Probe speed data are widely used to calculate performance measures for quantifying state-wide traffic conditions. Estimation of the accurate performance measures requires adequate speed data observations. However, probe vehicles reporting the speed data may not be available all the time on each road segment. Agencies need to develop a good understanding of the adequacy of these reported data before using them in different transportation applications. This study attempts to systematically assess the quality of the probe data by proposing a method, which determines the minimum sample rate for checking data adequacy. The minimum sample rate is defined as the minimum required speed data for a segment ensuring the speed estimates within a defined error range. The proposed method adopts a bootstrapping approach to determine the minimum sample rate within a pre-defined acceptance level. After applying the method to the speed data, the results from the analysis show a minimum sample rate of 10% for Kentucky’s roads. This cut-off value for Kentucky’s roads helps to identify the segments where the availability is greater than the minimum sample rate. This study also shows two applications of the minimum sample rates resulted from the bootstrapping. Firstly, the results are utilized to identify the geometric and operational factors that contribute to the minimum sample rate of a facility. Using random forests regression model as a tool, functional class, section length, and speed limit are found to be the significant variables for uninterrupted facility. Contrarily, for interrupted facility, signal density, section length, speed limit, and intersection density are the significant variables. Lastly, the speed data associated with the segments are applied to improve Free Flow Speed estimation by the traditional model.

Emergency response times have been shown to be directly correlated with mortality rates of out-of-hospital patients. Studies have been conducted to show the relationship between time and mortality rates until patients receive the proper treatment. With more cardiac arrests and other life threatening illnesses occurring in the United States, more emergency calls will be required as well. As of today, technological advancements have been made to reduce response times, but human factors still require certain procedures, causing delays in the run time and increasing the rate of mortality. Here we show the results of emergency response times with the market penetration of connected and autonomous vehicles. With connected and autonomous vehicles, the average time emergency vehicles spend on the roadways can be significantly decreased. Safety procedures with human drivers can be eliminated, giving the emergency vehicle a proper right-of-way through virtual emergency lanes and removing the need to slow down and avoid vehicles at intersections or during periods of heavy congestion. Our results show a three minute decrease in response time under full market penetration of the technology, reducing the mortality rate and increasing the potential to save lives.

Road crashes are one of the main causes of death in the United States. To reduce the number of accidents, roadway assessment programs take a proactive approach, collecting data and identifying high-risk roads before crashes occur. However, the cost of data acquisition and manual annotation has restricted the effect of these programs. In this thesis, we propose methods to automate the task of roadway safety assessment using deep learning. Specifically, we trained convolutional neural networks on publicly available roadway images to predict safety-related metrics: the star rating score and free-flow speed. Inference speeds for our methods are mere milliseconds, enabling large-scale roadway study at a fraction of the cost of manual approaches.

In the 1976, the Institute of Transportation Engineers (ITE) compiled their first Handbook of guidelines and methods for evaluating development-level transportation impacts, specifically vehicular impacts (Institute of Transportation Engineers 1976). Decades later, these methods--essentially the same as when they were originally conceived--are used ubiquitously across the US and Canada. Only recently, with the guidelines in its third edition of the ITE's Trip Generation Handbook (Institute of Transportation Engineers 2014) new data and approaches have been adopted--despite substantial evidence that questions the accuracy of older data, automobile bias, and lack of sensitivity to urban contexts. This dissertation contributes to this literature by focusing on the data, methods, and assumptions so commonly included in development- or site-level evaluation of transportation impacts. These methods are omnipresent in development-level review--used in transportation impact analyses or studies (TIAs/TISs) of vehicular or mode-based impacts, vehicle miles traveled (VMT) and estimates of emissions, scaling or scoping development size, and evaluating transportation system development, impact or utility fees or charges. However, few have evaluated the underlying characteristics of these foundational data--with few exceptions--this manuscript takes aim at understanding inherent issues in the collection and application of ITE's data and methods in various urban contexts. This manuscript includes a compiled dissertation, four papers written consecutively. The first, evaluates state-of-the-art methods in Chapter 2--identifying gaps in the literature. Two such gaps are explored in Chapter 3 and Chapter 4. In Chapter 3, a larger implicit assumption present in ITE's methods--that the existing land-use taxonomy is an optimal and accurate way to describe land use and segment data. Results indicate a simplified taxonomy would provide substantial reductions in cost corresponding with a minor loss in the model's explanation of variance. Following, Chapter 4 explores a common assumption that requires ITE's vehicle trips be converted into person trips and applied across contexts. The results point to the need to consider demographics in site-level transportation impact analysis, particularly to estimate overall demand (person trips, transaction activity) at retail and service development. In Chapter 5, the findings from this research and previous studies are extrapolated to evaluate and quantify the potential bias when temporal, special, and social contexts are ignored. The results indicate the compounding overestimation of automobile demand may inflate estimation by more than 100% in contexts where ITE should be applicable (suburban areas with moderate incomes). In the conclusions (Chapter 6), the implications of this work are explored, followed by recommendations for practice and a discussion of the limitations of this research and future work.

