Development of a real time Image analysis system for traffic monitoring applications.

Image processing offers unparalleled potential for traffic monitoring and control. For many years engineers have attempted to perfect the art of automatic data abstraction from sequences of video images. This paper outlines a research project undertaken at Napier University by the authors in the field of image processing for automatic traffic analysis. A software based system implementing TRIP algorithms to count cars and measure vehicle speed has been developed by members of the Transport Engineering Research Unit (TERU) at the University. The TRIP algorithm has been ported and evaluated on an IBM PC platform with a view to hardware implementation of the pre-processing routines required for vehicle detection. Results show that a software based traffic counting system is realisable for single window processing. Due to the high volume of data required to be processed for full frames or multiple lanes, system operations in real time are limited. Therefore specific hardware is required to be designed. The paper outlines a hardware design for implementation of inter-frame and background differencing, background updating and shadow removal techniques. Preliminary results showing the processing time and counting accuracy for the routines implemented in software are presented and a real time hardware pre-processing architecture is described.

Network interactions and performance of a multi-function IEC 61850 process bus

New substation technology, such as non-conventional instrument transformers,and a need to reduce design and construction costs, are driving the adoption of Ethernet based digital process bus networks for high voltage substations. Protection and control applications can share a process bus, making more efficient use of the network infrastructure. This paper classifies and defines performance requirements for the protocols used in a process bus on the basis of application. These include GOOSE, SNMP and IEC 61850-9-2 sampled values. A method, based on the Multiple Spanning Tree Protocol (MSTP) and virtual local area networks, is presented that separates management and monitoring traffic from the rest of the process bus. A quantitative investigation of the interaction between various protocols used in a process bus is described. These tests also validate the effectiveness of the MSTP based traffic segregation method. While this paper focusses on a substation automation network, the results are applicable to other real-time industrial networks that implement multiple protocols. High volume sampled value data and time-critical circuit breaker tripping commands do not interact on a full duplex switched Ethernet network, even under very high network load conditions. This enables an efficient digital network to replace a large number of conventional analog connections between control rooms and high voltage switchyards.

Sensors for missions

An onboard payload may be seen in most instances as the “Raison d’Etre” for a UAV. It will define its capabilities, usability and hence market value. Large and medium UAV payloads exhibit significant differences in size and computing capability when compared with small UAVs. The latter have stringent size, weight, and power requirements, typically referred as SWaP, while the former still exhibit endless appetite for compute capability. The tendency for this type of UAVs (Global Hawk, Hunter, Fire Scout, etc.) is to increase payload density and hence processing capability. An example of this approach is the Northrop Grumman MQ-8 Fire Scout helicopter, which has a modular payload architecture that incorporates off-the-shelf components. Regardless of the UAV size and capabilities, advances in miniaturization of electronics are enabling the replacement of multiprocessing, power-hungry general-purpose processors for more integrated and compact electronics (e.g., FPGAs). Payloads play a significant role in the quality of ISR (intelligent, surveillance, and reconnaissance) data, and also in how quick that information can be delivered to the end user. At a high level, payloads are important enablers of greater mission autonomy, which is the ultimate aim in every UAV. This section describes common payload sensors and introduces two examples cases in which onboard payloads were used to solve real-world problems. A collision avoidance payload based on electro optical (EO) sensors is first introduced, followed by a remote sensing application for power line inspection and vegetation management.

Injury narrative text classification : a preliminary study

Description of a patient's injuries is recorded in narrative text form by hospital emergency departments. For statistical reporting, this text data needs to be mapped to pre-defined codes. Existing research in this field uses the Naïve Bayes probabilistic method to build classifiers for mapping. In this paper, we focus on providing guidance on the selection of a classification method. We build a number of classifiers belonging to different classification families such as decision tree, probabilistic, neural networks, and instance-based, ensemble-based and kernel-based linear classifiers. An extensive pre-processing is carried out to ensure the quality of data and, in hence, the quality classification outcome. The records with a null entry in injury description are removed. The misspelling correction process is carried out by finding and replacing the misspelt word with a soundlike word. Meaningful phrases have been identified and kept, instead of removing the part of phrase as a stop word. The abbreviations appearing in many forms of entry are manually identified and only one form of abbreviations is used. Clustering is utilised to discriminate between non-frequent and frequent terms. This process reduced the number of text features dramatically from about 28,000 to 5000. The medical narrative text injury dataset, under consideration, is composed of many short documents. The data can be characterized as high-dimensional and sparse, i.e., few features are irrelevant but features are correlated with one another. Therefore, Matrix factorization techniques such as Singular Value Decomposition (SVD) and Non Negative Matrix Factorization (NNMF) have been used to map the processed feature space to a lower-dimensional feature space. Classifiers with these reduced feature space have been built. In experiments, a set of tests are conducted to reflect which classification method is best for the medical text classification. The Non Negative Matrix Factorization with Support Vector Machine method can achieve 93% precision which is higher than all the tested traditional classifiers. We also found that TF/IDF weighting which works well for long text classification is inferior to binary weighting in short document classification. Another finding is that the Top-n terms should be removed in consultation with medical experts, as it affects the classification performance.

