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.

Background: The environmental aspect of transportation has got a lot of attention over the past years. It has its origin in the growing awareness of environmental problems such as the global warming. In Europe the transportation industry is responsible for 21 per cent of the total emission. While studies of the subject show that an environmental friendly distribution and transportation is considered a success factor for many companies, there is a lack of interest from them to invest to obtain it. Purpose: The purpose of this paper is to find the current distribution situations and the factors that influence the transportation and environmental impacts while maintaining the same customer service level, as well as how these factors will influence distribution situations in some Chinese medical instrument manufacturing companies. Method: To gather data the authors will conduct a qualitative multiple case studies in the form of interviews at couple of medical equipment manufacturing companies to create the deep understanding needed to comprehend a company’s distribution system. Results, conclusion: Initially, the current situation of distribution system in Chinese medical instrument manufacturing companies has been found according to the cases companies’ analysis. Second, the four factors which would influence transportation and the environmental impact while keeping the same customer service level have been identified. They are fill rate, consolidation, standardization and postponement. Furthermore, benefiting how these factors will influence distribution situation through efficiency in transportation has been given as the suggestion and recommendation to some Chinese medical instrument manufacturing companies.

Geographical location of Lithuania determines its role as a transit country. This fact obliges to assure an efficient movement of the goods through the territory of Lithuania. One of the directions to evolve transport sector can be the development of combined road-rail transport (CT). The purpose of the dissertation – on the basis of analysis of scientific works and best practical experience in the field of CT to determine means that stipulate development of CT, arrange them according to the particularity of Lithuanian transport sector, and create a model for the development of combined carriages through the territory of Lithuania. In order to reach this purpose, following tasks are accomplished: 1.Determined all combined road-rail transport elements and their importance; 2.Investigated current market of CT in the EU and technological measures that assure development of these carriages; 3.Carried out an investigation of capabilities of Lithuanian transport system stressing an interaction of road and rail transport; 4.Created model which involves linkage of infrastructure of different transport modes in to one network and assures an optimal exploitation of infrastructure by flows of different transport modes. 5.Explained technological factors that influence possibilities to develop combined carriages through the territory of Lithuania.

Geographical location of Lithuania determines its role as a transit country. This fact obliges to assure an efficient movement of the goods through the territory of Lithuania. One of the directions to evolve transport sector can be the development of combined road-rail transport (CT). The purpose of the dissertation – on the basis of analysis of scientific works and best practical experience in the field of CT to determine means that stipulate development of CT, arrange them according to the particularity of Lithuanian transport sector, and create a model for the development of combined carriages through the territory of Lithuania. In order to reach this purpose, following tasks are accomplished: 1.Determined all combined road-rail transport elements and their importance; 2.Investigated current market of CT in the EU and technological measures that assure development of these carriages; 3.Carried out an investigation of capabilities of Lithuanian transport system stressing an interaction of road and rail transport; 4.Created model which involves linkage of infrastructure of different transport modes in to one network and assures an optimal exploitation of infrastructure by flows of different transport modes. 5.Explained technological factors that influence possibilities to develop combined carriages through the territory of Lithuania.

After World War II, automobile use expanded rapidly in the developed countries. As a result, travel pattern changed entirely and automobile has become the dominant form of transport in cities. As a result, the city has been shaped and sized in response to automobile needs. Such increase caused traffic problems in the Central Business Districts and surrounding areas. The problems of traffic congestion and pedestrian circulation have become an important issue in the whole city. As traffic problems have grown in developed cities, they had to be engaged in managing travel demand of people in order to provide mobility and access with reference to the advancing principles of sustainability. In this scope, this study shows the need of travel demand management to create a sustainable transport system. As a case, this study will evaluate the transport problems of Ankara and the place of the city in the urban transport policy process. At this point, transport problems and the transformation of road network and their impacts on the city will be examined in four periods. As a conclusion, urban transportation strategies needed for creating a sustainable transport system are overviewed for the city of Ankara.

This thesis presents a comparison of the two urban systems in Dublin and Bratislava with regard to the organization of transport and traffic management, fleet composition and fare. Aims to show the different approaches to the concept of public transport and progression, which in recent years the city has achieved.

