Browsing by Subject "driver behavior"

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    The Decision To Speed In the United States – A Mixed Methods Study
    (2020-06) Peterson, Colleen
    Speeding remains a major and consistent cause of U.S. roadway fatalities. The current research used a mixed methods approach to build a more comprehensive understanding of which U.S. drivers decide to speed and why to inform novel speeding interventions. Data came from an online survey of a diverse group of drivers (N=309) from across the U.S. The survey collected information on participant demographics, driving history, behaviors, and related attitudes in the form of both open- and close-ended questions. The first manuscript identified qualitative themes from narratives explaining how and why participant speeding behaviors changed with age. Results show U.S. drivers often make deliberate choices to speed and do not consider speeding to be dangerous after achieving perceived driving mastery, but they tend to speed less due to family responsibility and prioritizing safety. The second manuscript featured latent class analysis resulting in four driver typologies representing: Externally Motivated Reactors, Non-Reactors, the Perceived Invulnerable, and the Perceived Vulnerable. Externally Motivated Reactors and Non-Reactors class members had the highest probability of extreme speeding, while Perceived Vulnerable class members endorsed a host of less risky driving responses. The third manuscript identified quantitative and qualitative commonalities and differences between minor, moderate, and extreme speeders. Speeders were most differentiated quantitatively by proportion of high risk and sensation-seeking personalities and qualitatively by the permanence and extent of speed reductions after crashes, speeding tickets, or driving with passengers. For all speeder types, considering oneself a good driver or not at-fault for a crash reduced intention to change speeding behaviors. These mixed methods results holistically describe a spectrum of U.S. drivers, their perceptions, attitudes, and contexts that lead to different speeding behaviors, and how these change with age. Findings show that effective means of encouraging U.S. drivers not to speed may be multi-pronged interventions encompassing environmental, social, and cognitive reframing approaches. Anti-speeding campaigns should target high sensation seekers, emphasize the safety of all roadway users, explain the connection between speed and safety, underscoring how speeding reduces driver control. Broad-based use of safe systems road design and expanded law enforcement strategies are also recommended.
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    Understanding Driver Contributions to Rear-End Crashes on Congested Freeways and their Implications for Future Safety Measures
    (2016-04) Chatterjee, Indrajit
    Empirical evidence for occurrences of shockwaves as a primary cause of rear-end crashes on freeways is well documented in the transportation safety literature. However, existing studies fail to provide a satisfactory explanation of why some shockwaves produce rear-end crashes and others do not. In pursuit of answering such a question, my doctoral research focuses on understanding the behavior of individual drivers involved in brake-to-stop events on congested freeways, and using this understanding to evaluate the implications for future safety measures. Using video recordings of shockwaves from a section of a congested freeway my doctoral research verifies a sufficient condition for a rear-end collision to happen when a sequence of drivers interact with each other in a brake-to-stop situation. Then drawing on classic results from the theory of random walks, it is possible to estimate the probability that successive braking by a platoon of drivers results in a rear-end crash. Finally, as the ultimate goal of this research is to understand the underlying mechanism that governs the behavior of drivers involved in rear-end events, this research treats drivers in a brake-to-stop event as engaged in strategic interactions in the roles of a leader and follower, who aim to maximize individual utilities. This leads to a population game whose steady state distribution describes the long-run behavior of the drivers in the population. The proposed framework is then extended to investigate (a) the safety implications of mixtures of human-operated and automated vehicles (b) the safety implications of negligence-based liability policies where individual drivers are penalized based on degree of causal contribution to the crash.