This study sought to investigate the relationship between cell phone conversation type and dangerous driving behaviors. It was hypothesized that more emotional phone conversations engaged in while driving would produce greater frequencies of dangerous driving behaviors in a simulated environment than more mundane conversation or no phone conversation at all. Participants were semi-randomly assigned to one of three conditions: (1) no call, (2) mundane call, and, (3) emotional call. While driving in a simulated environment, participants in the experimental groups received a phone call from a research confederate who either engaged them in innocuous conversation (mundane call) or arguing the opposite position of a deeply held belief of the participant (emotional call). Participants in the no call and mundane call groups differed significantly only on percent time spent speeding and center line crossings, though the mundane call group consistently engaged in more of all dangerous driving behaviors than did the no call participants. Participants in the emotional call group engaged in significantly more dangerous driving behaviors than participants in both the no call and mundane call groups, with the exception of traffic light infractions, where there were no significant group differences. Though there is need for replication, the authors concluded that whereas talking on a cell phone while driving is risky to begin with, having emotionally intense conversations is considerably more dangerous.

Driving is a high-risk adventure which many enjoy on a daily basis. The driving task is highly complex, ever-changing, and one which requires continuous attention and rapid decision making. It is a task that is not without risk, where the cost to reach the desired destination can be too great – your life could be at stake. Driving is not without incidents. Rear-end collision is a common problem in the Swedish traffic environment, with over 100 police-reported individual incidents per year. The amount of rear-end collisions can be hypothetically reduced by introducing new technology in the driver’s vehicle, technology which attempts to improve the driver’s safety driving. This technology is called Advanced Driver Assistance Systems – ADAS. In this study two ADAS were evaluated in a driving simulator study: An Adaptive Cruise Control (ACC) which operates on both hazardous and non-hazardous events, and a Collision Warning System (CWS) which operates solely on non-hazardous events. Both of these ADAS function to guard against risky driving and are based on the assumption that drivers will not act in such a manner that they would willingly reduce the effectiveness of the system. A within-subjects simulation study was conducted where participants drove under three conditions: 1) with an adaptive cruise controller, 2) a frontal rear-end collision warning system ADAS, and 3) unaided, in order to investigate differences between the three driving conditions. Particular focus was on whether the two ADAS improved driving safety. The study results indicate that driving enhanced by the two ADAS made the participating drivers drive less safely.

This thesis summarizes an approach for building a trajectory-tracking framework for autonomous robots working in low-speed and controlled space. A modularized robot framework can provide easy access to hardware and software replacement, which can be a tool for validating trajectory-tracking algorithms in controlled laboratory conditions. An introduction to other existing methods for trajectory tracking is presented. These advanced trajectory control methods and studies aim to improve trajectory tracking control for better performance under different environments. This research uses ROS as the middleware for connecting the actuators and computing units. A market-existing global position measurement tool, the UWB system, was selected as the primary localization sensor. A Raspberry Pi and an Arduino Uno are used for high-level and low-level control. The separation of the control units benefits the modularization design of the framework. A robust control approach has also been introduced to prevent the disturbance of uneven terrain to improve the framework's capability to drive arbitrary robot chassis in different testing grounds. During each stage of development, there are offline and online tests for live control tests. The trajectory tracking controller requires a robot kinematic model and tracking control program for better results of controlled behaviour. A custom trajectory control program was made and implemented into the tests. A digital simulation and a physical robot are built to validate the algorithm and the designed framework for performance validation. This framework aims to suit the other scholar's developments and can be used as a testing platform to implement their autonomous driving algorithms or additional sensors. By replacing the control algorithm in the existing trajectory-tracking robotic framework, this autonomous, universal platform may benefit the validation of these algorithms' performance in the field experiment. / Thesis / Master of Applied Science (MASc) / This thesis contains five chapters. Chapter 1 provided the information and background for this research topic regarding the key components, methods, and tools for creating trajectory tracking. Chapter 2 focuses on the existing methods and deep study of tools, equipment and hardware setups for trajectory tracking in simulation and physical setups. The experiments referenced from other studies can benefit the research and development work for the current trajectory tracking development work. The review provides different kinematics models for robot layouts, which impacts the final design of the field experiment robot. Chapter 3 presents the design work process for creating a controller based on the final field experiment robot. This chapter provides steps and considerations while building the control system for a trajectory-tracking robot from scratch. Chapter 4 demonstrates the simulation results and field experiment results. A study of error analysis and repeatability justification can also be found in this chapter. Chapter 5 summarizes the research and development contribution, primary findings, and concerns for identified problems.

Despite modest reductions over previous decades, improvements in impaired driving prevalence have stalled at problematic levels in recent years. Recent self-report data indicate that 20 percent of driving age individuals acknowledge operating a vehicle within two hours of alcohol consumption within the previous year and there are approximately 121 million episodes of impaired driving annually. Extant research has consistently identified specific subgroups, including men, young adults, and individuals with less education, as being high risk for driving under the influence. Additionally, researchers of impaired driving have discerned certain impaired driving-related attitudes and behaviors as important predictors of impaired driving. Despite a large and growing base of literature, impaired driving research has been notably atheoretical and restricted by samples limited to specific ages or geographic regions. Regardless of the prevalence of impaired driving episodes, the likelihood of apprehension for DUI remains low and little is known about how offenders respond to an impaired driving arrest. I address these limitations in the current study. Using nationally representative data from the National Survey of Drinking and Driving Attitudes and Behaviors, I consider the role of cognitive and behavioral predictors as mediating the association between key socio-structural indicators and impaired driving. To consider how individuals respond to DUI arrests, I performed an extensive qualitative content analysis on 627 DUI narratives from reddit (i.e., an online social forum) to consider how the arrest affects individuals apprehended for driving under the influence. Path analyses provide further support for previous studies, with men and young adults more likely to self-report impaired driving compared to females and older reference groups. Further, analyses indicate this increased likelihood of impaired driving by men and young adults was explained in part by differences in monthly alcohol consumption, binge drinking, supportive social networks, and more positive assessments of impaired driving. Analyses of DUI offenders indicate a stigmatizing effect of the DUI arrest, where offenders strategically attempt to deflect culpability for their role in attempts to minimize the range of perceived negative consequences. Overall, theoretical considerations and findings provide additional insight and areas of exploration for researchers and practitioners tasked with DUI mitigation efforts.

