1,720,957 research outputs found
Driver Psychology during Automated Platooning
No full textWith the rapid increase in vehicle automation technology, the call for understanding how humans behave while driving in an automated vehicle becomes more urgent. Vehicles that have automated systems such as Lane Keeping Assist (LKA) or Adaptive Cruise Control (ACC) not only support drivers in their journey, but also place them in a passive supervising role, scanning for potential hazardous stimuli in the environment or a system malfunction. More advanced technology that includes both lateral and longitudinal control and enables vehicles to drive at close distances from each other (called platooning technology) has the potential to reduce energy consumption and highway congestion. However, such technology places the driver in an even more critical position, as the time headway between vehicles is often below human reaction time (i.e., down to approximately 0.3 seconds). Little is known about driver behaviour, and the psychological constructs involved therewith, in automated platoons. This thesis investigates driver psychology during automated platooning.Transport and Plannin
Working towards a Meaningful Transition of Human Control over Automated Driving Systems
No full textAutomated vehicles with partial automation, supporting both longitudinal and lateral control of the vehicle, are currently available for the consumer. The consequences of driving with this type of advanced driver assistance systems is not well-known, and could cause the human driver to become out-of-the-loop, or cause other types of adverse behavioural adaptation, leading to dangerous circumstances. Therefore, understanding what the effects of driving with automated driving systems are from the human driver’s perspective is becoming imperative. By means of a literature-based approach, this paper presents a framework of human control over automated driving systems. This framework shows the quantified distribution of human behaviour over all the levels of automation. The implications, discrepancies and apparent mismatches this framework elicits are discussed, and recommendations are made to provide a meaningful transition of human control over automated driving systems.Transport and Plannin
Automated bus systems in Europe: A systematic review of passenger experience and road user interaction
No full textAutomated driving systems promise a tremendous amount of benefits. Especially when applied in the domain of public transport, economic and passenger advantages are thought to be manifold. As technology rapidly advances, and projects involving automated buses appear throughout the world, investigating how its users and surrounding road traffic interact with these novel technologies need to advance with a similar pace. However, up to now, a reliable and up-to-date overview of performed, running, and planned projects is lacking. Moreover, little is known about human interaction with automated bus systems, and what is known is not always reported. By means of a systematic review, an overview of the current state-of-the-art knowledge on the interaction between automated bus systems and its interactors is presented. Results of these studies are described and discussed, and implications are being made regarding future policies to be applied in this domain to safeguard safe interaction with automated bus systems.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Transport and Plannin
The influence of take-over requests on driver workload: The role of personality: A driving simulation self-experiment
No full textThe development of automated vehicles on the road is in full swing. As vehicles are getting increasingly automated, the human factor is diminished or eventually removed from automated driving. Until then, a combination of human input and automation is necessary during automated driving. This research focuses on the interaction between humans and machine and how a safe interaction can be designed by incorporating meaningful human control. Initially, the aim was to study how different personalities are reflected in driver workload induced by take-over requests (TORs). However, the COVID-19 circumstances changed the aim to validate the design of the driving simulation experiment by means of an N = 1 experiment. Design variables that have been found to play a role in driver workload are varied in the validation experiment. These variables are the duration of the time budget, traffic density, location of the TOR and task involvement during automated driving. Subsequently, workload was measured by a combination of subjective and physiological indicators and driving performance. Notably, this study includes the Root Mean Square of Successive Differences (RMSSD) and Standard Deviation of Normal to Normal peak intervals (SDNN) as heart rate variability (HRV) measures, which is a novel approach in studies measuring TOR-induced workload. Despite the study design that involved performing an N = 1 driving simulation experiment, significant differences between attribute levels have been found. This study provides recommendations on an empirically-validated set of design variables for future studies involving TORs and driver workload, specifically for the future study on personality and automated driving.Meaningful Human Control over Automated Driving SystemsTransport, Infrastructure and Logistic
Does personality affect responses to auditory take-over requests? Validating a simulator experiment setup through a N=1-study
