Digitized by Kansas Correctional Industries

Digitized by Kansas Correctional Industries

Typescript (photocopy). / Digitized by Kansas Correctional Industries

This research developed a new methodology and new models for assessing the potential of motorcycle crashes and selecting countermeasures to improve motorcyclist safety in a motorcycle-dominated traffic environment of urban roads. The crash risk models were developed based on discrete choice models and traffic conflict techniques. The innovative features of this research are that the non-lane-based movements of motorcycles were captured to evaluate their contributions to crash risk and a new concept - that of the Conflict Modification Factor (CoMF) - was proposed to use as a surrogate measure to assess the relative contribution of risk factors to crashes. In addition, a methodology was also developed to enhance the existing International Road Assessment Programme (iRAP) star rating system for motorcyclists. The developed models were fitted and validated using data collected from urban roads in the city of Danang in Vietnam. The operating speed, speed difference, traffic density, front distance, longitudinal gap, lateral clearance and road surface condition were found to significantly contribute to motorcycle crash risk and several countermeasures have been consequently identified to improve motorcyclist safety including: installing changeable speed limit signs, installing changeable gap warning signs, installing changeable road surface condition warning signs and providing segregated motorcycle lanes.

Highway engineers have addressed the problem of pavement maintenance by developing remaining life assessment methods based on structural analysis of computer simulations of pavements tested in the field by non-destructive testing devices such as the Falling Weight Deflectometer (FWD). However the methodologies followed have been shown to be unable to provide accurate solutions without undue reliance on the knowledge of the expert engineer who conducts the analysis. A knowledge-based system (KBS) is proposed to "inject" engineering knowledge into the conventional techniques. It has been established on a systematic basis and seeks to cover the variety of the issues which may be encountered in such systems. In its prototype form the system consists of three parts: 1. The finite element analytical program ROSTRA-1. 2. A deductive database. 3. A back-analysis subsystem. The analytical program carries out the analysis of the pavements tested in the field. The deductive database holds the properties of a variety of paving materials and establishes the analytical model. The back-analysis subsystem seeks to perform the tasks required for the analysis of the FWD deflection bowl. To build this system, the POPLOG-Prolog computer language operated under VAX/VMS was selected to work in connection with the analytical program. An evaluation procedure was carried out to investigate the performance characteristics of the prototype system. The results indicated that the POPLOG-Prolog development environment is not the ideal tool for such an application. In addition, it appears unlikely that there is any other development tool available which is markedly more effective than that used. However it is felt that similar functions to those required by the POPLOG-Prolog environment, may be implemented using conventional programming. To permit this, a logical design of a KBS to conduct this task is presented.

The performance of roads is known to progressively reduce as a result of separate and interactive effects of climate and traffic. Existing decision support tools such as HDM-4, which are widely used to investigate long-term road maintenance strategies, utilise past climate data instead of future climate predictions. Uncertainties inherent in future climate predictions however imply that application of such tools could lead to outputs that are not robust in light of climate change. The objectives of the study were threefold: firstly, to develop a rut depth prediction model that considered potential effects of future climate; secondly, to formulate a framework for quantification of uncertainties; and finally, to demonstrate the application of the tools developed using a case study. The model was developed using data provided by the UK Highways Agency and UK Climate Impacts Programme. The methodology used was based on Bayesian regression. The developed model was found to perform better than the current asphalt surfacing rut depth model implemented in HDM-4 when future climate data was used. It was concluded that probabilistic outputs from the tools developed including deterioration rates, pavement condition and discounted maintenance costs for each maintenance strategy, and future climate and socio-economic scenarios provide a useful decision making framework for considering alternative strategies for road maintenance on the basis of the level of climate change risks that can be tolerated.

No description available.

This research study intended to evaluate the impact of Local Government Performance Management System (PMS) on service delivery using Tshwane’s Roads and Stormwater division. / Graduate School of Business Leadership / (M.B.A.)

Flexible pavements are environmentally sensitive elements of infrastructure and their performance can be influenced by climate. Climate change poses a challenge to design and management of flexible pavements in the future. Climate change can occur worldwide and thus all flexible pavements can be exposed to the impact. However, an assessment framework is not available to evaluate the impact of climate change on flexible pavements in terms of performance, maintenance decision-making and the subsequent life-cycle costs (LCC). This research has attempted to develop such a framework. Case studies on six flexible pavement sections from the United States were performed to demonstrate the application of the framework. The framework started with the investigation of climate change using IPCC’s (Inter-governmental Panel on Climate Change) climate change projections. Combinations of climate change projections and local historical climate were adopted as climatic inputs for the prediction of pavement performance. The Mechanistic-Empirical Pavement Design Guide (MEPDG) was used for prediction of pavement performance because it can provide reliable performance predictions with consideration of climatic factors. Pavement performance predictions were applied to schedule maintenance interventions. Maintenance effects of treatments were considered in maintenance decision-making. Maintenance effect models of International Roughness Index (IRI) and rutting were validated using pavement condition survey data from Virginia. With selected climate related LCC components, three maintenance interventions were optimised using a genetic algorithm to achieve the minimum LCC. Eventually the outputs of the system including pavement performance, intervention strategies, and LCC can be compared under various climate change and baseline scenarios. Hence, the differences in performance, decision-making, and LCC due to climate change can be derived. The conclusions were drawn based on the scheme of maintenance decision-making. If flexible pavements are not maintained (Alternative 0), an increase in LCC will be incurred by climate change due to an increase in road roughness (IRI). For pavements maintained with strict thresholds (Alternative 1), climate change may lead to a significant reduction in the service life when the maintenance is triggered by climate sensitive distress. However, benefit can be gained from decreasing LCC as the earlier triggered maintenance may result in less average IRI. As a consequence, user costs, which can be associated with IRI, can be reduced. Hence, LCC can be reduced as user costs usually dominate LCC. However, the net present value (NPV) of agency costs can be increased due to the early intervention. For pavements with optimised maintenance (Alternative 2), the LCC is almost unaffected by climate change. However, the type or application time of interventions may need to be changed in order to achieve this. Furthermore, the balance between agency and user costs did not seem to be influenced by climate change for Alternative 2. Agencies should be aware that maintenance optimisation can significantly reduce the LCC and make the best use of treatments to mitigate the effects of climate change on flexible pavements. Pavement maintained with strict triggers may require earlier interventions as a result of climate change but can gain benefit in LCC. However, this indicates that a responsive maintenance regime may not take full advantage of interventions and that maintenance could be planned to be performed earlier in order to achieve minimised LCC. Due to climate change, road users may spend more on fuels, lubricants and tyre wear on flexible pavement sections that do not receive any maintenance treatments.

Nowadays, there is increasing number of facilities that implement various pricing strategies in order to manage increasing traffic demand. Most of these strategies use traffic data collected on several points in the system, aggregate them in certain aggregation interval and calculate tolls based on them. Some strategies derive performance measures (as traffic density) based on aggregated data, and define tolls. However, derived performance measures tend to underestimate traffic conditions and data aggregation interval can smooth traffic data. On the other hand, travel time has not been utilized in order to calculate user tolls on such systems, and yet it can directly measure users delay in the system, and directly capture field conditions. In addition, technology to collect travel times is becoming more popular and used in transportation systems. Hence, this study aims to test alternative methods for toll calculation that will rely on travel time data and compare their performance with currently utilized toll calculation algorithm on I-95 Express lanes in South Florida. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2019. / FAU Electronic Theses and Dissertations Collection