Cheong Chi Hong. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2006. / Includes bibliographical references (leaves 81-86). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgement --- p.v / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Problem statement --- p.1 / Chapter 1.2 --- Major contributions --- p.4 / Chapter 1.3 --- Thesis organization --- p.4 / Chapter 2 --- Smart Card System --- p.6 / Chapter 2.1 --- Introduction --- p.7 / Chapter 2.2 --- Related Work --- p.11 / Chapter 2.2.1 --- Mining Customer Behaviors --- p.11 / Chapter 2.2.2 --- Privacy Preserving Data Mining --- p.12 / Chapter 2.2.3 --- Definitions of Privacy --- p.13 / Chapter 2.3 --- Model --- p.14 / Chapter 2.4 --- Algorithms --- p.17 / Chapter 2.4.1 --- Baseline Algorithm --- p.17 / Chapter 2.4.2 --- Privacy Equation --- p.19 / Chapter 2.4.3 --- Random Subsequence Selection Algorithm (RSSA) --- p.20 / Chapter 2.4.4 --- Popular Item Selection Algorithm (PISA) --- p.21 / Chapter 2.5 --- Analysis --- p.26 / Chapter 2.5.1 --- Accuracy --- p.26 / Chapter 2.5.2 --- Analysis of RSSA: Determine te values --- p.27 / Chapter 2.5.3 --- Analysis of RSSA: Accuracy --- p.30 / Chapter 2.5.4 --- Analysis of PISA --- p.33 / Chapter 2.5.5 --- Theoretical Proof of PISA --- p.41 / Chapter 2.5.6 --- Privacy Protection --- p.42 / Chapter 2.6 --- Simulations --- p.45 / Chapter 3 --- Transportation System --- p.48 / Chapter 3.1 --- Introduction --- p.49 / Chapter 3.2 --- Related Work --- p.51 / Chapter 3.3 --- Model --- p.56 / Chapter 3.4 --- Algorithms --- p.60 / Chapter 3.5 --- Simulations --- p.63 / Chapter 4 --- Enhanced Features in a Smart Card System --- p.67 / Chapter 4.1 --- Adding Time Information --- p.68 / Chapter 4.1.1 --- Motivation --- p.68 / Chapter 4.1.2 --- Time Intervals --- p.68 / Chapter 4.1.3 --- Original Graph --- p.69 / Chapter 4.1.4 --- New Graph --- p.70 / Chapter 4.1.5 --- Adding the New Graph into the Model --- p.72 / Chapter 4.1.6 --- Rewriting the Definition of a Path --- p.73 / Chapter 4.1.7 --- Drawback of Adding Time Information --- p.73 / Chapter 4.2 --- Generalization --- p.75 / Chapter 4.2.1 --- Motivation --- p.75 / Chapter 4.2.2 --- Generalization --- p.75 / Chapter 4.3 --- Specialization vs. Generalization --- p.75 / Chapter 5 --- Conclusion --- p.79 / Bibliography --- p.81

Li Xiang. / "September 2004." / Thesis (Ph.D.)--Chinese University of Hong Kong, 2004. / Includes bibliographical references (p. 164-172) / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. Ann Arbor, MI : ProQuest Information and Learning Company, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Mode of access: World Wide Web. / Abstracts in English and Chinese.

