Since before the release of the Highway Safety Manual research has been indicating the need to incorporate mobility and control aspects to road safety analysis. The first part of this work developed and implement in an existing computational engine a signal timing optimization method that considers mobility, safety, and emissions measures simultaneously. A sensitivity analysis was conducted to provide insight on the practical effects and order of relevance of 20 key input variables. Mobility improvement performance usually coincides with emissions improvements, but sometimes at the expense of safety. The second part of this work investigated the relationship between hourly traffic density and crash rates on Brazilian expressways with different characteristics, based on a database containing over 20,000 crashes and more than 35 million traffic volume observations and. The resulting curves for urban expressways follow a U shape, with minimum values associated with LOS B to C, while the relationships for rural expressways were found to be continuously increasing, suggesting that low volume rural roads are safer than the higher volume ones. The analysis of other influencing factors revealed that nighttime conditions, weaving segments and urban multilane highways could be related to higher crash rates. The third part of the project extends the analysis to crash severity modeling, using an ordered response choice model. The framework that better fit this database led to the development of two different models: single-vehicle crashes (SV) and multiple-vehicle crashes (MV), since the factors that explain the severity of crashes varies widely between these models. For instance, guardrails and barriers proved to effectively reduce severity for SV crashes, for which run-offs are the most severe crash type. The unique database used in this study also allowed for an investigation of the influence of prevailing traffic conditions on crash severity, while still controlling for all other factors. The results suggested that multiple-vehicle crash severity is negatively related with traffic density, while single-vehicle crashes are more closely related to speed. The findings of this work have implications to policy and design decisions, and the produced equation could be incorporated to active traffic management (ATM) and HCM reliability analysis. / Desde antes da publicação do Highway Safety Manual, vários pesquisadores indicam a necessidade de se incorporar aspectos de operação de tráfego à análise de segurança viária. A primeira parte deste trabalho desenvolveu e implementou em uma ferramenta computacional existente um método de otimização de tempos semafóricos que considera medidas de desempenho de operação, segurança e emissões simultaneamente. Uma análise de sensibilidade foi realizada para produzir conhecimento sobre os efeitos práticos e a ordem de relevância de 20 variáveis de entrada principais. O desempenho da programação semafórica em termos de redução dos atrasos geralmente coincide com redução das emissões, embora às vezes às custas da segurança. A segunda parte deste trabalho investigou a relação entre a densidade horária de tráfego e as taxas de acidentes em autoestradas e rodovias de pista dupla brasileiras com características diversas, com base em um banco de dados contendo mais de 20.000 registros de acidentes e mais de 35 milhões de observações de tráfego. As curvas resultantes para rodovias urbanas seguem um formato em U, com valores mínimos associados aos níveis de serviço B a C, enquanto que as relações para as rodovias rurais são contínuas e crescentes, sugerindo que rodovias rurais de baixo volume são mais seguras do que as de maior volume. A análise de outros fatores revelou que condições noturnas, segmentos de entrelaçamento e rodovias de pista dupla convencionais urbanas estariam relacionadas a maiores taxas de acidentes. A terceira parte deste projeto amplia a análise para modelagem de severidade dos acidentes, usando um modelo de escolha discreta ordenado. A estrutura que melhor se adequa a esse banco de dados levou ao desenvolvimento de dois modelos diferentes: acidentes com um veículo e acidentes com múltiplos veículos, já que os fatores que explicam a severidade dos acidentes variam muito entre esses modelos. Por exemplo, defensas e barreiras se mostraram efetivas para a redução da severidade de acidentes com um veículo, para as quais a saída de pista é o tipo de acidente mais grave. O amplo banco de dados usado neste estudo também permitiu uma investigação da influência das condições de tráfego na severidade do acidente, em comparação com todos os outros fatores. Os resultados sugeriram que a severidade de acidentes de múltiplos veículos está negativamente relacionada com a densidade de tráfego, enquanto colisões com um único veículo estão mais relacionadas à velocidade. As descobertas deste trabalho têm implicações nas decisões sobre políticas e projetos de transportes, e a equação produzida pode ser incorporada à análise de confiabilidade do gerenciamento ativo do tráfego (ATM) e do Highway Capacity Manual.

