Over the last 20 to 30 years, there have been a significant number of statistical methods proposed for analyzing crash data. Traffic crashes are characterized as random and independent discrete non-negative events. Crash data have often been shown to exhibit over-dispersion. Therefore, the Negative Binomial (NB) is the preferred and widely used model to analyze this kind of data. Although NB model is very popular in traffic safety area, it still has limitations modeling crash data especially when crash data are characterized by low sample mean and small sample size. The main research objective of this thesis is to develop a new statistical method namely, Poisson-Weibull (PW) Generalized Linear Model (GLM) to analyze vehicle crash data and to evaluate its modeling performance at different dispersion levels. This study makes use of both simulated and observed data for accomplishing the research objectives. The PW model is the mixture of Poisson and Weibull distributions. In this research, the statistical characteristics of the PW model were well defined and the parameters were estimated using a Bayesian approach. The PW model was initially evaluated using a series of simulated data for different dispersion levels. It was found that the PW model was able to reproduce and capture the true parameter values with high accuracy. After the initial analysis using the simulated data, the PW GLM was applied to two observed datasets and compared with the NB model. The goodness-of-fit (GOF) tests and model comparisons showed that the PW model performed as well as the NB model. Therefore, the PW model can be considered as an innovative and promising alternative for analyzing crash data.

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Signalized Intersections on the State Roads in Hillsborough and Pinellas County, Florida with observed left turn lane overflow (spill) were selected for a safety and operational study. The study analyzed the crash data for safety hazards that the situation presents. Crashes within 100 feet from the center line of the crossroad of intersections under study to distances 200 feet beyond the end of the turn lane were chosen for the analysis. Left turn overflow is the situation at the approach of an intersection where left turning vehicles back up from the turn lane into the through traffic lane. Crashes within the intersection legs with the left turn lane overflow problems resulted in more crashes than the intersection legs without the spill problem at 95 percent confidence level. However the result was not overwhelming when 3 leg intersections are combined with 4 leg intersections. The rush periods within the leg of the intersection where left turn overflow occurred did not seem to have any correlation at all using paired t test.

Traumatic brain injuries (TBIs) are injuries to the brain associated with the transfer of energy from some external source. There are an estimated 1.4 million TBIs each year, and about half are due to transportation crashes (NINDS, 2007). Driver distraction is defined as a process or condition that draws a driver's attention away from driving activities toward a competing activity (Sheridan, 2004) and has been identified as an under-examined issue for TBI populations (Cyr, et al., 2008). The interaction between the cognitive impairments related to TBIs and the competing demands from driver distraction may be especially problematic. The goal of this dissertation is to investigate the effect of driver distraction on individuals with TBI. This dissertation uses several approaches and data sources: crash data, a TBI registry, a survey of TBI drivers, and an on-road driving study of TBI and non-TBI drivers. Results demonstrate that a subset of TBI drivers are more willing to engage in distracting tasks and they are more likely to have received speeding tickets. TBI drivers involved in crashes were less likely to wear seatbelts and were more likely to be involved in multiple crashes compared to all other drivers in crashes. Additionally, a subset of TBI drivers exhibits more risk-taking while driving that may result from the TBI or a predisposition to take risks. A Bayesian approach was used to analyze the effect of distracting tasks on driving performance of TBI drivers in an on-road study. A simulator study of non-TBI drivers was used to develop prior distributions of parameter estimates. The distracting tasks include a CD selecting task, a coin sorting task, and a radio tuning task. All of the tasks contained visual-manual components and the coin sorting task contained an additional cognitive component associated with counting the currency. This suggests that TBI drivers exhibited worse driving performance during a coin sorting task than the non-TBI drivers in terms of the standard deviation of speed and maximum lateral acceleration of the vehicle. This suggests that the cognitive component of the coin sorting task may be causing the decreased performance for the TBI drivers. Across all tasks, TBI drivers spent a larger percent of the task duration looking at the task with a larger number of glances towards the distraction task than the non-TBI drivers. Driver distractions with cognitive components may be especially problematic for TBI drivers. Future work should investigate if this effect is consistent across more complex cognitive driver distraction tasks (e.g., cell phone usage) for this population. Additionally, future work should validate the high proportion of TBI drivers involved in multiple crashes.