Most safety analysis is conducted using crash data. Surrogate safety measures, such as various time-based measures of time-to-collision can be related to crash potential and used to gain insight into the frequency and severity of crashes at a specific location. One of the most common and acknowledged measures is post-encroachment time (PET) which defines the time between vehicles occupying a conflicting space. While commonly used in studies of motor vehicle interactions, studies of PET for bicycle-vehicle interactions are few. In this research, the PET of bicycle-vehicle interactions measured in the field, a driving simulator, and in a micro-simulation are compared. A total of 52 right-hook conflicts were identified in 135 hours of video footage over 14 days at a signalized intersection in Portland, OR (SW Taylor and SW Naito Pkwy). The results showed that 4 of 17 high-risk conflicts could not be identified by the conventional definition of PET and PET values of some conflicts did not reflect true risk of collision. Therefore, right-hook conflicts were categorized into two types and a modified measure of PET was proposed so that their frequency and severity were properly measured. PETs from the field were then compared to those measures in the Oregon State University driving simulator during research conducted by Dr. Hurwitz et al. (2015) studying the right-hook conflicts. Statistical and graphical methods were used to compare field PETs to those in the simulator. The results suggest that the relative validity of the OSU driving simulator was good but not conclusive due to differences in traffic conditions and intersections. To further explore the field-observed PET values, traffic simulation models of the field intersection were developed and calibrated. Right-hook conflicts were extracted from the simulation files and conflicts observed in PM-peak hours over 6 days in the field were compared to those obtained from 24 traffic simulation runs. The field-observed PET values did not match the values from the simulation values very well. However, the approach does show promise. Further calibration of driving and bicycling behaviors would likely improve the result.

Cracked pavement slabs lead to uncomfortable and eventual unsafe driving conditions for motorists. Replacement of cracked pavement slabs can interrupt traffic flow in the form of lane closures. In Florida, the traffic demands are high and pavement repairs need to be carried out swiftly typically using concrete with high cement contents and accelerators to create rapid setting and strength gain. The concrete used in these pavement replacements is usually accompanied by a high temperature rise, making the replaced slabs susceptible to cracking. Cracking is a result of developed tensile stresses in the concrete, which exceed the concrete's tensile strength capacity. This research is being conducted to determine the risk of cracking for pavement slabs with varying dosages of chloride based accelerator used to promote high early strength. To analyze the effect of the accelerator, five different concrete mixtures including a control were assessed in a series of tests with varying accelerator dosages. Experiments included: mortar cube testing, concrete cylinder testing, autogenous deformation measured with a free-shrinkage frame, and restrained stress analysis using a rigid cracking frame. The findings indicate that accelerators are necessary to meet the strength requirements, and that the higher the accelerator dose, the higher the early shrinkage in the first 24 hours determined from the free shrinkage frame. Accidental overdose of the chloride-based accelerator results in the highest cracking potential and the highest shrinkage when tested under field generated temperature profiles.

University of Macau / Faculty of Science and Technology / Department of Electromechanical Engineering

Mid-sized metropolitan areas face very different challenges and transportation planning issues than those faced by larger metropolitan areas. This is especially true in the area of safety conscious planning (SCP). Conflicting organizational cultures and limited staff and technical tools are major challenges in SCP efforts for mid-sized metropolitan areas (200,000 to 600,000 population). This study surveyed mid-sized metropolitan planning organizations (MPOs) and conducted seven case studies of mid-sized metropolitan areas to better understand the challenges and opportunities facing SCP in such a context. The national survey and case studies focused on long range planning, data collection, human resources, technical analysis, and collaboration aspects of SCP as applied today. The results indicate that the majority of mid-sized MPOs have incorporated safety consideration into their long range transportation plans vision, goals and objectives, but some mid-sized MPOs are more proactive in the quantitative analysis of project safety outcomes than others. The dissertation recommends that the institutional and technical issues faced by mid-sized MPOs can be overcome by engaging all government levels of planning in SCP efforts that identify a safety champion in the management ranks, encourage state departments of transportation to provide mid-sized MPOs with more tools and training in SCP, promote a stronger relationship between the Governor s Safety Representative and the MPO, and create a more comprehensive forum for collaboration among safety professionals.

This thesis investigates the effects of urban land use on transportation system performance in terms of various land use factors such as density, mixed or single land use, jobs-housing balance, street patterns, transit accessibility. Reviewed studies show that urban land use has considerable effects on transportation system performance measures which are average travel distances per person, level of service, air quality, gasoline consumption etc. Based on the obtained results, it is concluded that one of the basic reasons behind increasing auto dependency and outcoming problems in recent years is lack of coordination between land use and transportation system. The obtained results are used to analyze land use impacts on transportation system of Ankara. Urban transportation planning decisions, deficiencies in implementation and resulted problems are discussed in terms of land use and transportation interaction. Possible land use regulations which can contribute to relieve transportation problems of Ankara are proposed.

In this thesis, airline network revenue management problem is considered for the case with no cancellations and overbooking. In literature, there exist several approximate probabilistic and deterministic mathematical models developed in order to maximize expected revenue at the end of the reservation period. The aim of this study is to develop models considering also the risks involved in the proposed booking control policies. Two linear programming models are proposed which incorporate the variance of the revenue. The objective of the models is to effectively balance the tradeoff between the expectation and variance of the revenue. The performances of the proposed models are compared to the previous models through a numerical study. The seat allocations resulting from the mathematical models are used in a simulation model working with several booking control policies. The probability distributions of the revenues are investigated and the revenues are compared in terms of expectation, standard deviation, coefficient of variation and probability of poor performance. It is observed that the use of the proposed models decreases the variability of the revenue and thereby the risk of probability of poor performance. Also, the expected revenues obtained by implementing the solutions of the proposed models with nested booking control policies turn out to be higher than other probabilistic models as long as the degree of variance incorporation is within some interval. When compared with the deterministic models, the proposed models provides for the decision makers with alternative, preferable policies in terms of the expectation and the variability measures.