Although public transit bus accounts for only a small percentage of the mode share for transportation in Florida, the annual passenger miles were over 1 billion with over 200 million passenger trips in 2005. These numbers warrant close attention to be paid to the safety of public transit vehicles. Despite the relatively low occurrence of fatalities and bus crashes, each crash of a high occupancy vehicle such as a public transit bus could expose more people to injury than a private automobile crash. Bus crashes also have a significant impact on the automobiles that are involved. Since a high percentage of bus crashes in Florida are caused by rear-end collisions with private automobiles, improving the signage and lighting that will allow buses to move back into traffic safely is very important for bus safety and operations. This paper uses bus operator surveys, crash data, and field studies to develop recommendations for lighting and signage on the back of the bus, roadway signs and revised Florida legislations. Improved signage and lighting will help the bus move back into traffic safely, decrease bus delay and improve bus operations however it must be accompanied by laws and law enforcement.

Two-way left-turn lane (TWLTL) is one of the common median treatments on the roadway. It is found that a number of crashes reported in Florida State are related to TWLTLs. This research focused on evaluating the effect of TWLTLs on these crashes by using the statistical crash prediction model that can estimate the expected number of crashes on TWLTLs. The crash database for analysis was extracted from the Florida Traffic Crash Database based on the TWLTL section list provided by FDOT and combined with some traffic characteristics. It consisted of totally 1688 sample sections within a three-year period from 1996 to 1998. Based on the crash database, distribution fittings for Poisson, Negative Binomial and Lognormal regression were conducted for average number of crashes. According to the results, statistical crash predictive model was developed to estimate the average number of crashes. Negative Binomial regression was applied with four variables, ADT, access density, posted speed and number of lanes for the TWLTL sections. The regression parameters were estimated by using maximum likelihood method with statistical software. The findings of the analysis indicated that all of the variables adopted in the predictive model significantly affect the occurrence of crashes. And the average number of crashes increases with the increase of ADT, access density and number of lanes, while with the decrease of posted speed. After that, the goodness-of-fit of developed model was performed in term of Pearson's R-square and likelihood ratio index. The results showed that the Negative Binomial regression model could explain the relationship between the variables and the crash occurrence In the third part, an approach was developed to identify the TWLTL sections with safety concern. For an undivided roadway, the approach can be carried out to judge if the TWLTL is appropriate to be selected as the median treatment. During the process, the whole database was divided into six categories according to the posted speed and number of lanes. By adopting the selected percentile value from the distribution of average number of crashes for each category in the predictive model, the critical ADT values according to specific access density, number of lane and posted speed level for each category were calculated and tabulated. With the comparison of the actual ADT value and the critical ADT value, if the actual ADT is higher than the critical value, the TWLTL section is determined as the critical section, which means the TWLTL is not appropriate to be selected as the median treatment in this roadway section.

<p>This thesis is devoted to understanding and counteracting the primary contributing factor in traffic crashes: inattention. Foremost, it demonstrates the fundamental importance of proactive gaze in the road centre area for action guidance in driving. Inattention is explained with regard to two visual functions (vision-for-action and vision-for-identification), three forms of attentional selection (action-driven-, stimulus-driven-, and goal-directed attention), and two forms of prediction influences (extrapolation-based- and decision-based prediction influences). In Study I an automated eye-movement analysis method was developed for a purpose-built eye-tracking sensor, and was successfully validated. This analysis method was further developed, and several new measures of gaze concentration to the road centre area were created. Study II demonstrated that a sharp decrease in the amount of road centre viewing time is accompanied by a dramatic spatial concentration towards the road centre area in returning gaze during visual tasks. During cognitive tasks, a spatial gaze concentration to road centre is also evident; however contrary to visual tasks, road centre viewing time is increased because the eyes are not directed towards an object within the vehicle. Study III found that gaze concentration measures are highly sensitive to driving task demands as well as to visual and auditory in-vehicle tasks. Gaze concentration to the road centre area was found as driving task complexity increased, as shown in differences between rural curved- and straight sections, between rural and motorway road types, and between simulator and field motorways. Further, when task duration was held constant and the in-vehicle visual task became more difficult, drivers looked less at the road centre area ahead, and looked at the display more often, for longer periods, and for more varied durations. In closing, it is shown how this knowledge can be applied to create in-vehicle attention support functions that counteract the effects of inattention.</p>

