"uuid","repository link","title","author","contributor","publication year","abstract","subject topic","language","publication type","publisher","isbn","issn","patent","patent status","bibliographic note","access restriction","embargo date","faculty","department","research group","programme","project","coordinates"
"uuid:5a44e49e-6df3-469b-b9a6-f19085188280","http://resolver.tudelft.nl/uuid:5a44e49e-6df3-469b-b9a6-f19085188280","Drivers’ Behaviour on Freeway Curve Approach: Different Angles, Different Perspectives","Vos, J. (TU Delft Transport and Planning)","Hagenzieker, Marjan (promotor); Farah, H. (promotor); Delft University of Technology (degree granting institution)","2024","This dissertation explores what road characteristics trigger drivers’ speed adjustments when approaching freeway curves. It combines speed prediction modelling and human factors research methods. The results show that drivers primarily consider visible cues such as the preceding roadway, deflection angle, and the number of lanes, as opposed to traditional factors like horizontal radius or speed signs, when starting to decelerate. The study advocates for integrating driver perspectives into road design.","Geometric freeway design; human factors; Curve driving","en","doctoral thesis","","978-90-5584-340-4","","","","","","","","","Transport and Planning","","",""
"uuid:c5b1a63b-3873-4b1b-b4ed-e12390d21d40","http://resolver.tudelft.nl/uuid:c5b1a63b-3873-4b1b-b4ed-e12390d21d40","The identification of incidental learning as a cause of human error by exploring big data within railway safety","Burggraaf, J.M. (TU Delft Safety and Security Science)","van Gelder, P.H.A.J.M. (promotor); Groeneweg, J. (promotor); Delft University of Technology (degree granting institution)","2023","Accidents at work come at a major cost including fatalities, disability and economic burden. The ideas around accident causation have changed over time from describing accidents as ‘acts of gods’ and as the fault of individual employees, to accidents being the result of an interaction between organizational, technical and human factors. Included in the more recent ideas is the notion that organizations have a role and responsibility in preventing accidents. Prevention can include eliminating error-promoting factors or adding safety barriers to prevent errors from leading to accidents.
When employees interact with any system in their organization, interventions can be aimed at employees and at the system. When investigating possibilities to improve the system, it is important to take into account how employees interact with the system. We need to be able to predict human behavior and in order to do that, we need to understand human behavior....","Human error; safety; SPAD; Incidental learning; human factors","en","doctoral thesis","","","","","","","","","","","Safety and Security Science","","",""
"uuid:0d612f72-3f95-4b71-9a6a-4b16032159ab","http://resolver.tudelft.nl/uuid:0d612f72-3f95-4b71-9a6a-4b16032159ab","""Oh yes! over-preparing for meetings is my jam :)"": The Gendered Experiences of System Administrators","Kaur, M. (TU Delft Information and Communication Technology); Sri Ramulu, Harshini (The George Washington University); Acar, Yasemin (The George Washington University); Fiebig, T. (Max Planck Institut für Informatik)","","2023","In the system and network administration domain, gender diversity remains a distant target. The experiences and perspectives of sysadmins who belong to marginalized genders (non cis-men) are not well understood beyond the fact that sysadmin work environments are generally not equitable. We address this knowledge gap in our study by focusing on the ways in which sysadmins from marginalized genders manage their work in men-dominated sysadmin work spaces and by understanding what an inclusive workplace would look like. Using a feminist research approach, we engaged with a group of 16 sysadmins who are not cis-men via six online focus groups. We found that managing the impact of gender identity in the sysadmin workplace means demonstrating excellence and going above and beyond in system administration tasks, and also requires performing additional care work not expected from cis men. Furthermore, our participants handle additional layers of work due to gender considerations and to actively find community in the workplace. We found that sysadmins manage by going above and beyond in their tasks, performing care work and doing extra layers of work because of gender considerations, and finding community in the workplace. To mitigate this additional workload, we recommend more care for care work. For future research, we recommend the use of feminist lenses when studying sysadmin work in order to provide more equitable solutions that ultimately contribute to improving system security by fostering a just workplace.","care work; feminism; feminist approach; gender; human factors; sysadmin; system administration","en","journal article","","","","","","","","","","","Information and Communication Technology","","",""