As an example, the thesis proposes a real-time route guidance system to show how it supports other transportation services, which can then automatically guide vehicles by voice. It illustrates the system architecture and describes the establishment of each part. The concept of agent network is introduced to build up the system. Furthermore, a dynamic route algorithm is presented in brief. A communication system integrating the existing infrastructure is discussed and simulation results are provided to testify the applicability of the proposed wireless data communication system. / Finally, the thesis sums up the contributions achieved and proposes some future works. / For the communication network, the main challenging problems are the large scale of the network, the movement of vehicles that may cause the levity of the network structure, and the large demands on communication capacity. In order to solve these problems, the performance optimization technique is accredited as one of the most important techniques for such a large scale wireless sensor network. This thesis focuses on the research in the following aspects. First, the optimal combination of the duty cycle, one of the most important parameters, is introduced to optimize the system performance. A duty cycle optimization model is put forward based on calculating n-times reachable matrix. Now that the parameter optimization model can be boiled down to a NP-hard problem, an improved genetic algorithm is introduced to solve the problem. The computational procedure and efficiency are discussed, and simulation study based on a practical road network is given to illustrate the validity of the proposed method. Second, the topological structure optimization problem is formulated as a graph problem, while fulfilling random node-to-node communication demands. A new optimization method, called un-detour optimization, is proposed to optimize the topological structure based on the improved genetic algorithm. In addition, the approach is evaluated quantitatively by simulating community wireless sensor networks. The comparison results demonstrate that some significant performance advantages can be achieved by this approach. / In addition, two important techniques required to build the new surveillance system are discussed in this thesis. (1) the sensors to collect traffic information; (2) the communication network to transmit information among all sensors and vehicles. / In order to detect and track the moving objects, this thesis presents a creative background updating method, which can works effectively even for some complex circumstances. The image processing results show that this method can realize the segmentation of the moving objects. Due to the simple model and fast calculation speed, the method can satisfy the requirements of detecting and tracking traffic objects in real time and at a high speed. Additionally, the thesis designs a new kind of object detection and tracking algorithm based on the attributive combination of contour and color in order to deal with the occlusion problem to some extent. Some experiments have testified to the robustness and practicability of the proposed system. / Nowadays, with the rapid development of economics and societies, transportation is playing a very important role in the balanced running of social and economic systems. However, urban traffic problems such as traffic accidents and traffic congestions are becoming more and more serious in almost all large cities in the world. / This thesis is focused on a traffic surveillance system which collects and transmits real-time traffic information in a large city, which is one of the most important steps in solving the transportation problems above. Considering the drawbacks of current traffic surveillance system, a brand-new system with a distributed architecture is proposed based on the concept of sensor networks. Then, an intelligent sensor node using an embedded ARM chip and MCU is developed and software system is built up accordingly, including Linux operating system, hardware drivers, and so on. Finally, a simulation program proves the validity of the system. / Shi, Xi. / "September 2007." / Adviser: YangShong Xu. / Source: Dissertation Abstracts International, Volume: 69-08, Section: B, page: 4946. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2007. / Includes bibliographical references (p. 120-130). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts in English and Chinese. / School code: 1307.

Today transportation systems are facing big transitions all over the world. We created fly overs, roads under the ground, bridges over the river and ocean to get efficient access and to increase the road connectivity. Our transportation system is more intelligent than ever. Our traffic signaling system became adaptive. Our vehicles equipped with new gadgets and we developed new tools for more efficient analysis of traffic. Our research relies on existing traffic infrastructure to generate better understanding of traffic. More specifically, this research focused on traffic and UAV cameras to extract information about the traffic. Our first goal was to create an automatic system to count the cars using traffic cameras. To achieve this goal, we implemented Background Subtraction Method (BSM) and OverFeat Framework. BSM compares consecutive frames to detect the moving objects. Because BSM only works for ideal lab conditions, therefor we implemented a Convolutional Neural Network (CNN) based classification algorithm called OverFeat Framework. We created different segments on the road in various lanes to tabulate the number of passing cars. We achieved 96.55% accuracy for car counting irrespective of different visibility conditions of the day and night. Our second goal was to find out traffic density. We implemented two CNN based algorithms: Single Shot Detection (SSD) and MobileNet-SSD for vehicle detection. These algorithms are object detection algorithms. We used traffic cameras to detect vehicles on the roads. We utilized road markers and light pole distances to determine distances on the road. Using the distance and count information we calculated density. SSD is a more resource intense algorithm and it achieved 92.97% accuracy. MobileNet-SSD is a lighter algorithm and it achieved 79.30% accuracy. Finally, from a moving platform we estimated the velocity of multiple vehicles. There are a lot of roads where traffic cameras are not available, also traffic monitoring is necessary for special events. We implemented Faster R-CNN as a detection algorithm and Discriminative Correlation Filter (with Channel and Spatial Reliability Tracking) for tracking. We calculated the speed information from the tracking information in our study. Our framework achieved 96.80% speed accuracy compared to manual observation of speeds. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2019. / FAU Electronic Theses and Dissertations Collection