This thesis is devoted to understanding and counteracting the primary contributing factor in traffic crashes: inattention. Foremost, it demonstrates the fundamental importance of proactive gaze in the road centre area for action guidance in driving. Inattention is explained with regard to two visual functions (vision-for-action and vision-for-identification), three forms of attentional selection (action-driven-, stimulus-driven-, and goal-directed attention), and two forms of prediction influences (extrapolation-based- and decision-based prediction influences). In Study I an automated eye-movement analysis method was developed for a purpose-built eye-tracking sensor, and was successfully validated. This analysis method was further developed, and several new measures of gaze concentration to the road centre area were created. Study II demonstrated that a sharp decrease in the amount of road centre viewing time is accompanied by a dramatic spatial concentration towards the road centre area in returning gaze during visual tasks. During cognitive tasks, a spatial gaze concentration to road centre is also evident; however contrary to visual tasks, road centre viewing time is increased because the eyes are not directed towards an object within the vehicle. Study III found that gaze concentration measures are highly sensitive to driving task demands as well as to visual and auditory in-vehicle tasks. Gaze concentration to the road centre area was found as driving task complexity increased, as shown in differences between rural curved- and straight sections, between rural and motorway road types, and between simulator and field motorways. Further, when task duration was held constant and the in-vehicle visual task became more difficult, drivers looked less at the road centre area ahead, and looked at the display more often, for longer periods, and for more varied durations. In closing, it is shown how this knowledge can be applied to create in-vehicle attention support functions that counteract the effects of inattention.

In roadway projects, design exceptions are implemented when the project site consists of one or more substandard design elements. The objective of this thesis is to conduct an initial investigation for a monitoring program for the safety performance of design exceptions in Georgia. A total of 467 projects containing design exceptions were reported in Georgia from 1995 to 2011, and from this crash data for 179 projects from 2003 to 2008 were sampled. The crash data collected in this research pertains to all roadway segments within the projects and is not necessarily related to the design exceptions. Future efforts will be required to explore potential connections between the crash rates and design exceptions. The annual crash results generally revealed a high variability and randomness in the data. For this reason, the average 3-year crash frequencies before design exception approval date and after it were calculated to determine the safety performance for projects containing design exceptions. A method for determining expected results using the Highway Safety Manual (HSM) predictive method is also discussed. The findings will be used to guide future research on design exceptions and mitigation measures to improve roadway safety.

Analyses of traffic accidents are often focused on the characteristics of the accident event and hence do not take into account the broader neighborhood contexts in which accidents are located. This thesis seeks to extend empirical analyses of accidents by understanding the link between accidents and their surroundings. The case study for this thesis is Hillsborough County, Florida, within which the city of Tampa is located. The Tampa Bay region ranks very high in terms of accident rates within U.S. metropolitan areas and is also characterized by transport policies which favor private automobiles over mass transit options, making it an especially valuable case study. This thesis seeks explanations for accidents through regression models which relate accident occurrence and accident rates to traffic, roadway and socioeconomic characteristics of census tracts. The overall findings are that socioeconomic variables, especially poverty rates and percent non-white, and transport characteristics, such as density of bus stops, show a significant relationship with both dependent variables. This research provides support for considering the wider urban context of social inequalities in order to understand the complex geographic distribution of accidents.