"uuid:94925cc9-6365-4e49-bb3c-554905372779","http://resolver.tudelft.nl/uuid:94925cc9-6365-4e49-bb3c-554905372779","A risk-based driver behaviour model","Yuan, Y. (TU Delft Transport and Planning; Technische Universität München); Wang, X. (Queen Mary University of London); Calvert, S.C. (TU Delft Transport and Planning); Happee, R. (TU Delft Intelligent Vehicles); Wang, M. (Technische Universität Dresden)","","2023","Current driver behaviour models (DBMs) are primarily designed for the general driver population under specific scenarios, such as car following or lane changing. Hence DBMs capturing individual behaviour under various scenarios are lacking. This paper presents a novel method to quantify individual perceived driving risk in the longitudinal and lateral directions using risk thresholds capturing the time headway and time to line crossing. These are integrated in a risk-based DBM formulated under a model predictive control (MPC) framework taking into account vehicle dynamics. The DBM assumes drivers to operate as predictive controllers jointly optimising multiple criteria, including driving risk, discomfort, and travel inefficiency. Simulation results in car following and passing a slower vehicle demonstrate that the DBM predicts plausible behaviour under representative driving scenarios, and that the risk thresholds are able to reflect individual driving behaviour. Furthermore, the proposed DBM is verified using empirical driving data collected from a driving simulator, and the results show it is able to accurately generate vehicle longitudinal and lateral control matching individual human drivers. Overall, this model can capture individual risk perception behaviour and can be applied to the design and assessment of intelligent vehicle systems.","driver behaviour model; human factors; path planning; risk perception; vehicle dynamics and control","en","journal article","","","","","","","","","","","Transport and Planning","","",""
"uuid:c78ac1b9-ce90-4459-8075-bb0f27d5acb6","http://resolver.tudelft.nl/uuid:c78ac1b9-ce90-4459-8075-bb0f27d5acb6","Clearing the way for participatory data stewardship in artificial intelligence development: a mixed methods approach","Kelly, Sage (Queensland University of Technology); Kaye, Sherrie Anne (Queensland University of Technology); White, Katherine M. (Queensland University of Technology); Oviedo-Trespalacios, O. (TU Delft Safety and Security Science)","","2023","Participatory data stewardship (PDS) empowers individuals to shape and govern their data via responsible collection and use. As artificial intelligence (AI) requires massive amounts of data, research must assess what factors predict consumers’ willingness to provide their data to AI. This mixed-methods study applied the extended Technology Acceptance Model (TAM) with additional predictors of trust and subjective norms. Participants’ data donation profile was also measured to assess the influence of individuals’ social duty, understanding of the purpose and guilt. Participants (N = 322) completed an experimental survey. Individuals were willing to provide data to AI via PDS when they believed it was their social duty, understood the purpose and trusted AI. However, the TAM may not be a complete model for assessing user willingness. This study establishes that individuals value the importance of trusting and comprehending the broader societal impact of AI when providing their data to AI. Practitioner summary: To build responsible and representative AI, individuals are needed to participate in data stewardship. The factors driving willingness to participate in such methods were studied via an online survey. Trust, social duty and understanding the purpose significantly predicted willingness to provide data to AI via participatory data stewardship.","AI; human factors; participatory data stewardship; psychosocial models; user acceptance","en","journal article","","","","","","","","","","","Safety and Security Science","","",""
"uuid:7da602ca-94d1-440e-9e16-7c1d54bea676","http://resolver.tudelft.nl/uuid:7da602ca-94d1-440e-9e16-7c1d54bea676","Safety Assessment of the Interaction Between an Automated Vehicle and a Cyclist: A Controlled Field Test","Oskina, M.I. (Royal HaskoningDHV); Farah, H. (TU Delft Transport and Planning); Morsink, Peter (Royal HaskoningDHV); Happee, R. (TU Delft Intelligent Vehicles); van Arem, B. (TU Delft Transport and Planning)","","2023","The operation of automated vehicles (AVs) on shared roads requires attention concerning their interactions with vulnerable road users (VRUs), such as cyclists. This study investigates the safety of cyclists when they interact with an AV and compares it with their interaction with a conventional vehicle. Overall, 29 cyclists participated in a controlled field experiment consisting of interaction scenarios in which a vehicle approached the cyclist from behind. Four interaction scenarios were included: manual and automated following and manual and automated overtaking of the cyclist. The vehicle operated in all scenarios in a manual mode for safety reasons. However, before each ride, participants received information about the vehicle’s operation mode (automated or manual). The following attributes were considered: overtaking speed, overtaking lateral distance, following distance, and roadside objects. The objective and the subjective risks