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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Detecting driver distraction

Liang, Yulan. Lee, John D., January 2009 (has links)
Thesis (Ph. D.)--University of Iowa, 2009. / Thesis supervisor: John D. Lee. Includes bibliographical references (leaves 130-137).
2

The impact of cell phone classification and experience on driver distraction

Heath, Amie Marie. January 1900 (has links)
Thesis (M.S.)--West Virginia University, 2007. / Title from document title page. Document formatted into pages; contains vi, 74 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 68-71).
3

Assessing the variation of driver distraction with experience

Akuraju, Nagaanupama. January 2009 (has links)
Thesis (M.S.)--West Virginia University, 2009. / Title from document title page. Document formatted into pages; contains ix, 81 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 59-65).
4

Effects of cognitive processing and cell phone use while driving

Sudhoff, Michelle Leigh. January 1900 (has links)
Thesis (M.S.)--West Virginia University, 2008. / Title from document title page. Document formatted into pages; contains vi, 47 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 43-46).
5

Exploratory Study of Distracted Behaviors of Transit Operators

Arbie, Nurlayla 30 August 2014 (has links)
Bus transit driving is an occupation that requires high concentration in driving and is demanding due to work overload, time pressure, and responsibility for lives. In 2006, there were 103 fatal crashes involving transit buses. As the number of distraction-related crashes increases, it is important to conduct a transit distraction study to reduce future crashes. This thesis focused on the analysis of the likelihood of the operator distraction behaviors and the analysis to find a predictive model to classify different distraction categories. An ordinal logistic regression was carried out to evaluate how age, gender, driving experience of the operators, and their driving frequencies accounts for the likelihood of 17 potential distracted driving behaviors. The results of this analysis showed that there were only 5 best models (p-value of model fit less than 0.005 and p-value of parallel line test more than 0.005) that could be constructed, including: listening to the radio/ CD/DVD/MP3 player (D1); picking Up and Holding 2-way Radio (D5); listening to the Dispatch Office broadcast (D6); adjusting switches/controls on dashboard (D15); and utilizing mentor ranger (D16). On the other hand, a discriminant analysis was performed to predict how different transit operator driving behaviors when exposed by 10 different distraction activities and 16 predictors were considered in this analysis. The final results showed that there are 4 predictors that seem to be able to classify distraction groups across all 4 models; those include segment length, average duration of idling time/stop delay at speed interval 0—4 km/hr, frequency of speed transitions that deviate by ± 0 to 4 km/hr from its speed, and frequency of speed transitions that deviate by ± 8 to 12 km/hr from its speed. / Master of Science
6

Machine Learning Based Action Recognition to Understand Distracted Driving

Radlbeck, Andrew J 03 December 2019 (has links)
The ability to look outward from your vehicle and assess dangerous peer behavior is typically a trivial task for humans, but not always. Distracted driving is an issue that has been seen on our roadways ever since cars have been invented, but even more so after the wide spread use of cell phones. This thesis introduces a new system for monitoring the surrounding vehicles with outside facing cameras that detect in real time if the vehicle being followed is engaging in distracted behavior. This system uses techniques from image processing, signal processing, and machine learning. It’s ability to pick out drivers with dangerous behavior is shown to be accurate with a hit count of 87.5%, and with few false positives. It aims to help make either the human driver or the machine driver more aware and assist with better decision making.
7

The Impact of Cell Phone use on the Driving Performance of Teenagers with and without Attention Deficit Hyperactivity Disorder

Narad, Megan 10 October 2014 (has links)
No description available.
8

Examining the Effect of Driving Experience on Teenage Driving Ability with Secondary Tasks

Howard, Edwin Henry III 26 February 2010 (has links)
This research examined the relationship between experience and driving performance with secondary tasks. Data were collected from 42 teenage drivers and their parents using an instrumented vehicle for two one hour test track sessions spaced 12 months apart. For part of the sessions, participants followed a lead vehicle which allowed for range data to be collected. Teenage and experienced drivers' driving were compared for cell phone and odometer tasks. Variables such as Speed, Range to Forward Vehicle, and Driving-Related Eyeglance percentages were all analyzed utilizing ANOVA. Post-hoc analysis on continuous data was performed using a Tukey HSD test. Lane Deviations were examined using Chi-Square analyses. Experienced drivers drove faster overall than teenage drivers. Teenage drivers drove faster in the 12 month session than the first session. No significant effects were found for Speed Variance, Range Variance, or Lane Deviations. Experienced drivers had a higher percentage of driving-related glances than teenage drivers. For the odometer task, teenage drivers were found to follow further behind a lead vehicle than adults. Driving experience was believed to have an effect on driver eyeglance patterns due to increased development of attentional control resulting in better switching between the task and the driving environment. Experienced drivers likely drove faster due to increased confidence in their driving ability. This research supports current GDL cell phone restrictions. A drivers' education lesson plan framework was developed to address these differences. Future research should focus on further refining GDL legislation to address the cognitive differences between teenage and experienced drivers. / Master of Science
9