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The Dula Dangerous Driving Index (DDDI) was created to measure drivers' self-reported propensity to drive dangerously (Dula & Ballard, in press). In the early stages of development, the DDDI and each of its subscales (Dangerous Driving Total, Aggressive Driving, Negative Emotional Driving, and Risky Driving) were found to have strong internal reliability (alphas from .83 to .92), and there was evidence of construct validity. In Study One, the alpha coefficient of .91 for the DDDI Total scale indicated excellent internal reliability for the measure and good internal reliability was demonstrated for its subscales with coefficient alphas equal to .81 for the DDDI Risky Driving subscale, .79 for the DDDI Negative Emotional subscale, and the DDDI Aggressive Driving subscale. Additionally, convergent and divergent validity was shown for the DDDI, but evidence was weaker for the validity of the separate subscales. Factor analysis demonstrated that the DDDI seemed to measure a unitary construct. In Study Two, coefficients of stability were generated from a four-week test-retest procedure, which were .76 for the DDDI Risky Driving subscale, .68 for the DDDI Negative Emotional subscale, .55 for the DDDI Aggressive Driving subscale, and .73 for the DDDI Total. In Study Three, the percentage of variance accounted for in criterion variables by different models ranged from 13.6% to 47.7%, where the DDDI Negative Emotional and DDDI Total scales frequently accounted for large portions of variance. In Study Four, the percent of variance accounted for in criterion variables by different models ranged from 22.0% to 65.6%, where some of the DDDI scales were regularly found to account for significant variance. Thus, it was concluded that the DDDI is a measure with high levels of internal reliability and reasonable stability across time, and that face, construct, and predictive validity was demonstrated. However, the evidence in support of the present division of subscales was weak, though present. Therefore, should further data fail to produce more substantial evidence for the validity of the DDDI subscales, a singular dangerous driving measure would be warranted, and the number of items should be shortened as guided by results from factorial analysis. / Ph. D.

Motor-Vehicle crashes are the leading cause of death for teens and young adults. Research and public interventions have primarily examined the impact of external factors related to driving; however, less work has examined internal factors. Limited research has shown a negative association between trait forgiveness of others and both driving anger and driving aggression. The current study replicates previous findings and expands to include multiple dimensions of forgiveness and adverse driving outcomes as a dependent variable. It was predicted that multiple dimensions of forgiveness would be directly and indirectly related to adverse driving outcomes through the mediators of anger rumination, stress, and dangerous driving. Undergraduate students (N=759) at a regional university completed a series of self-report questionnaires online examining driving anger, driving aggression, multiple dimensions of forgiveness, adverse driving outcomes, anger rumination, stress, and dangerous driving behaviors. Hierarchical multiple regression analyses were used to replicate previous findings (analysis 1) and multiple serial mediations as expansion (analysis 2). In replication, trait forgiveness of others was shown to have a negative bivariate correlation with driving anger and driving aggression and to be a significant predictor of driving aggression above that of driving anger (analysis 1). Multiple serial mediation demonstrated an indirect only effect of multiple dimensions of forgiveness on adverse driving outcomes through the various mediators (analysis 2); however, varied relationships were observed. As a result, forgiveness of self and of uncontrollable situations demonstrated a significant negative effect on adverse driving outcomes through the various mediators. However, although, forgiveness of others was found to have a significant negative effect through anger rumination and dangerous driving behaviors in serial, it demonstrated a positive effect with stress as a mediator. The results support and replicate previous research and demonstrate a significant indirect only effect of multiple dimensions of forgiveness on adverse driving outcomes through the current mediators. The relationships were varied, however. Therefore, multiple dimensions of forgiveness continue to be meaningful variables related to driving anger, driving aggression, and adverse driving outcomes.

abstract: Previous literature was reviewed in an effort to further investigate the link between notification levels of a cell phone and their effects on driver distraction. Mind-wandering has been suggested as an explanation for distraction and has been previously operationalized with oculomotor movement. Mind-wandering’s definition is debated, but in this research it was defined as off task thoughts that occur due to the task not requiring full cognitive capacity. Drivers were asked to operate a driving simulator and follow audio turn by turn directions while experiencing each of three cell phone notification levels: Control (no texts), Airplane (texts with no notifications), and Ringer (audio notifications). Measures of Brake Reaction Time, Headway Variability, and Average Speed were used to operationalize driver distraction. Drivers experienced higher Brake Reaction Time and Headway Variability with a lower Average Speed in both experimental conditions when compared to the Control Condition. This is consistent with previous research in the field of implying a distracted state. Oculomotor movement was measured as the percent time the participant was looking at the road. There was no significant difference between the conditions in this measure. The results of this research indicate that not, while not interacting with a cell phone, no audio notification is required to induce a state of distraction. This phenomenon was unable to be linked to mind-wandering. / Dissertation/Thesis / Masters Thesis Human Systems Engineering 2019