The Flashing Yellow Arrow Left Turn signal is quickly becoming prominent in Central Florida as a new method of handling left turns at traffic signals. While the concept of a protected-permitted left turn is not groundbreaking, the departure from the typical display of a five-section signal head is, for this type of operation. The signal head introduced is a four-section head with a flashing yellow arrow between the yellow and green arrows. With this signal head quickly becoming the standard, there is a need to re-evaluate the operational characteristics of the left turning vehicle and advance the knowledge of the significant parameters that may affect the ability for a driver to make a left turn at a signalized intersection. With previous research into the behavioral and operational characteristics of the flashing yellow arrow conducted, there is more information becoming available about the differences between this signal and the previously accepted method of allowing left turns at an intersection. The protected-permitted signal is typically displayed at an intersection with up to two through lanes and generally a protected signal is installed when the number of through lanes increases above two unless specific criteria is met. With the advent of larger arterials and more traffic on the highway networks, the push to operate these intersections at their maximum efficiency has resulted in more of these protected-permitted signals being present at these larger intersections, including the flashing yellow arrow. The core of the research that follows is a comparative analysis of the operation and parameters that affect the left turn movement of the intersection with larger geometry to that of the smaller geometry. The significant parameters of the left turn movement were examined through means of collecting, organizing and analyzing just over 68 hours of field data. This research details the determining of the significant parameters based on the generation of a simulation model of the protected left turn using Synchro, a traffic simulation package, and regression models using field driven data to determine the significant parameters for predicting the number of left turns that can be made in the permitted phase under specific operating conditions. Intuitively, there is an expectation that a larger intersection will not allow for as many permitted lefts as a smaller intersection with all conditions remaining the same. The conclusions drawn from this analysis provide the framework to understanding the similarities and the differences that are encountered when the intersection geometry differs and help to more efficiently manage traffic at signalized intersections. The work of this field promises to enhance the operations of the left turning movement for traffic control devices. With an understanding of the statistical models generated, a broader base of knowledge is gained as to the significant parameters that affect a driver's ability to make the left turn. A discussion of the statistical differences and between the models generated from the small and large geometry intersections is critical to drive further research into standards being developed for the highway transportation network and the treatment of these large signalized intersections. The exploration of specific parameters to predict the number of permitted left turns will yield results as to if there is more to be considered with larger intersections moving forward as they become a standard sight on the roadway network.

The standard method for assessing traffic safety is to use the predictive method outlined in the Highway Safety Manual (HSM). This method is site-level, data-intensive, and does not account for interactions between sites, making it difficult to assess larger areas. This dissertation develops a corridor-level approach to traffic safety which uses less data than the HSM predictive method and views roadways holistically rather than combinations of individual, independent sites. First, a corridor definition is developed and applied to 10 urban Florida counties with a history of many crashes, resulting in the identification of 1,048 corridors. These corridors were primarily defined using context classification and lane count, with additional considerations for data availability and minimum length. From 2017–2021, these corridors experienced 459,603 unique crashes. After preliminary modeling and scope refinement, 559 corridors received supplemental data collection. Between the two datasets, a total of 11 models were developed using either negative binomial (NB) or random forest (RF) regression. NB models can be used for network screening purposes or identifying the impacts of potential safety improvements, while RF models can be used to identify variables important to the accuracy of the prediction. Potential safety improvements identified from the NB models include increasing proactive law enforcement patrols for dangerous driving behaviors and installing corridor lighting in corridors without lighting. While both NB and RF models were accurate, NB models were recommended due to resulting in a definite equation and overdispersion parameter that could be used with the empirical Bayes (EB) method to improve prediction accuracy. Overall, the corridor-level NB models outperformed the HSM models in terms of accuracy and statistical reliability. Using a corridor-level approach can help agencies quickly network screen their systems to identify high-risk corridors in need of safety improvements or supplement site-level analyses.

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Highway roughness is a concern for both the motoring public and highway authorities. Roughness may even increase the risk of crashes. Rail-highway grade crossings are particularly problematic. Roughness may be due to deterioration or simply due to the way the crossing was built to accommodate grade change, local utilities, or rail elevation. With over 216,000 crossings in the US, maintenance is a vast undertaking. While methods are available to quantify highway roughness, no method exists to quantitatively assess the condition of rail crossings. Conventional inspection relies on a labor-intensive process of qualitative judgment. A quantifiable, objective and extensible procedure for rating and prioritizing improvement of crossings is thus desired. In this dissertation, a 3D infrastructure condition assessment model is developed for evaluating the condition and performance of rail highway grade crossings. Various scanning techniques and devices are developed or used to obtain the 3D “point cloud” or surface as the first step towards quantifying crossing roughness. Next, a technique for repeatable field measurement of acceleration is presented and tested to provide a condition index. Acceleration-based metrics are developed, and these can be used to rate and compare crossings for improvement programs to mitigate potential vehicle damage and provide passenger comfort. A vehicle dynamic model is next customized to use surface models to estimate vertical accelerations eliminating the need for field data collection. Following, crossing roughness and rideability is estimated directly from 3D point clouds. This allows isolation of acceleration components derived from the surface condition and original design profile. Finally, a practice ready application of the 3D point cloud is developed and presented to address hump crossing safety. In conclusion, the dissertation presents several methods to assess the condition and performance of rail crossings. It provides quantitative metrics that can be used to evaluate designs and construction methods, and efficiently implement cost effective improvement programs. The metrics provide a technique to measure and monitor system assets over time, and can be extended to other infrastructure components such as pavements and bridges.

