensor. In the latter role, the TV camera is often moved in some pan or tilt, and even zoom mode. Following such a use, the camera is returned to its traffic monitor role. For many systems, this return to the traffic monitor mode requires a manual realignment. For other systems, this alignment is automatic and based upon a straightforward use of correlation or a variant of a modified correlation scheme. The question the system designer is required to answer is that of how accurate is this realignment. The answer is a function of measurable image variables. What is presented below is the theoretical analysis of that correlation process. This analysis allows the designer to tradeoff the selection of the correlation process such that accuracy might be maintained in spite of changes in such variables as signal-to-background measurements, signal-to-noise, and average pixel-to-pixel correlation.     

Calculation of traffic flow breakdown probability to optimize link throughput

Traffic breakdown phenomenon is prevalent in empirical traffic system observations. Traffic flow breakdown is usually defined as an amount of sudden drop in traffic flow speed when traffic demand exceeds capacity. Modeling and calculating traffic flow breakdown probability remains an important issue when analyzing the stability and reliability of transportation system. The breakdown mechanism is still mysterious to practitioners and researchers in varying manner. Treating breakdown as a random event, this paper use discrete time Markov chain (DTMC) to model traffic state transition path, as a result, a transition probability matrix can be generated from empirical observations. From empirical analysis of breakdown, we found this formulation of breakdown probability follows the Zipf distribution. Therefore, a connection from traffic flow breakdown probability to how many vehicles are occupying a certain freeway segment (e.g. a link) will be established. Following from the results, a quantitative measure of breakdown probability can be obtained to optimize ramp metering rates to achieve optimum system performance measures.     

A simulation optimization-based decision support tool for mitigating traffic congestion

Traffic congestion has grown considerably in the United States over the past 20 years. In this paper, we develop a robust decision support tool based on simulation optimization to evaluate and recommend congestion mitigation strategies to transportation system decision-makers. A tabu search-based optimizer determines different network design strategies on the road network while a traffic simulator evaluates the goodness of fit. The tool is tested with real-world traffic data.     

高速公路行车时间估计和最优路径

行车时间估计和最优路径选择是智能交通系统中的研究热点,特别是对于车辆导航系统更具有深远的意义.首先以传统的交通流理论为基础,采用间接模型和动力学模型进行行车时间估计,通过仿真实验比较了两模型的优劣,并使用实测数据分析得到的车流量信息对动力学模型进行改进.然后使用Dijkstra算法寻找出静态状态下的最优路径,再结合前面建立的时间估计模型,给出了适用于动态随机状态下的路径寻优算法,用于解决路段行车时间期望随出发时刻动态变化的问题.最后指出了交通实时信息对解决动态随机最优路线问题的重要性,并结合卡尔曼滤波算法对路段相关的情况作了进一步讨论.     

Instability of cooperative adaptive cruise control traffic flow: A macroscopic approach

This paper proposes a macroscopic model to describe the operations of cooperative adaptive cruise control (CACC) traffic flow, which is an extension of adaptive cruise control (ACC) traffic flow. In CACC traffic flow a vehicle can exchange information with many preceding vehicles through wireless communication. Due to such communication the CACC vehicle can follow its leader at a closer distance than the ACC vehicle. The stability diagrams are constructed from the developed model based on the linear and nonlinear stability method for a certain model parameter set. It is found analytically that CACC vehicles enhance the stabilization of traffic flow with respect to both small and large perturbations compared to ACC vehicles. Numerical simulation is carried out to support our analytical findings. Based on the nonlinear stability analysis, we will show analytically and numerically that the CACC system better improves the dynamic equilibrium capacity over the ACC system. We have argued that in parallel to microscopic models for CACC traffic flow, the newly developed macroscopic will provide a complete insight into the dynamics of intelligent traffic flow.     

A traffic shaping model for optimizing network operations

The management of technology in multi-service computer networks, such as university networks, has become a challenge with the explosive growth of entertainment oriented peer-to-peer (P2P) traffic. Traffic shaping is one of the tools used to manage bandwidth to improve system performance by allocating bandwidth between P2P and non-peer-to-peer (NP2P) traffic. We present a model for traffic shaping and bandwidth management that considers the trade-offs from allocating different amounts of bandwidths for different application categories and use data from a university network. The current policy allocates varying bandwidths over the day to P2P and NP2P traffic to reflect the importance of not letting entertainment based traffic choke the network during the day time at the expense of the more important traffic, such as Web traffic. We highlight the difficulties in obtaining data in the form required for analysis, and the need to estimate demand for allocations not covered by current policy. We present a goal programming model for this estimation task. We also model the traffic shaping problem as a Markov decision process and develop an algorithm for determining the optimal bandwidth allocation to maximize the utility of all users. Finally we use a numerical example to illustrate our approach.     