Providing transportation system operators and travelers with accurate travel time information allows them to make more informed decisions, yielding benefits for individual travelers and for the entire transportation system. Most existing advanced traveler information systems (ATIS) and advanced traffic management systems (ATMS) use instantaneous travel time values estimated based on the current measurements, assuming that traffic conditions remain constant in the near future. For more effective applications, it has been proposed that ATIS and ATMS should use travel times predicted for short-term future conditions rather than instantaneous travel times measured or estimated for current conditions. This dissertation research investigates short-term freeway travel time prediction using Dynamic Neural Networks (DNN) based on traffic detector data collected by radar traffic detectors installed along a freeway corridor. DNN comprises a class of neural networks that are particularly suitable for predicting variables like travel time, but has not been adequately investigated for this purpose. Before this investigation, it was necessary to identifying methods for data imputation to account for missing data usually encountered when collecting data using traffic detectors. It was also necessary to identify a method to estimate the travel time on the freeway corridor based on data collected using point traffic detectors. A new travel time estimation method referred to as the Piecewise Constant Acceleration Based (PCAB) method was developed and compared with other methods reported in the literatures. The results show that one of the simple travel time estimation methods (the average speed method) can work as well as the PCAB method, and both of them out-perform other methods. This study also compared the travel time prediction performance of three different DNN topologies with different memory setups. The results show that one DNN topology (the time-delay neural networks) out-performs the other two DNN topologies for the investigated prediction problem. This topology also performs slightly better than the simple multilayer perceptron (MLP) neural network topology that has been used in a number of previous studies for travel time prediction.

The accurate and reliable estimation of travel time based on point detector data is needed to support Intelligent Transportation System (ITS) applications. It has been found that the quality of travel time estimation is a function of the method used in the estimation and varies for different traffic conditions. In this study, two hybrid on-line travel time estimation models, and their corresponding off-line methods, were developed to achieve better estimation performance under various traffic conditions, including recurrent congestion and incidents. The first model combines the Mid-Point method, which is a speed-based method, with a traffic flow-based method. The second model integrates two speed-based methods: the Mid-Point method and the Minimum Speed method. In both models, the switch between travel time estimation methods is based on the congestion level and queue status automatically identified by clustering analysis. During incident conditions with rapidly changing queue lengths, shock wave analysis-based refinements are applied for on-line estimation to capture the fast queue propagation and recovery. Travel time estimates obtained from existing speed-based methods, traffic flow-based methods, and the models developed were tested using both simulation and real-world data. The results indicate that all tested methods performed at an acceptable level during periods of low congestion. However, their performances vary with an increase in congestion. Comparisons with other estimation methods also show that the developed hybrid models perform well in all cases. Further comparisons between the on-line and off-line travel time estimation methods reveal that off-line methods perform significantly better only during fast-changing congested conditions, such as during incidents. The impacts of major influential factors on the performance of travel time estimation, including data preprocessing procedures, detector errors, detector spacing, frequency of travel time updates to traveler information devices, travel time link length, and posted travel time range, were investigated in this study. The results show that these factors have more significant impacts on the estimation accuracy and reliability under congested conditions than during uncongested conditions. For the incident conditions, the estimation quality improves with the use of a short rolling period for data smoothing, more accurate detector data, and frequent travel time updates.

Contemporary studies of Intelligent Transportation Systems (ITS) use simulations of vehicular and communications traffic, due to the ethical and practical infeasibility of conducting experiments on real transportation networks. Different simulators have been developed for modeling real-time vehicular mobility and inter-vehicular communication under varying traffic and roadway conditions. While most model the effect of mobility on communications, only a few simulate the impact of inter-vehicular communication on vehicular mobility. None, moreover, are implemented as parallel or distributed frameworks: an essential requirement for the study of ITS applications in large-scale urban environments. As a starting point for developing such a framework, one contemporary simulator, VNetInetSim, was tested to determine its behavior under large loads. Testing determined that VNetInetSim's memory usage and execution time increase exponentially in the number of simulated vehicles while remaining relatively constant under increased communication traffic.

京都大学 / 0048 / 新制・課程博士 / 博士(社会健康医学) / 甲第20290号 / 社医博第79号 / 社新制||医||9(附属図書館) / 京都大学大学院医学研究科社会健康医学系専攻 / (主査)教授 小池 薫, 教授 佐藤 俊哉, 教授 中山 健夫 / 学位規則第4条第1項該当 / Doctor of Public Health / Kyoto University / DFAM