A safe and efficient highway infrastructure is a critical component and a valuable asset in terms of its monetary value, as well as supporting the way of life and economic activities of the people it serves. In North America, performing maintenance, repair, and expansion of an aging highway infrastructure to a target level of performance while dealing with ever-increasing traffic demands creates a significant challenge in terms of road user safety and mobility. Much of the current highway infrastructure was built several decades ago and it is therefore requiring increasing levels of maintenance and rehabilitation. <p>The cost of delays resulting from traffic congestion induced by work zones is estimated to be more than $6 billion per year. Work zone related traffic fatalities exceed more than 1000 lost lives per year in North America. Work zone related fatalities account for approximately 2.8 percent of highway fatalities in United States and 1.3 percent in Canada. While overall fatal crash rates have been steadily decreasing in both Canada and United States, work zone related fatalities have not been decreasing. <p>Smart Work Zones are an emerging technology designed to improve the safety and mobility within work zones on highways. Smart Work Zones employ various technologies to monitor current traffic conditions and provide relevant information to road managers and road users on current traffic flow conditions and automatically provide guidance to motorists for safer and more efficient navigation of the work zone. <p>This research examined the effects of a Smart Work Zone deployment by modeling traffic flow with and without a Smart Work Zone at the case study site in North Carolina to provide inputs into a performance analysis framework. The quantification of benefits and costs related to the deployment of a Smart Work Zone was developed in a probabilistic analysis framework model. The performance was quantified in economic terms of expected benefit cost ratio and net value realized from the deployment of a Smart Work Zone. The model considers the cost of deployment and potential savings in terms of motorist safety (fatal and injury crash reduction) as well as improvements in traveler mobility including reductions in user delays, vehicle operating costs, and emissions.<p>The model output is a risk profile that provides a range of expected values and associated probabilities of occurrence to quantify the expected benefits while also taking into consideration the uncertainty of the most sensitive input variables. The uncertainty of input variables determined to be the most sensitive were those associated with the amount of user delay and the valuation of user delay. The next most sensitive inputs are those associated with the cost of deploying and operating the Smart Work Zone system. <p>The model developed in this research concurs with the approach and analysis used in other models for the analysis of transportation projects. The model developed in this research provides a tool that can be used for decision making regarding the deployment of a Smart Work Zone and comparison with other transportation project alternatives. The model employs a user definable approach that enables it to be adapted to the specific conditions of a diverse range of field state conditions and has the ability to interface with several traffic flow models. <p>When applied to a case study project on Interstate 95 in North Carolina, the model was found to be capable of providing useful and relevant results that correlated to observed performance. The case study represented one of many operating scenarios on the project, and is not necessarily representative of all the field state conditions occurring over the period of the entire deployment. <p>The model results included a sensitivity analysis that identified the sensitivity of the outcome to uncertainty in the input values and a risk analysis that quantified the uncertainty of the predictions. The findings indicated that, at a 95 percent confidence level, the expected benefit / cost ratio of deploying a Smart Work Zone system was between 1.2 and 11.9 and the net value was between $10,000 and $225,000 per month of operation. Approximately 94 percent of the expected benefits were from savings in user delay and the remainder from savings due to improved safety, reduced emissions, and reduced vehicle operating costs. The results indicate that when applied under appropriate conditions, Smart Work Zones have the potential to provide significant benefits to road users. Under heavily congested conditions, the diversion of even a small amount of traffic to a more efficient route can provide sizable travel time improvements for all traffic.<p>In summary, the model developed in this research was specifically developed to apply to Smart Work Zones, but in its general form could also be applied to other work zone traffic management applications. In the case study the model was applied to a single rural work zone, but the framework could be extended for an integrated analysis of multiple work zones and network analysis in an urban setting. The research provides a fundamental framework and model for the analysis of Smart Work Zones and a method to determine the sensitivity of the uncertainty of input values. The research also identifies areas for continued examination of the effects of Smart Work Zone deployment and the prediction of expected benefits.