were evaluated in each scenario. The objective risk was assessed using the probabilistic driving risk field, and the subjective risk was assessed based on the cyclists’ selfreported risk values, cycling behavior, and their trust in AVs. The results show that automated and manual following have similar objective and subjective risks, while automated overtaking has a higher level of objective and subjective risks than manual overtaking. The results also show that a longer interaction time leads to an increase in cycling speed and a decrease in the lateral distance of the cyclist to the curb. Thus, we conclude that automated following is a safer option for short traveling distances, while for longer traveling distances, manual overtaking is preferred. Additionally, a short lateral distance from the cyclist when overtaking increases the subjective and objective risks.","advanced driver assistance systems; bicycles; human factors; modeling and forecasting; pedestrians; safety","en","journal article","","","","","","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.","","2023-08-28","","","Transport and Planning","","",""
"uuid:a55611cf-1ebc-4190-a456-4d1795db078f","http://resolver.tudelft.nl/uuid:a55611cf-1ebc-4190-a456-4d1795db078f","The impact of road traffic context on secondary task engagement while driving","Cuentas-Hernandez, Sandra (Queensland University of Technology); Li, Xiaomeng (Queensland University of Technology); King, Mark J. (Queensland University of Technology); Oviedo-Trespalacios, O. (TU Delft Values Technology and Innovation; TU Delft Safety and Security Science; Queensland University of Technology)","","2023","Introduction: Driver distraction has been recognized for a long time as a significant road safety issue. It has been consistently reported that drivers spend considerable time engaged in activities that are secondary to the driving task. The temporary diversion of attention from safety-critical driving tasks has often been associated with various adverse driving outcomes, from minor driving errors to serious motor vehicle crashes. This study explores the role of the driving context on a driver’s decision to engage in secondary activities non-critical to the driving task. Method: The study utilises the Naturalistic Engagement in Secondary Tasks (NEST) dataset, a complementary dataset derived from the SHRP2 naturalistic dataset, the most extensive naturalistic study to date. An initial exploratory analysis is conducted to identify patterns of secondary task engagements in relation to context variables. Maximum likelihood Chi-square tests were applied to test for differences in engagement between types of driver distraction for the selected contextual variables. Pearson residual graphs were employed as a supplementary method to visually depict the residuals that constitute the chi-square statistic.Lastly, a two-step cluster analysis was conducted to identify common execution scenarios among secondary tasks. Results: The exploratory analysis revealed interesting behavioral trends among drivers, with higher engagement rates in left curves compared to right curves, while driving uphill compared to driving downhill, in low-density traffic scenarios compared to high-density traffic scenarios, and during afternoon periods compared to morning periods. Significant differences in engagement were found among secondary tasks in relation to locality, speed, and roadway design. The clustering analysis showed no significant associations between driving scenarios of similar characteristics and the type of secondary activity executed. Discussion: Overall, the findings confirm that the road traffic environment can influence how car drivers engage in distracted driving behavior.","attention; driver distraction; human factors; multitask; risky behavior","en","journal article","","","","","","","","","","Values Technology and Innovation","Safety and Security Science","","",""
"uuid:81829072-4f3d-468b-a9ad-ff1b222fd6ca","http://resolver.tudelft.nl/uuid:81829072-4f3d-468b-a9ad-ff1b222fd6ca","Exploring the Influence of Signal Countdown Timers on Driver Behavior: An Analysis of Pedestrian–Vehicle Conflicts at Signalized Intersections","Sheykhfard, Abbas (Babol Noshirvani University of Technology); Haghighi, Farshidreza (Babol Noshirvani University of Technology); Papadimitriou, E. (TU Delft Safety and Security Science); Das, Subasish (Texas State University); van Gelder, P.H.A.J.M. (TU Delft Safety and Security Science)","","2023","Although signal countdown timers (SCTs) are likely to enhance efficiency at signalized intersections, there is little research on how they affect road users’ behavior. The present study explores factors associated with driver behavior through two approaches to examine how SCTs influence drivers’ actions toward pedestrians violating red lights. In the first approach, through an on-road questionnaire survey, the self-reported behavior of 369 drivers when crossing an intersection enabled with SCTs was analyzed. In the second approach, the drivers’ behavior was studied through naturalistic driving studies at two signalized intersections equipped with SCTs in Babol, Iran. Analyzing vehicle–pedestrian conflicts indicated