@phdthesis{Dittrich2021,
  author    = {Dittrich, Monique},
  title     = {Persuasive Technology to Mitigate Aggressive Driving : A Human-centered Design Approach},
  doi       = {10.25972/OPUS-23022},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-230226},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2021},
  abstract  = {Manifestations of aggressive driving, such as tailgating, speeding, or swearing, are not trivial offenses but are serious problems with hazardous consequences—for the offender as well as the target of aggression. Aggression on the road erases the joy of driving, affects heart health, causes traffic jams, and increases the risk of traffic accidents. This work is aimed at developing a technology-driven solution to mitigate aggressive driving according to the principles of Persuasive Technology. Persuasive Technology is a scientific field dealing with computerized software or information systems that are designed to reinforce, change, or shape attitudes, behaviors, or both without using coercion or deception. Against this background, the Driving Feedback Avatar (DFA) was developed through this work. The system is a visual in-car interface that provides the driver with feedback on aggressive driving. The main element is an abstract avatar displayed in the vehicle. The feedback is transmitted through the emotional state of this avatar, i.e., if the driver behaves aggressively, the avatar becomes increasingly angry (negative feedback). If no aggressive action occurs, the avatar is more relaxed (positive feedback). In addition, directly after an aggressive action is recognized by the system, the display is flashing briefly to give the driver an instant feedback on his action. Five empirical studies were carried out as part of the human-centered design process of the DFA. They were aimed at understanding the user and the use context of the future system, ideating system ideas, and evaluating a system prototype. The initial research question was about the triggers of aggressive driving. In a driver study on a public road, 34 participants reported their emotions and their triggers while they were driving (study 1). The second research question asked for interventions to cope with aggression in everyday life. For this purpose, 15 experts dealing with the treatment of aggressive individuals were interviewed (study 2). In total, 75 triggers of aggressive driving and 34 anti-aggression interventions were identified. Inspired by these findings, 108 participants generated more than 100 ideas of how to mitigate aggressive driving using technology in a series of ideation workshops (study 3). Based on these ideas, the concept of the DFA was elaborated on. In an online survey, the concept was evaluated by 1,047 German respondents to get a first assessment of its perception (study 4). Later on, the DFA was implemented into a prototype and evaluated in an experimental driving study with 32 participants, focusing on the system's effectiveness (study 5). The DFA had only weak and, in part, unexpected effects on aggressive driving that require a deeper discussion. With the DFA, this work has shown that there is room to change aggressive driving through Persuasive Technology. However, this is a very sensitive issue with special requirements regarding the design of avatar-based feedback systems in the context of aggressive driving. Moreover, this work makes a significant contribution through the number of empirical insights gained on the problem of aggressive driving and wants to encourage future research and design activities in this regard.},
  subject      = {Fahrerassistenzsystem},
  language  = {en}
}
@phdthesis{Schnabel2011,
  author    = {Schnabel, Eva},
  title     = {Alcohol and driving-related performance - A comprehensive meta-analysis focusing the significance of the non-significant},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-69959},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2011},
  abstract  = {The present work reviews the experimental literature on the acute effects of alcohol on human behaviour related to driving performance. A meta-analysis was conducted which includes studies published between 1954 and 2007 in order to provide a comprehensive knowledge of the substance alcohol. 450 studies reporting 5,300 findings were selected from over 12,000 references after applying certain in- and exclusion criteria. Thus, the present meta-analysis comprises far more studies than reviews on alcohol up to now. In the selected studies, different performance tests were conducted which were relevant for driving. The classification system used in this work assigns these tests to eight categories. The main categories consist of several sub categories classifying the tasks more precisely. The main categories were: (1) visual functions, (2) attention (including vigilance), (3) divided attention, (4) en-/decoding (including information processing and memory), (5) reaction time (including simple reaction time and choice reaction time), (6) psychomotor skills, (7) tracking and (8) driving. In addition to the performance aspect, the classification system takes into account mood and social behaviour variables related to driving safety like tiredness or aggression. Following the evaluation method of vote-counting, the number of significant findings and the number of non-significant findings were summarised per blood alcohol concentration (BAC) group. Thereby, a quantitative estimation of the effects of alcohol depending on the BAC was established, the so-called impairment function, which shows the percentage of significantly impaired findings. In order to provide a general overview of alcohol effects on driving-related performance, a global impairment function was established by aggregating all performance findings. The function is nearly linear with about 30\% significant findings