A safe and efficient highway infrastructure is a critical component and a valuable asset in terms of its monetary value, as well as supporting the way of life and economic activities of the people it serves. In North America, performing maintenance, repair, and expansion of an aging highway infrastructure to a target level of performance while dealing with ever-increasing traffic demands creates a significant challenge in terms of road user safety and mobility. Much of the current highway infrastructure was built several decades ago and it is therefore requiring increasing levels of maintenance and rehabilitation. <p>The cost of delays resulting from traffic congestion induced by work zones is estimated to be more than $6 billion per year. Work zone related traffic fatalities exceed more than 1000 lost lives per year in North America. Work zone related fatalities account for approximately 2.8 percent of highway fatalities in United States and 1.3 percent in Canada. While overall fatal crash rates have been steadily decreasing in both Canada and United States, work zone related fatalities have not been decreasing. <p>Smart Work Zones are an emerging technology designed to improve the safety and mobility within work zones on highways. Smart Work Zones employ various technologies to monitor current traffic conditions and provide relevant information to road managers and road users on current traffic flow conditions and automatically provide guidance to motorists for safer and more efficient navigation of the work zone. <p>This research examined the effects of a Smart Work Zone deployment by modeling traffic flow with and without a Smart Work Zone at the case study site in North Carolina to provide inputs into a performance analysis framework. The quantification of benefits and costs related to the deployment of a Smart Work Zone was developed in a probabilistic analysis framework model. The performance was quantified in economic terms of expected benefit cost ratio and net value realized from the deployment of a Smart Work Zone. The model considers the cost of deployment and potential savings in terms of motorist safety (fatal and injury crash reduction) as well as improvements in traveler mobility including reductions in user delays, vehicle operating costs, and emissions.<p>The model output is a risk profile that provides a range of expected values and associated probabilities of occurrence to quantify the expected benefits while also taking into consideration the uncertainty of the most sensitive input variables. The uncertainty of input variables determined to be the most sensitive were those associated with the amount of user delay and the valuation of user delay. The next most sensitive inputs are those associated with the cost of deploying and operating the Smart Work Zone system. <p>The model developed in this research concurs with the approach and analysis used in other models for the analysis of transportation projects. The model developed in this research provides a tool that can be used for decision making regarding the deployment of a Smart Work Zone and comparison with other transportation project alternatives. The model employs a user definable approach that enables it to be adapted to the specific conditions of a diverse range of field state conditions and has the ability to interface with several traffic flow models. <p>When applied to a case study project on Interstate 95 in North Carolina, the model was found to be capable of providing useful and relevant results that correlated to observed performance. The case study represented one of many operating scenarios on the project, and is not necessarily representative of all the field state conditions occurring over the period of the entire deployment. <p>The model results included a sensitivity analysis that identified the sensitivity of the outcome to uncertainty in the input values and a risk analysis that quantified the uncertainty of the predictions. The findings indicated that, at a 95 percent confidence level, the expected benefit / cost ratio of deploying a Smart Work Zone system was between 1.2 and 11.9 and the net value was between $10,000 and $225,000 per month of operation. Approximately 94 percent of the expected benefits were from savings in user delay and the remainder from savings due to improved safety, reduced emissions, and reduced vehicle operating costs. The results indicate that when applied under appropriate conditions, Smart Work Zones have the potential to provide significant benefits to road users. Under heavily congested conditions, the diversion of even a small amount of traffic to a more efficient route can provide sizable travel time improvements for all traffic.<p>In summary, the model developed in this research was specifically developed to apply to Smart Work Zones, but in its general form could also be applied to other work zone traffic management applications. In the case study the model was applied to a single rural work zone, but the framework could be extended for an integrated analysis of multiple work zones and network analysis in an urban setting. The research provides a fundamental framework and model for the analysis of Smart Work Zones and a method to determine the sensitivity of the uncertainty of input values. The research also identifies areas for continued examination of the effects of Smart Work Zone deployment and the prediction of expected benefits.

Automatic Incident Detection Algorithms (AIDA) have been part of freeway management system software from the beginnings of ITS deployment. These algorithms introduce the capability of detecting incidents on freeways using traffic operations data. Over the years, several approaches to incident detection have been studied and tested. However, the size and scope of the urban transportation networks under direct monitoring by transportation management centers are growing at a faster rate than are staffing levels and center resources. This has entailed a renewed emphasis on the need for reliability and accuracy of AIDA functionality. This study investigates a new approach to incident detection that promises a significant improvement in operational performance. This algorithm is formulated on the premise that the current conditions facilitate the prediction of future traffic conditions, and deviations of observations from the predictions beyond a calibrated level of tolerance indicate the occurrence of incidents. This algorithm is specifically designed for easy implementation and calibration at any site. Offline tests with data from the Georgia-Navigator system indicate that this algorithm realizes a substantial improvement over the conventional incident detection algorithms. This algorithm not only achieves a low rate of false alarms but also ensures a high detection rate.