基于网络受限移动对象数据库的交通流统计分析模型

网络动态交通流的统计分析技术是目前移动计算及智能运输系统领域的一个重要研究方向．然而，现有的交通流统计分析方法(如基于固定传感器的方法、高空交通流监视方法、浮动车法等)存在着信息量少、数据处理复杂、精确度及效率低下、通信代价高昂等缺陷．为了有效地提高交通流统计分析的效率与精度，提出了一种基于网络受限移动对象数据库的交通流统计分析方法(network constrained moving objects database based traffic flow statistical analysis．NMOD—TFSA)．通过对移动对象所提交的位置更新信息进行联机统计，NMOD-TFSA能够实时地获取交通网络各部分的动态交通参数．由于在数据采集时考虑了道路网络的拓扑结构，NMOD．TFSA有效地降低了通信及计算的代价；此外，NMoD—TFSA所采集的数据能够反映移动对象完整的时空轨迹，因此为数据分析提供了更为丰富的信息，提高了数据处理的精度．实验结果表明，与目前通行的浮动车法相比，NMOD—TFSA有效地降低了 通信及计算代价，提高了交通流统计分析的精度与灵活性．

交通监控系统中运动目标分类和跟踪研究

文章讲述了交通监控系统中应用视频图像流来跟踪运动目标并对目标进行分类的具体过程和原则.基于目标检测提出了双差分的目标检测算法,目标分类应用到了连续时间限制和最大可能性估计的原则,目标跟踪则结合检测到的运动目标图像和当前模板进行相关匹配.实验结果表明,该过程能够很好地探测和分类目标,去除背景信息的干扰,并能够在运动目标部分被遮挡、外观改变和运动停止等情况下连续地跟踪目标.

Fuzzy-Rough Attribute Reduction with Application to Web Categorization.

R. Jensen and Q. Shen, 'Fuzzy-Rough Attribute Reduction with Application to Web Categorization,' Fuzzy Sets and Systems, vol. 141, no. 3, pp. 469-485, 2004.

Visible light communication systems for road safety applications

Esta tese apresenta um estudo exploratório sobre sistemas de comunicação por luz visível e as suas aplicações em sistemas de transporte inteligentes como forma a melhorar a segurança nas estradas. Foram desenvolvidos neste trabalho, modelos conceptuais e analíticos adequados à caracterização deste tipo de sistemas. Foi desenvolvido um protótipo de baixo custo, capaz de suportar a disseminação de informação utilizando semáforos. A sua realização carece de um estudo detalhado, nomeadamente: i) foi necessário obter modelos capazes de descrever os padrões de radiação numa área de serviço pré-definida; ii) foi necessário caracterizar o meio de comunicações; iii) foi necessário estudar o comportamento de vários esquemas de modulação de forma a optar pelo mais robusto; finalmente, iv) obter a implementação do sistema baseado em FPGA e componentes discretos. O protótipo implementado foi testado em condições reais. Os resultados alcançados mostram os méritos desta solução, chegando mesmo a encorajar a utilização desta tecnologia em outros cenários de aplicação.

All-optical routing functionalities

All-optical solutions for switching and routing packet-based traffic are crucial for realizing a truly transparent network. To meet the increasing requirements for higher bandwidth, such optical packet switched networks may require the implementation of digital functions in the physical layer. This scenario stimulated us to research and develop innovative high-speed all-optical storage memories, focusing mainly on bistables whose state switching is triggered by a pulsed clock signal. In clocked devices, a synchronization signal is responsible for controlling the enabling of the bistable. This thesis also presents novel solutions to implement optical logic gates, which are basic building blocks of any processing system and a fundamental element for the development of complex processing functionalities. Most of the proposed schemes developed in this work are based on SOA-MZI structures due to their inherent characteristics such as, high extinction ratio, high operation speed, high integration capability and compactness. We addressed the experimental implementation of an all-optical packet routing scheme, with contention resolution capability, using interconnected SOAMZIs. The impact on the system performance of the reminiscent power of the blocked packets, from the non ideal switching performed by the SOA-MZIs, was also assessed.

Visual surveillance using deformable models of vehicles

This paper presents recent developments to a vision-based traffic surveillance system which relies extensively on the use of geometrical and scene context. Firstly, a highly parametrised 3-D model is reported, able to adopt the shape of a wide variety of different classes of vehicle (e.g. cars, vans, buses etc.), and its subsequent specialisation to a generic car class which accounts for commonly encountered types of car (including saloon, batchback and estate cars). Sample data collected from video images, by means of an interactive tool, have been subjected to principal component analysis (PCA) to define a deformable model having 6 degrees of freedom. Secondly, a new pose refinement technique using “active” models is described, able to recover both the pose of a rigid object, and the structure of a deformable model; an assessment of its performance is examined in comparison with previously reported “passive” model-based techniques in the context of traffic surveillance. The new method is more stable, and requires fewer iterations, especially when the number of free parameters increases, but shows somewhat poorer convergence. Typical applications for this work include robot surveillance and navigation tasks.