No full textAutomated vehicles with conditional driving automation (SAE level 3 (SAE, 2018)) will request the human driver to intervene when reaching its system boundaries by issuing a take-over request (TOR). This study is investigating whether a speech-based auditory take-over request is influencing the time it takes from automated to manual driving, taking into account the personality trait of the human driver based on theory of Goldberg (1992). The audible warning is based on a woman's voice, varying in three levels of urgency, speech-rate and syntax, and incorporate a lateral deviation measurement by varying the lane width. Due to the COVID-19 pandemic, the experiment was changed to a N=1-study, meaning that only one participant, namely the lead researcher, partook in his own experiment. The driving experiment consisted of 81 runs, each having a TOR after approximately 8 minutes of automated driving. When the automated vehicle is in control, the human driver is asked to do a secondary task, namely the challenging game Tetris on a tablet to get distracted from the situation on the road. It was found that an increase in urgency (take-over type) means a decrease in take-over time (TOT). No significant differences were found for the speech-rate in relation to the TOT, whereas for the syntax, only the STR and UTR had significant differences. Lateral deviation was found to increase when urgency increases, which means that accuracy decreases with higher urgency. Overall, a final design is given based on the results of the N=1-study which could be used for a larger experiment including the personality trait.Transport, Infrastructure and Logistic
Highly automated platooning: Effects on mental workload, stress, and fatigue
No full textAutomatically driving platoons of vehicles are a likely candidate for solving many existing issues of road safety and congestion. However, the psychological effects of such technology are yet to be understood. Therefore, by means of a driving simulator experiment, we aimed to assess the psychological effects of driving in a highly automated platoon. The results showed that the type of task had no substantial effect on heart rate and self-reported stress, fatigue, and workload. However, time-on-task substantially reduced participants’ heart rate. Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Transport and PlanningBiomechatronics & Human-Machine Contro
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Effects of platooning on signal-detection performance, workload, and stress: A driving simulator study
No full textPlatooning, whereby automated vehicles travel closely together in a group, is attractive in terms of safety and efficiency. However, concerns exist about the psychological state of the platooning driver, who is exempted from direct control, yet remains responsible for monitoring the outside environment to detect potential threats. By means of a driving simulator experiment, we investigated the effects on recorded and self-reported measures of workload and stress for three task-instruction conditions: (1) No Task, in which participants had to monitor the road, (2) Voluntary Task, in which participants could do whatever they wanted, and (3) Detection Task, in which participants had to detect red cars. Twenty-two participants performed three 40-min runs in a constant-speed platoon, one condition per run in counterbalanced order. Contrary to some classic literature suggesting that humans are poor monitors, in the Detection Task condition participants attained a high mean detection rate (94.7%) and a low mean false alarm rate (0.8%). Results of the Dundee Stress State Questionnaire indicated that automated platooning was less distressing in the Voluntary Task than in the Detection Task and No Task conditions. In terms of heart rate variability, the Voluntary Task condition yielded a lower power in the low-frequency range relative to the high-frequency range (LF/HF ratio) than the Detection Task condition. Moreover, a strong time-on-task effect was found, whereby the mean heart rate dropped from the first to the third run. In conclusion, participants are able to remain attentive for a prolonged platooning drive, and the type of monitoring task has effects on the driver's psychological state.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Biomechatronics & Human-Machine ControlTransport and Plannin
Effects of mental demands on situation awareness during platooning: A driving simulator study
No full textPrevious research shows that drivers of automated vehicles are likely to engage in visually demanding tasks, causing impaired situation awareness. How mental task demands affect situation awareness is less clear. In a driving simulator experiment, 33 participants completed three 40-min runs in an automated platoon, each run with a different level of mental task demands. Results showed that high task demands (i.e., performing a 2-back task, a working memory task in which participants had to recall a letter, presented two letters ago) induced high self-reported mental demands (71% on the NASA Task Load Index), while participants reported low levels of self-reported task engagement (measured with the Dundee Stress State Questionnaire) in all three task conditions in comparison to the pre-task measurement. Participants’ situation awareness, as measured using a think-out-loud protocol, was affected by mental task demands, with participants being more involved with the mental task itself (i.e., to remember letters) and less likely to comment on situational features (e.g., car, looking, overtaking) when task demands increased. Furthermore, our results shed light on temporal effects, with heart rate decreasing and self-constructed mental models of automation growing in complexity, with run number. It is concluded that mental task demands reduce situation awareness, and that not only type-of-task, but also time-on-task, should be considered in Human Factors research of automated driving.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Transport and PlanningBiomechatronics & Human-Machine Contro
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