Safety at intersections is of significant interest to transportation professionals due to the large number of possible conflicts that occur at those locations. In particular, rural intersections have been recognized as one of the most hazardous locations on roads. However, most models of crash frequency at rural intersections, and road segments in general, do not differentiate between crash type (such as angle, rear-end or sideswipe) and injury severity (such as fatal injury, non-fatal injury, possible injury or property damage only). Thus, there is a need to be able to identify the differential impacts of intersection-specific and other variables on crash types and severity levels. This thesis builds upon the work of Bhat et al., (2013b) to formulate and apply a novel approach for the joint modeling of crash frequency and combinations of crash type and injury severity. The proposed framework explicitly links a count data model (to model crash frequency) with a discrete choice model (to model combinations of crash type and injury severity), and uses a multinomial probit kernel for the discrete choice model and introduces unobserved heterogeneity in both the crash frequency model and the discrete choice model, while also accommodates excess of zeros. The results show that the type of traffic control and the number of entering roads are the most important determinants of crash counts and crash type/injury severity, and the results from our analysis underscore the value of our proposed model for data fit purposes as well as to accurately estimate variable effects. / text

Young adults' risk-taking attitudes, risk perception, and knowledge of road laws and signs influence their driving behaviors. The adoption of risky driving behaviors increases young adults' risk of motor vehicle crashes. The purpose of this study was to increase the understanding of the factors that lead to increased risks of MVC-related mortality and morbidity for young adults in Belize, to provide support for the development of evidence-based programs, and, more importantly, to investigate the relationships involving young adults' risk-taking attitudes, risk perception, and knowledge of road laws and signs and their relation to driving behaviors. The Precaution Adoption Process Model provided the theoretical foundation for this study and was used as the framework to investigate the variables of interest. This study used a nonexperimental, cross-sectional research design to examine the relationships between the latent variables. A convenience sample of 532 students enrolled at the University of Belize participated in this study. Data were collected through the completion of the Driving Behavior Survey. Structural equation modeling was used to examine the strength and direction of relationships among these latent variables and provide a better understanding of the relationships among these latent variables. The study found that the majority of students were in the final stages of the Precaution Adoption Process Model and were exhibiting the safest behaviors. However, the risk-taking attitudes significantly contributed to the manifestation of risky driving behavior and to a lesser extent so did risk perception. The study's findings suggest that interventions should focus on lowering young adults' risk-taking attitudes and raising risk perception to reduce risky driving behaviors.

The well-being of tourists or visitors within a destination has, until recently, received little attention. Issues relating to the personal safety and health of the travelling public have been highlighted by a number of high profile incidents of terrorist attacks, large scale natural disasters and life threatening epidemics. While such events are devastating in nature and of great concern, for the majority of travellers, health and personal safety are more likely to be impacted on by illness, being involved in an accident or becoming the victim of crime. This thesis contributes to our existing understanding of how tourism can be affected by incidents by selecting a definable geographical area and investigating the available data from official sources to examine the dimensions, scale and nature of visitor-related incidents of crime, road traffic accidents and emergency health care. This audit was undertaken through collaborative research with the Central Scotland Police Force, the Central Scotland Road Accident Investigation Unit and the National Health Service Forth Valley. Primary research was then undertaken with visitors to the area. This in-depth approach looks beyond existing statistics to probe factors contributing to visitor-related incidents, in relation to existing tourism literature. The results indicate that, visitors experience incidents that differ in nature and type from those experienced by local residents, and the times and places they were most at risk also varied. With visitors accounting for less than 10% of the total population, these differences are not apparent in the overall patterns and, therefore, the particular needs of visitors are unlikely to be met through existing measures. This research has the ability to form the basis of improved measures to benefit visitor health and personal safety even though the nature of the visiting population presents challenges in relation to when, where and how such preventative measures are introduced. Visitors are not homogenous and distinct groupings based on perceptions, attitudes and behaviours were found. Therefore, there is a requirement to examine how incidents impact on visitors by distinguishing them from the overall incident figures, but measures to protect visitors also have to be tailored to take cognisance of typologies of visitors.