Distracted Driving: A Cross-Disciplinary Analysis Exploring The Effectiveness Of Public Service Announcements Regarding Texting And Driving That Employ A Filmed Narrative With Emotional Appeals

Unknown Date (has links)
Despite efforts to mitigate texting and driving in the United States, accidents as a result of distracted driving continue to increase, especially within the 16-24 age group. Considering the traits of the members of this age group, as well as the attributes of the various means that are utilized to mitigate such behavior, I hypothesize that the employment of filmed narratives in public service announcements is more effective than any other established approach. Testing the validity of this hypothesis, contributing to a lack of research, three methods of analysis were employed in this project: a textual analysis of a filmed narrative; an audience analysis of the comments accompanying the filmed narrative; and a video session followed by a self-administered questionnaire. The results of this study indicate that while the filmed narrative is more effective than the spoken narrative, more intensive analyses are necessary for further speculation. / Includes bibliography. / Thesis (M.A.)--Florida Atlantic University, 2017. / FAU Electronic Theses and Dissertations Collection
10

Adaptação do tempo de frenagem de idosos e adultos em simulador de direção veicular com ou sem presença de distratores / Adaptation of the braking time of elderly and adults in vehicle direction simulator with and without the presence of distractors

Canonica, Alexandra Carolina 04 July 2018 (has links)
Estudos mostram a importância de se avaliar o tempo de adaptação dos indivíduos em um ambiente virtual de direção veicular, para que a resposta seja a mais próxima daquela obtida na direção real de um veículo. Assim, o objetivo deste trabalho foi identificar e analisar a adaptação ao simulador de direção, pelas repetições do tempo de frenagem, de idosos e adultos com e sem distrator e secundariamente identificar preditores do desempenho seguro dos condutores idosos. Foram avaliados 164 indivíduos de ambos os sexos divididos em dois grupos: 102 idosos acima de 65 anos e 62 adultos de 30 a 40 anos. O tempo de frenagem foi avaliado em um simulador de direção veicular, a cognição pelo Mini Exame do Estado Mental, a força muscular do flexor plantar de tornozelo pelo dinamômetro isocinético, a força de preensão palmar pelo dinamômetro manual e o equilíbrio postural pelo \"Time-Up and Go Test\" com e sem tarefa cognitiva. Idosos (homens e mulheres) e mulheres adultas demandam maior número de repetições do tempo de frenagem para se adaptar ao simulador de direção. O distrator aumenta o número de repetições de frenagem para que ocorra adaptação em todos os grupos. Os principais preditores do tempo de frenagem para as idosas são idade, força muscular e equilíbrio postural associados com dupla tarefa e para os idosos a força muscular. Desta forma, idade, sexo e presença de distrator interferem na adaptação à tarefa virtual de dirigir. O modelo de avaliação desenvolvido com multidomínios demonstrou ser capaz de predizer quais habilidades estão relacionadas com o tempo de frenagem com e sem a presença do distrator / Studies show the importance of evaluating the adaptation time of individuals in a virtual environment of vehicular direction, so that the response is the one closest to that obtained in the real direction of a vehicle. Thus, the objective of this work was to identify and analyze the adaptation to the steering simulator, by repetitions of braking time, of elderly and adults with and without distractor, and secondarily to identify predictors of the safe performance of elderly drivers. One hundred sixty-four individuals of both sexes were divided into two groups: 102 elderly over 65 years and 62 adults aged 30 to 40 years. The braking time was evaluated in a vehicle direction simulator, the cognition by Mini Mental State Examination, the ankle flexor muscle strength by isokinetic dynamometer, the palmar grip strength by manual dynamometer and the postural balance by \"Time-Up and Go Test\" with and without cognitive task. Elderly (men and women) and adult women require a greater number of repetitions of the braking time to adapt themselves to the steering simulator. The distractor increases the number of braking repetitions for adaptation in all groups. The main predictors of braking time for the elderly women are age, muscle strength and postural balance associated with dual task, and for the elderly men is the muscular strength. So age, gender and distractor presence interfere in the adaptation to the virtual task of driving. The evaluation model developed with multi-domains demonstrated to be able to predict which abilities are related to braking time with and without the presence of distractor

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