Road network and GPS tracking with data processing and quality assessment

GPS technology has been embedded into portable, low-cost electronic devices nowadays to track the movements of mobile objects. This implication has greatly impacted the transportation field by creating a novel and rich source of traffic data on the road network. Although the promise offered by GPS devices to overcome problems like underreporting, respondent fatigue, inaccuracies and other human errors in data collection is significant; the technology is still relatively new that it raises many issues for potential users. These issues tend to revolve around the following areas: reliability, data processing and the related application. This thesis aims to study the GPS tracking form the methodological, technical and practical aspects. It first evaluates the reliability of GPS based traffic data based on data from an experiment containing three different traffic modes (car, bike and bus) traveling along the road network. It then outline the general procedure for processing GPS tracking data and discuss related issues that are uncovered by using real-world GPS tracking data of 316 cars. Thirdly, it investigates the influence of road network density in finding optimal location for enhancing travel efficiency and decreasing travel cost. The results show that the geographical positioning is reliable. Velocity is slightly underestimated, whereas altitude measurements are unreliable.Post processing techniques with auxiliary information is found necessary and important when solving the inaccuracy of GPS data. The densities of the road network influence the finding of optimal locations. The influence will stabilize at a certain level and do not deteriorate when the node density is higher.

Trips and their CO2 emissions induced by a shopping center

Most previous studies have focused on entire trips in a geographic region, while a few of them addressed trips induced by a city landmark. Therefore paper explores trips and their CO2 emissions induced by a shopping center from a time-space perspective and their usage in relocation planning. This is conducted by the means of a case study in the city of Borlänge in mid-Sweden where trips to the city’s largest shopping mall in its center are examined. We use GPS tracking data of car trips that end and start at the shopping center. Thereafter, (1) we analyze the traffic emission patterns from a time-space perspective where temporal patterns reveal an hourly-based traffic emission dynamics and where spatial patterns uncover a heterogeneous distribution of traffic emissions in spatial areas and individual street segments. Further, (2) this study reports that most of the observed trips follow an optimal route in terms of CO2 emissions. In this respect, (3) we evaluate how well placed the current shopping center is through a comparison with two competing locations. We conclude that the two suggested locations, which are close to the current shopping center, do not show a significant improvement in term of CO2 emissions.

Sistema de referenciação geográfica

Nos dias de hoje o acesso à informação por parte das empresas é vital para o bom desempenho das suas funções. As empresas de telecomunicações não fogem à regra, a sua posição no mercado está dependente das decisões que são tomadas com base na avaliação dessa informação. Para suportar os processos de apoio à decisão é coerente recorrer-se a Data Warehouses que permitem integrar informação de diversas fontes, verificando a sua qualidade, actualização e coerência, organizando-a para um fácil acesso e consulta de vários pontos de vista. Numa empresa de telecomunicações móvel, um Data Mart geográfico baseado na informação de tráfego da companhia que pode identificar as localizações preferenciais dos utilizadores na rede é muito importante porque fornece indicadores muito úteis para o departamento de marketing e negócio da empresa de maneira a que se saiba onde e como actuar para permitir que esta se desenvolva e ganhe vantagem no mercado. ABSTRACT: Today the access to information by enterprises is vital for the company’s performance. Telecommunications companies are no exception. Their position in the market is dependent on the decisions that are taken based on the evaluation of such information. To support the decision making process Data Warehouse is today an extremely useful tool; it integrates information from different sources, checking on its validity, quality and update, coherence, organizing it for an easy access and search from various perspectives. ln a mobile telecommunications company a geographical Data Mart-based traffic information that can identify the preferential locations of users on the network is very important It provides useful indicators to the Department of Marketing and Business there by allowing you to know where and how to act and boosting the development of the company.

Freeway traffic estimation in Beijing based on particle filter

Short-term traffic flow data is characterized by rapid and dramatic fluctuations. It reflects the nature of the frequent congestion in the lane, which shows a strong nonlinear feature. Traffic state estimation based on the data gained by electronic sensors is critical for much intelligent traffic management and the traffic control. In this paper, a solution to freeway traffic estimation in Beijing is proposed using a particle filter, based on macroscopic traffic flow model, which estimates both traffic density and speed.Particle filter is a nonlinear prediction method, which has obvious advantages for traffic flows prediction. However, with the increase of sampling period, the volatility of the traffic state curve will be much dramatic. Therefore, the prediction accuracy will be affected and difficulty of forecasting is raised. In this paper, particle filter model is applied to estimate the short-term traffic flow. Numerical study is conducted based on the Beijing freeway data with the sampling period of 2 min. The relatively high accuracy of the results indicates the superiority of the proposed model.