Second, this research investigates lane-specific traffic behavior through empirical analysis and statistical modeling of lane flow distribution. Lane-specific traffic behavior is also an important component in evaluating freeway performance and has a significant impact in the mechanism of queue evolution, particularly around merges, and bottleneck discharge rate. In this research, site-specific linear LFD trends of three-lane congested freeways were investigated and modeled. A large-scale data collection process was implemented to systematically characterize the effects of several traffic and geometric features of freeways in the occurrence of between-site LFD variations. Also, an innovative three-stage modeling framework was used to model LFD behavior using multiple logistic regression to describe between-site LFD variations and Dirichlet regression to model recurrent combinations of linear LFD trends. This novel approach is able to represent both between and within site variations of LFD trends better, while accounting for the unit-sum constraint and distribution assumptions inherent of proportions data. Results revealed that proximity to freeway merges, a site’s level of congestion, and the presence of HOV lanes are significant factors that influence site-specific recurrent LFD behavior.
Findings from this work significantly improve the state-of-the-art knowledge on merging and lane-specific traffic behavior, which can help to improve traffic operations and reduce traffic congestion in freeways.
In this research effort, a reliability framework is developed using Monte Carlo simulation for predicting the fatigue life of AC material using the S-VECD model. The reliability analysis reveals that the fatigue life prediction is very sensitive to the uncertainty in the input variables. FAM testing in similar loading conditions as AC, and upscaling of AC modulus and damage response using FAM properties from a relatively simple homogenized continuum approach shows promising results. The FAM phase fatigue life prediction and upscaling of FAM results to AC show more reliable fatigue life prediction than the fatigue life prediction of AC material using its experimental data. To assess the sensitivity of fatigue life prediction model to uncertainty in the input variables, a parametric sensitivity study is conducted on the S-VECD model. Overall, the findings from this research show promising results both in terms of upscaling FAM to AC properties and the reliability of fatigue prediction in AC using experimental data on FAM.
There is a growing need to quantify the project performance and financial benefits of PPP. This dissertation fills this gap in knowledge by performing a comprehensive quantitative analysis of PPP project performance and financial sources for transportation projects in the U.S. This study’s specific research objectives are:
(1) Develop a solid baseline for comparison, comprised of non-PPP projects;
(2) Quantify PPP project cost and schedule performance; and
(3) Quantify private versus public financing sources of PPP.
A thorough literature review led to the development of a structured data collection process for PPP and comparable non-PPP projects. Financing data was collected and verified for a total of 133 ongoing and completed projects; while performance data was verified for a subset of 81 completed projects. Data analysis included regression analysis, descriptive statistics, inferential statistics and non-parametric statistical tests.
The results provide benchmarks for PPP project performance and financing sources. For the performance results, non-PPP projects have an average cost change of 8.46 percent and an average schedule change of -0.22 percent. PPP projects have an average cost change of 3.04 percent and average schedule change of 1.38 percent. Statistical analysis showed cost change for PPP projects were superior to that of non-PPP; however, schedule change differences were not significant. For the financing results, private financing totaled 44.5 percent while public financing totaled 55.5 percent. This result shows private financing can be used to leverage public financing with close to a one-to-one ratio and that PPP has the potential to double the amount of infrastructure delivered to the public.
Crack sealing is considered one of the least expensive and cost effective maintenance activity used on pavements. In some cases, crack sealing suffers from premature failure due to various material, environmental, and construction issues. A survey that was conducted as part of this study showed that the highest sealant failure year occurring on the second year. Therefore, any attempt to increase the sealants’ service life by addressing and improving the sealant properties and their resistance to failure will benefit the effectiveness of this treatment.
The goal behind this study was to evaluate the potential improvement in performance of hot applied sealant material commonly used in the Phoenix area, and evaluate the performance of using a neat binder modified with crumb rubber (at 5 and 10% by weight of binder) as a low-grade sealing material. The sealants was also modified with crumb rubber at 2.5, and 5% by weight fo the sealant. Six ASTM tests were conducted for the comparison. These tests are the Standard Penetration Test (SPT) and Cone Penetration Test (CPT), Resilience Test, Softening Point Test, Brookfield Viscometer Test, and Dynamic Shear Rheometer (DSR).
The results showed that adding only crumb rubber to a neat binder for its potential use as a crack sealant is inadequate to meet the specifications expected for sealants. However, the modification of the sealant with crumb rubber showed some benefits, such as increased elasticity and decreased temperature susceptibility. A crumb rubber content of 2.5% by weight of the sealant was recommended.
Findings indicate that the deployment of green roofs will cool the urban environment in daytime and warm it at night, via evapotranspiration and soil insulation. At the annual scale, green roofs are effective in decreasing building energy demands for both summer cooling and winter heating. For cities in arid and semiarid environments, an optimal trade-off between water and energy resources can be achieved via innovative design of smart urban irrigation schemes, enabled by meticulous analysis of the water-energy nexus. Using water-saving plants alleviates water shortage induced by population growth, but comes at the price of an exacerbated urban thermal environment. Realizing the potential water buffering capacity of urban green infrastructure is crucial for the long-term water sustainability and subsequently multisector sustainability of cities. Environmental performance of urban green infrastructure is determined by land-atmosphere interactions, geographic and meteorological conditions, and hence it is recommended that analysis should be conducted on a city-by-city basis before actual implementation of green infrastructure.
The activity-based approach to travel demand analysis and modeling, which has been developed over the past 30 years, has received tremendous success in transportation planning and policy analysis issues, capturing the multi-way joint relationships among socio-demographic, economic, land use characteristics, activity participation, and travel behavior. The development of synthesizing population with an array of socio-demographic and socio-economic attributes has drawn remarkable attention due to privacy and cost constraints in collecting and disclosing full scale data. Although, there has been enormous progress in producing synthetic population, there has been less progress in the development of population evolution modeling arena to forecast future year population. The objective of this dissertation is to develop a well-structured full-fledged demographic evolution modeling system, capturing migration dynamics and evolution of person level attributes, introducing the concept of new household formations and apprehending the dynamics of household level long-term choices over time. A comprehensive study has been conducted on demography, sociology, anthropology, economics and transportation engineering area to better understand the dynamics of evolutionary activities over time and their impacts in travel behavior. This dissertation describes the methodology and the conceptual framework, and the development of model components. Demographic, socio-economic, and land use data from American Community Survey, National Household Travel Survey, Census PUMS, United States Time Series Economic Dynamic data and United States Center for Disease Control and Prevention have been used in this research. The entire modeling system has been implemented and coded using programming language to develop the population evolution module named `PopEvol' into a computer simulation environment. The module then has been demonstrated for a portion of Maricopa County area in Arizona to predict the milestone year population to check the accuracy of forecasting. The module has also been used to evolve the base year population for next 15 years and the evolutionary trend has been investigated.