一种基于收费数据的断面流量估算方法

高速公路的流量是反映高速公路交通状态的一个重要参数.目前,针对高速公路断面流量的采集主要依靠人工方式或者通过安装一些车流检测设备来获得,成本较高.结合高速公路收费系统的特点,通过对收费数据的统计分析,提出一种基于收费数据估算高速公路断面流量的方法.首先,对收费数据进行初步的处理,从中计算出行驶时间;然后,根据收费数据中的车辆信息统计出各个OD的交通流量;最后,结合各个收费站出入口的位置信息、路段行驶速度信息以及OD流量来估算断面的交通流量.     

基于多维模糊关联规则的道路交通阻断分析方法

交通阻断成因复杂,与气象环境、道路线形、车辆状态以及交通环境等多因素相关。由于缺乏对造成交通阻断相关因素间潜在关联的研究,交通阻断管控一直是公路管理,特别是高速公路管理的难点。本文提出了一种基于多维模糊关联规则的道路交通阻断分析方法,发掘交通阻断的潜在规律和各因素间的关联关系。首先在国家现有相关划分体系和大量交通阻断(事件)案例的基础上,根据道路管理实际需求,建立了交通阻断多维属性模型,然后利用基于FCM的模糊关联规则,挖掘阻断因素的多维属性的依存关系,得到面向道路交通阻断分析的多维模糊关联规则。通过研究成果的实践应用,证明关联规则可以为道路交通阻断预防和管理提供有效支持,在道路交通阻断分析领域有着良好的应用前景。     

Improving short-term conflict alert via tabu search

In this paper we describe some work carried out by National Air Traffic Services in the UK into developing optimisation tools to help improve the effectiveness of one of their air traffic control safety systems—short-term conflict alert. In short-term conflict alert a computer system continually monitors radar data and alerts air traffic controllers if it detects a situation where two aircraft are in danger of approaching too close to one other. Within the computer program that makes up the short-term conflict alert system is a large number of parameters. Choosing appropriate values for these parameters is a task that is currently done via extensive human intervention. In this paper we describe how a modern heuristic technique, tabu search, can be used to make parameter choices.     

Macroscopic traffic models: Shifting from densities to “Celerities”

The advent of techniques to measure velocities of “GPS equipped vehicles” using satellite technology, replacing the density of the road traffic sensors, motivates and justifies the revision of conceptual, mathematical algorithms and software based models. This paper summarizes studies on the traffic evolutions achieving the minimum of a congestion function controlled “macroscopic traffic velocities” called “celerities” instead of founding traffic regulation on the measures of traffic densities. The flux valued function is the Fenchel transform of the fundamental diagram and is a convex decreasing function. We use the properties of capture basins investigated in viability theory, specifically a Lax-Hopf formula characterizing them and the “Max-Plus” morphism of capture basins for deriving the statements proved in this paper. Traffic conditions involve as well boundary conditions or conditions on trajectories inside the domain.     

移动GSM网话务量的ARIMA模型的建立及其预测

本文用ARIMA模型对株洲移动GSM网的话务量进行了建模分析和预报，研究表明ARIMA模型不但适合株洲移动GSM网话务量的非平稳时间序列的特点，而且预测效果比较理想。结果表明，ARIMA（1，1，1）提供了较精确的预测结果，可以用来对未来几周的话务量进行预测，有一定的实际价值。     

我国典型省份交通网络建设系统效用及关联分析

着眼于国家在2006年提出的中部地区建设综合交通运输枢纽的战略部署,结合我国在2008年进行大规模建设投资的背景,按照系统工程的观点,分析了区域交通建设投资对经济增长的拉动效应及关联性问题,试图探求我国典型省份在区域经济,财政等资源受限情况下交通网络建设投资的合理性及风险问题,并根据研究区域的实际情况提出压缩交通建设总规模,转变交通建设重点,大力发展城市公共交通等对策和建议,以期对提高交通建设投资效益提供参考.     

A network of priority queues in heavy traffic: One bottleneck station

In this paper we consider an open queueing network having multiple classes, priorities, and general service time distributions. In the case where there is a single bottleneck station we conjecture that normalized queue length and sojourn time processes converge, in the heavy traffic limit, to one-dimensional reflected Brownian motion, and present expressions for its drift and variance. The conjecture is motivated by known heavy traffic limit theorems for some special cases of the general model, and some conjectured “Heavy Traffic Principles” derived from them. Using the known stationary distribution of one-dimensional reflected Brownian motion, we present expressions for the heavy traffic limit of stationary queue length and sojourn time distributions and moments. For systems with Markov routing we are able to explicitly calculate the limits.     