Since 2014, a distinction between Pedelec (electrical support up to 25 km/h) and bicycle crashes is made in official police reported accidents with personal injuries in Germany. Yet, no comparative analysis using national data is available, moreover some estimation was done how Pedelec crashes may look like based on bicycle crashes. Hence, the present study aims to compare real-world crashes with personal injuries with both vehicle types - Pedelec and bicycle and show similarities and differences of the vehicle classes. Nearly a decade of reporting allows furthermore to have a closer look at the accident figures in a time series and to estimate possible trends.

This research sought to understand the relationship between licensing policy and the opportunity for the development of a scientifically-based approach to identifying high risk older drivers based on prior driving history. This research focused on five tasks: 1) review of the literature, 2) compilation of information on licensing policy for use by decision-makers, 3) assessment of charges and payer source for older driver crashes using linked crash and hospital data , and 4) the development and 5) validation of an older driver crash prediction model. There is relatively little available in the way of information for policymakers regarding licensing, and there is even less information available on evaluation of licensing practice effectiveness. Emergency department charges for older males were lower than females even though males accounted for a larger percentage of the injured population. Older drivers were no more likely to be covered by public insurance than the comparison group. Crash and citation data used to develop a driver history showed no differences between drivers in injury causing crashes and drivers in non-injury crashes. Logistic regression, Poisson regression, and negative binomial regression models were unable to effectively predict crash involvement based on driver history. This is likely due to self-selection bias for older drivers and truncated distribution of count variable (injury causing crashes). Recommendations resulting from this research include Massachusetts and national policy recommendations and additional research. Massachusetts should expand beyond its referral-based system for reviewing older drivers, consider restriction rather than only revocation, review medical advisory board practices, conduct evaluation of any policies it does implement, and conduct a thorough review of alternative transportation options. Nationally, efforts should focus on developing effective cognitive/functional testing by licensing agents, identification of effective second phase of testing, determination of a mechanism for determining when to retest, and assessment of the differences between older males and females for potential use in training, education, and testing. Research recommendations include continued exploration of the potential for systematic identification of high risk drivers using administrative data and in-depth analyses of the differences between males and females in terms of aging and driver safety.

Doctor of Philosophy / Department of Civil Engineering / Sunanda Dissanayake / Young drivers have elevated motor vehicle crash rates compared to other drivers. This dissertation investigated characteristics, contributory causes, and factors which increase the injury severity of young driver crashes in Kansas by comparing them with more experienced drivers. Crash data were obtained from the Kansas Department of Transportation. Young drivers were divided into two groups: 15-19 years (teen) and 20-24 years (young adult) for a detailed investigation. Using data from 2006 to 2009, frequencies, percentages, and crash rates were calculated for each characteristic and contributory cause. Contingency table analysis and odds ratios (OR) analysis were carried out to identify overly represented factors of young-driver crashes compared to experienced drivers. Young drivers were more likely to be involved in crashes due to failure to yield-right-of way, disregarding traffic signs/signals, turning, or lane changing, compared to experienced drivers. Ordered logistic regression models were developed to identify severity affecting factors in young driver crashes. According to model results, factors that decreased injury severity of the driver were seat belt use, driving at low speeds, driving newer vehicles, and driving with an adult passenger. The models also showed that alcohol involvement, driving on high-posted-speed-limit roadways, ejection at the time of crash, and trapping at the time of crash can increase young drivers’ injury severity. Based on identified critical factors, countermeasure ideas were suggested to improve the safety of young drivers. It is important for teen drivers and parents/guardians to gain better understanding about these critical factors that are helpful in preventing crashes and minimizing driving risk. Parents/guardians can consider high-risk conditions such as driving during dark, during weekends, on rural roads, on wet road surfaces, and on roadways with high speed limits, for planning teen driving. Protective devices, crash-worthy cars, and safer road infrastructures, such as rumble strips, and forgiving roadsides, will particularly reduce young drivers’ risk. Predictable traffic situations and low complexity resulting from improved road infrastructure are beneficial for young drivers. The effectiveness of Kansas Graduated Driver Licensing (GDL) system needs to be investigated in the future.