Construction ¡§traffic control system of high-speed road network Northern traffic information management and coordination command center systems engineering" Vendor, RPTI, due to execute his right to stop, causing to others under construction engineering progress into delay or even halt, Furthermore, causing irreparable damage to the public interest. This action will also affect either the progress to be procrastinating, or failure of the entire project of construction plan. In a word, it stalls off the development of the ITS industrial. This paper aimed at studying the case manufacturers suffer administrative relief and derivative right to stop financial crises, and finally to the brink of bankruptcy. Stopped right disputing caused by uncertain legal concept of cognitive difference. Once the vendor has been suspended for the execution of the contract likely to have non-compliance or abuse of the fact that compliance; legal system face the compliance phase of the case as a stop right to the subject, but also derivative is easy to mediation and complaint competing, as well as administrative litigation court rejected status; complaint Review lengthy process to consider the judgment as if the provisions of the appeal decision has resulted in the responsible entity procurement operations distress. The vendor will be published in the Government Procurement Gazette by the responsible organization. As the result, it might be more difficulty to maintain the business; moreover, the published not only announce to loss of right of government bidding; even worse, will affect the company¡¦s Goodwill and survival of business. The Suspended punishment of the Government Procurement Law system, whether is appropriateness, and the further influencing factors of overall competitiveness. Made by MICHAEL PORTER¡¦s diamond theory, "stop right" under the "other external factors opportunities (opportunity and Government policy) "An analysis of the State ITS industrial competitiveness. Diamond combination of the four factors is well and available, but opportunities exist does not necessarily help to enhance the competitiveness of industry, but counterproductive injury, will allow businesses or companies collapse, or even disappear. As the ITS industry as the government established policy of the Department of National Infrastructure, the opportunity this factor evolved out of the results of the company, the enterprise, the whole industry chain and even the country's competitiveness will be immeasurable. Therefore, this article will discuss actual cases of the case manufacturer¡¦s discussion. RPTI is to the brink of bankruptcy, forced to dissolve, engineers, technicians. Subsequently, a large number of employees left, the company¡¦s core values (the process of information technology and intelligent transportation systems technology and system integration capabilities) gone, the competitiveness of the domestic intelligent transportation industry will thus setback

Recurrent congestion in urban traffic networks, especially on arterials, is a growing problem. Non-recurrent congestion, mainly due to incidents, only aggravates the problem. Any solution requires monitoring of the network, for which many developing countries, such as Turkey, do not have the traditional surveillance systems on arterials mainly due to high costs. An alternative solution is the utilization of Global Positioning System (GPS) technology, which is increasingly used in traffic monitoring. It is easy and cheap to obtain the GPS track information,even in real-time, from a probe-vehicle or a fleet of vehicles / and spatial variation of speed and travel time of the vehicle(s) in a network can be determined. GPS-based data, especially with only one probe-vehicle, would not provide information on the concurrent states of upstream and downstream traffic, needed to define the state of traffic in a network. To overcome this obstacle, a methodology based on statistical analysis of archival traffic conditions obtained through different sources is proposed to analyze traffic fluctuations and identify daily traffic pattern. As a result, bottleneck and resulting queues can be detected on a corridor. Thus, it enables detection of recurrent congestion and queues that may result from incidents. The proposed methodology is tested on a corridor the roadway between METU and Kizilay of in&ouml / n&uuml / Boulevard. The results show that the methodology can effectively identify bottleneck locations on the corridor and also an incident observed during the data collection is detected correctly by the proposed algorithm.

Tez (Yüksek Lisans) - Süleyman Demirel Üniversitesi, Fen Bilimleri Enstitüsü, Yapı Eğitimi Anabilim Dalı, 2009. / Kaynakça var.