Merging from on-ramps to mainline traffic is one of the most challenging driving maneuvers on freeways. The challenges are further heightened for older drivers, as they are known to have longer perception-reaction times, larger acceptance gaps, and slower acceleration rates. In this research, VISSIM, a microscopic traffic simulation software, was used to evaluate the influence of the aging drivers on the operations of a typical diamond interchange. First, drivers were recorded on video cameras as they negotiated joining the mainline traffic from an on-ramp acceleration lane at two sites along I-75 in Southwest Florida. Several measures of effectiveness were collected including speeds, gaps, and location of entry to the mainline lanes. This information was used as either model input or for verification purposes. Two VISSIM models were developed for each site – one for the existing conditions and verification, and another for a sensitivity analysis, varying the percentage of older drivers and Level of Service (from A to E), to determine their influence on ramp operational characteristics. According to the results, there was a significant difference in driving behavior between older, middle-aged, and younger drivers, based on the measures of effectiveness analyzed in this study. Additionally, as the level of service and percentage of older adult motorists increased, longer queues were observed with slower speeds on the acceleration lanes and the right-most travel lane of the mainline traffic.

O ônibus ainda é o modo de transporte público mais usado nas cidades brasileiras, mesmo aquelas que contam com sistemas sobre trilhos extensos. Já centenários, os sistemas de ônibus urbanos ainda se debatem na peleja diária da competição com os demais veículos e na busca de uma imagem mais favorável perante a seus usuários e à população. O advento do ferramental de Sistemas Inteligentes de Transporte (ITS) ofereceu a oportunidade de que esses sistemas pudessem contar com instrumentos de Planejamento, Programação, Monitoração e Controle Operacional próximos àqueles que os sistemas metroferroviários já dispõem há muitas décadas. Entre os vários avanços proporcionados pelo emprego de ITS no campo operacional, destacam-se as intervenções operacionais em tempo real, isto é, a aplicação de medidas que buscam oferecer ou restabelecer a regularidade e a eficiência da operação dos ônibus urbanos frente a contingências que eles enfrentam diariamente. Este trabalho objetiva fazer uma resenha das diversas opções de intervenções estudadas no campo acadêmico e executar simulações de três modalidades dessas estratégias. Foi construída uma rede reproduzindo um trecho de Corredor de ônibus na cidade de São Paulo e simulada a operação de uma linha de alta demanda, com base nos dados reais da operação, do trânsito (semáforos) e velocidades de percurso dos ônibus. A simulação, por sua vez, permitiu apurar os benefícios propiciados pelas intervenções testadas, chegando aos ganhos de tempos nas viagens e o possível aumento de oferta de veículos sem aumento da frota. Além de comparar os resultados entre os tipos de intervenção, foi verificada a sensibilidade dos resultados de cada estratégia a mudanças na intensidade de sua aplicação.Os resultados enquadram-se na faixa dos resultados obtidos nos diversos experimentos acadêmicos analisados. Dentro das expectativas, a intervenção das Meias Viagens (\"deadheading\") apresentou melhores resultados nos ganhos de tempos de viagem variando entre 8,5% e 12,9%, secundados pelas Paradas Limitadas (\"skip-stop\") variando entre 2,9% e 4,7%, enquanto a Linha Expressa apresentou resultados menores, motivados, principalmente, pelas limitações da extensão do trecho analisado. / Buses are still the most common transit mode in Brazilian cities even in those that count with extensive rail systems. Century old city bus operations still struggle daily to compete with other road vehicles while trying to gain a better image before its users and the general public. The arrival of Intelligent Transportation System (ITS) solutions brought to these systems the opportunity of counting on Operational Planning, Programing, Monitoring and Control like those already used by rail transit for decades. Among several improvements possible using ITS real time intervention during operation stands out. This enables the application of measures to offer or restore regularity and efficiency of bus services in face of contingencies faced daily. This paper aims to review different options of intervention reported in academic publications and to perform simulations of three of these strategies. A network was modeled duplicating a real Sao Paulo bus corridor section on which a high demand bus line operation, based on actual operation data, traffic, traffic lights and bus speeds, was studied. The simulation, in turn, allowed us to assess the benefits of each alternative intervention tested by determining travel time gains and the increase in bus service supply without increasing the operating fleet. Besides comparing results between intervention types the sensitivity of each one\'s results to strategy application intensity was also reached. The final experiments results fall within the range of those obtained in several other academic studies analyzed. Within the expectations, the deadheading intervention presented better results in travel time gains ranging from 8.5% to 12.9%, followed by the skip-stop, ranging from 2, 9% and 4.7%, while the Express Line presented lower results motivated, mainly, by the limitations of the extension of the analyzed section