一种基于Q学习的单路口交通信号控制方法

利用Watkins(1989)提出的Q学习算法,基于不同相位的动态最小时间需求,并以相位通行需求时间为研究对象,以动态相位时间差为状态转换控制目标,建立了单路口交通信号控制的一种动态智能控制方法.计算机模拟仿真表明这种控制方法的好的控制效果.     

Das Vorhersagerisiko der Sterblichkeitsentwicklung – Kann es durch eine geeignete Portfoliozusammensetzung minimiert werden?

Annuities as well as term insurance create risks for the insurance companies due to changes in mortality/longevity – especially in low-interest phases. For the past decades an increase in life expectancy was observed. In this article, we examine whether an insurance company can minimise the longevity risk by means of an appropriate composition of its portfolio. We use stochastic interest rates and mortality trends. For annuities and term insurance different mortality trends are used. Based on an example we show the impact of the portfolio composition on the longevity risk. The results prove that a deliberate portfolio composition can significantly reduce the longevity risk for the insurance company.     

A GIS-based decision support system for planning urban transportation policies

A decision support system (DSS) integrated in a geographical information system (GIS) for the analysis and evaluation of different transport policies is presented. The objective of the tool is to assist transport administrators enhance the efficiency of the transportation supply while improving environmental and energy indicators. The DDS works on three levels. The first performs the transport network analysis, the second assesses the energy consumption and pollutant emissions and the third evaluates the several policies selected. Road traffic is simulated using a deterministic, multi-modal traffic assignment model with capacity constraints. The model allows the estimation of traffic flow patterns within each link of the road network starting from the knowledge of the network characteristics and traffic demand. Energy consumption and pollutant emission calculations are based on the methodology developed by the CORINAIR working group. The evaluation of each policy scenario is based on a number of traffic, environmental and energy indicators. A multi-criteria analysis, where decision is based upon judging over appropriate weighted criteria, is adopted. Models are integrated in a GIS environment, which serves as the repository of the data as well as the user interface of the tool. The use of the tool is demonstrated through characteristic case studies on the Greater Athens Area in Greece. Two policy measures, one concerning the extension of the region where half of the private cars are prohibited from entering to the Municipality of Athens and the other the reduction of parking places in the same region by 50% are evaluated.     

Optimization models for assessing the peak capacity utilization of intelligent transportation systems

With limited economic and physical resources, it is not feasible to continually expand transportation infrastructure to adequately support the rapid growth in its usage. This is especially true for traffic coordination systems where the expansion of road infrastructure has not been able to keep pace with the increasing number of vehicles, thereby resulting in congestion and delays. Hence, in addition to striving for the construction of new roads, it is imperative to develop new intelligent transportation management and coordination systems. The effectiveness of a new technique can be evaluated by comparing it with the optimal capacity utilization. If this comparison indicates that substantial improvements are possible, then the cost of developing and deploying an intelligent traffic system can be justified. Moreover, developing an optimization model can also help in capacity planning. For instance, at a given level of demand, if the optimal solution worsens significantly, this implies that no amount of intelligent strategies can handle this demand, and expanding the infrastructure would be the only alternative. In this paper, we demonstrate these concepts through a case study of scheduling vehicles on a grid of intersecting roads. We develop two optimization models namely, the mixed integer programming model and the space-time network flow model, and show that the latter model is substantially more effective. Moreover, we prove that the problem is strongly NP-hard and develop two polynomial-time heuristics. The heuristic solutions are then compared with the optimal capacity utilization obtained using the space-time network model. We also present important managerial implications.     

Estimation of urban traffic conditions using an Automatic Vehicle Location (AVL) System

The aim of this paper is to develop an Information Extension Model (IEM) which uses location data of bus fleets (AVL data) to estimate road traffic conditions and provide input for implementing control strategies. The IEM consists of three sub-models: the Link Traffic Condition Model (LTCM), the AVL Adaptation Model (AVLAM) and the Network Traffic Condition Model (NTCM). The first provides road traffic conditions as a function of mass-transit traffic conditions in the case of shared lanes, the second provides mass-transit traffic conditions as a function of AVL data, and the last provides road traffic conditions over the whole road network as a function of mass-transit traffic conditions.     

Estimating Effective Capacity in Erlang Loss Systems under Competition

We consider an Erlang loss system (modem bank) with two streams of arriving customers, where arrival rates vary by time-of-day. We can observe one of the traffic streams (our customers), but we do not know how many servers the system has, or the characteristics of the other stream. Using detailed sample-path data, we construct a maximum likelihood estimator that makes good use of the data, but is slow to evaluate. As an alternative, we present an estimation system based on traffic data summarized by hour. This estimation system is much faster, and tends to produce good lower bounds on the size of the system and competing traffic.