at a BAC of 0.05\% and 50\% significant findings at a BAC of 0.08\%. In addition, more specific impairment functions considering only the findings of the single behavioural categories were calculated. The results revealed that impairment depends not only on the BAC, but also clearly differs between most of the performance categories. Tracking and driving performance were most affected by alcohol with impairment beginning at very low BACs of 0.02\%. Also psychomotor skills were considerably affected by rather low BACs. Impairment of visual functions and information processing occurred at BACs of 0.04\% and increased substantially with higher BACs. Impairment in memory tests could be found with very low BACs of 0.02\%, but varied depending on the kind of memory. Performance decrements in divided attention tests could also be found with very low BACs in some studies. Attention started to be impaired at 0.04\% BAC, but - as in vigilance tasks - considerable impairment only occurred at higher BACs. Choice reaction time was affected at lower BACs than simple reaction time, which was - together with the critical flicker fusion frequency - the least sensitive parameter to the effects of alcohol. To conclude, most skills which are relevant for the safe operation of a vehicle are clearly impaired by BACs of 0.05\%, with motor functions being more affected than cognitive functions and complex tasks more than simple tasks. Generally, the results provided no evidence of a threshold effect for alcohol. There was no driving-related performance category for which a sudden transition from unimpaired to impaired occurred at a particular BAC level. In addition, a comparison was made between the present meta-analysis and two reviews of Moskowitz (Moskowitz \& Fiorentino, 2000; Moskowitz \& Robinson, 1988). Moskowitz reported much lower BACs at which performance was impaired. The reasons for this discrepancy lies in a different way to review scientific findings. On the one hand, Moskowitz focused on significant findings when selecting studies and findings for his reviews. On the other hand, the evaluation method used by Moskowitz ignored non-significant findings and counted each study once at the lowest BAC for which impairment was found. Those non-significant findings are as important as the significant ones in order to determine thresholds of impairment. Therefore, in contrast to Moskowitz, the present work describes the effects of alcohol with functions considering also the non-significant findings. The significance of the non-significant is emphasized with respect to the selection procedure as well as to the evaluation method.},
  subject      = {Trunkenheit im Verkehr},
  language  = {en}
}
@phdthesis{Wandtner2018,
  author    = {Wandtner, Bernhard},
  title     = {Non-driving related tasks in highly automated driving - Effects of task characteristics and drivers' self-regulation on take-over performance},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-173956},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2018},
  abstract  = {The rise of automated driving will fundamentally change our mobility in the near future. This thesis specifically considers the stage of so called highly automated driving (Level 3, SAE International, 2014). At this level, a system carries out vehicle guidance in specific application areas, e.g. on highway roads. The driver can temporarily suspend from monitoring the driving task and might use the time by engaging in so called non-driving related tasks (NDR-tasks). However, the driver is still in charge to resume vehicle control when prompted by the system. This new role of the driver has to be critically examined from a human factors perspective. The main aim of this thesis was to systematically investigate the impact of different NDR-tasks on driver behavior and take-over performance. Wickens' (2008) architecture of multiple resource theory was chosen as theoretical framework, with the building blocks of multiplicity (task interference due to resource overlap), mental workload (task demands), and aspects of executive control or self-regulation. Specific adaptations and extensions of the theory were discussed to account for the context of NDR-task interactions in highly automated driving. Overall four driving simulator studies were carried out to investigate the role of these theoretical components. Study 1 showed that drivers focused NDR-task engagement on sections of highly automated compared to manual driving. In addition, drivers avoided task engagement prior to predictable take-over situations. These results indicate that self-regulatory behavior, as reported for manual driving, also takes place in the context of highly automated driving. Study 2 specifically addressed the impact of NDR-tasks' stimulus and response modalities on take-over performance. Results showed that particularly visual-manual tasks with high motoric load (including the need to get rid of a handheld object) had detrimental effects. However, drivers seemed to be aware of task specific distraction in take-over situations and strictly canceled visual-manual tasks compared to a low impairing auditory-vocal task. Study 3 revealed that also the mental demand of NDR-tasks should be considered for drivers' take-over performance. Finally, different human-machine-interfaces were developed and evaluated in Simulator Study 4. Concepts including an explicit pre-alert ("notification") clearly supported drivers' self-regulation and achieved high usability and acceptance ratings. Overall, this thesis indicates that the architecture of multiple resource theory provides a useful framework for research in this field. Practical implications arise regarding the potential legal regulation of NDR-tasks as well as the design of elaborated human-machine-interfaces.},
  subject      = {Autonomes Fahrzeug},
  language  = {en}
}