This work deals with the impact of selected electronic chassis systems of modern vehicles, their driving dynamics. The general aim of this work is to create the basic methodology for assessing casualties of the influence of these systems. The thesis is describing functions and effects antilock and stability systems on vehicle dynamics. Below are possible methods and systems for determining the influence on accident plot. As part of the study was performed measuring the impact of anti-lock system on the vehicle. The result of this work is the basic methodology to the analysis of road accidents involving vehicles with electronic chassis systems.

This research assessed the criminological significance of motor vehicle crash data within the criminal justice context. The study was conducted at the southern region Accident Bureau of the Ekurhuleni Metropolitan Police Department (EMPD). The objectives of this research are to: a. Explore and describe the extent and criminological impact of road traffic crashes on a macro level. b. Explore and describe the impact of road traffic crashes on a micro level. c. Explain the criminological significance of road traffic crash data in relation to effective road safety management. d. Evaluate and describe the attendance and recording procedure of road crashes. e. Evaluate and describe the supervisor’s responsibility in relation to the quality of crash data recorded. f. Evaluate and describe the effectiveness of crash statistics accessed by management and/or officials. g. Evaluate and explain the current prosecution procedure as part of the CJS. h. Evaluate existing policy about the crash-recording process applicable to operational law enforcement practitioners of the EMPD. i. Explore and describe the current state of motor vehicle insurance and its necessity from a criminological perspective. The researcher followed a mixed-methods approach, collecting quantitative data from recorded Accident Report Forms and qualitative data from interviews with participants active in their fields of expertise. Road crashes are characterised by injury and damage; victims suffer trauma and economic consequences, and the society and the economy as a whole are affected. The research suggests that accurate road crash data form a crucial component in the investigation, prosecution and development of road safety strategies in the quest towards improved road safety efforts. It also indicates that existing crash data are of such a sub-standard that traffic professionals will not be able to develop effective and efficient road safety strategies in pursuit of road safety / Criminology and Security Science / M.A. (Criminology)

This research assessed the criminological significance of motor vehicle crash data within the criminal justice context. The study was conducted at the southern region Accident Bureau of the Ekurhuleni Metropolitan Police Department (EMPD). The objectives of this research are to: a. Explore and describe the extent and criminological impact of road traffic crashes on a macro level. b. Explore and describe the impact of road traffic crashes on a micro level. c. Explain the criminological significance of road traffic crash data in relation to effective road safety management. d. Evaluate and describe the attendance and recording procedure of road crashes. e. Evaluate and describe the supervisor’s responsibility in relation to the quality of crash data recorded. f. Evaluate and describe the effectiveness of crash statistics accessed by management and/or officials. g. Evaluate and explain the current prosecution procedure as part of the CJS. h. Evaluate existing policy about the crash-recording process applicable to operational law enforcement practitioners of the EMPD. i. Explore and describe the current state of motor vehicle insurance and its necessity from a criminological perspective. The researcher followed a mixed-methods approach, collecting quantitative data from recorded Accident Report Forms and qualitative data from interviews with participants active in their fields of expertise. Road crashes are characterised by injury and damage; victims suffer trauma and economic consequences, and the society and the economy as a whole are affected. The research suggests that accurate road crash data form a crucial component in the investigation, prosecution and development of road safety strategies in the quest towards improved road safety efforts. It also indicates that existing crash data are of such a sub-standard that traffic professionals will not be able to develop effective and efficient road safety strategies in pursuit of road safety / Criminology and Security Science / M.A. (Criminology)