that the presence of SCTs had a significant influence on driving behavior. Also, the ending seconds of green lights, as critical times of the SCTs, led to changes in driving behavior. Increasing the vehicle speed, changing lanes, and concurrent increases of speed and changing lanes were the common driver actions affected by critical times of the SCTs. Finally, the effect of critical times on drivers’ actions during conflicts was modeled by using the binary and multinomial logistic methods. The results show that SCTs are an external factor that can lead to risky driver behavior, such as errors and violations that might increase the potential for pedestrian accidents.","driver behavior; human factors; pedestrians; safety; signalized intersection; traffic signals","en","journal article","","","","","","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.","","2024-02-08","","","Safety and Security Science","","",""
"uuid:6bdec3fa-a7f5-4e14-8194-73bffaa99b6c","http://resolver.tudelft.nl/uuid:6bdec3fa-a7f5-4e14-8194-73bffaa99b6c","(Mis-)use of standard Autopilot and Full Self-Driving (FSD) Beta: Results from interviews with users of Tesla's FSD Beta","Nordhoff, S. (TU Delft Transport and Planning); Lee, John D. (University of Wisconsin-Madison); Calvert, S.C. (TU Delft Transport and Planning); Berge, S.H. (TU Delft Transport and Planning); Hagenzieker, Marjan (TU Delft Transport and Planning); Happee, R. (TU Delft Intelligent Vehicles)","","2023","Tesla's Full Self-Driving Beta (FSD) program introduces technology that extends the operational design domain of standard Autopilot from highways to urban roads. This research conducted 103 in-depth semi-structured interviews with users of Tesla's FSD Beta and standard Autopilot to evaluate the impact on user behavior and perception. It was found that drivers became complacent over time with Autopilot engaged, failing to monitor the system, and engaging in safety-critical behaviors, such as hands-free driving, enabled by weights placed on the steering wheel, mind wandering, or sleeping behind the wheel. Drivers' movement of eyes, hands, and feet became more relaxed with experience with Autopilot engaged. FSD Beta required constant supervision as unfinished technology, which increased driver stress and mental and physical workload as drivers had to be constantly prepared for unsafe system behavior (doing the wrong thing at the worst time). The hands-on wheel check was not considered as being necessarily effective in driver monitoring and guaranteeing safe use. Drivers adapt to automation over time, engaging in potentially dangerous behaviors. Some behavior seems to be a knowing violation of intended use (e.g., weighting the steering wheel), and other behavior reflects a misunderstanding or lack of experience (e.g., using Autopilot on roads not designed for). As unfinished Beta technology, FSD Beta can introduce new forms of stress and can be inherently unsafe. We recommend future research to investigate to what extent these behavioral changes affect accident risk and can be alleviated through driver state monitoring and assistance.","automated driving; Full Self-Driving (FSD) Beta; human factors; mind-off driving; traffic safety","en","journal article","","","","","","","","","","","Transport and Planning","","",""
"uuid:cd0ea01e-8f03-4bb9-88b5-2fa39ba7c2b1","http://resolver.tudelft.nl/uuid:cd0ea01e-8f03-4bb9-88b5-2fa39ba7c2b1","Analyzing the Impact of Perceived Exertion on Walking for Short-Distance Trips: A Comparative Case Study of Malta and the Netherlands","Scerri, Karyn (University of Malta); Attard, Maria (University of Malta); Duives, D.C. (TU Delft Transport and Planning); Cats, O. (TU Delft Transport and Planning)","","2023","Understanding people’s travel behavior is key to creating spaces that discourage car use, especially for short, walkable distances. The scope of this study is to understand better people’s propensity to use a car rather than walk for short-distance trips by focusing on the concept of perceived exertion (PE). A comparison is performed of two case study locations: Malta, a Euro-Mediterranean island with a high car dependency, and the Netherlands, a European country with a high active mode share of walking and cycling. Surveys were distributed to two university populations in each of the case study locations to analyze the parallels and variations in travel behavior and perceptions. Applying a mediation model analysis, the results show a partial mediation (Malta) and a full mediation (Netherlands) of PE in the relationship between car use frequency (CF) and distance threshold (DT), that is, the distance people are willing to walk rather than use a car. The mean DT for walking varied significantly between the two samples, resulting in 15.18 min (1.2 km or 0.7 mi) in the Netherlands and 17.99 min (1.4 km or 0.9 mi) in Malta, despite the comparatively larger active mode share in the Netherlands. Complementing this, the ordinal logistic models for the two countries indicate that those that perceive walking for short trips to be more effortful and those with a high CF are less inclined to walk long distances. Findings are compared with previous research, and policy-relevant suggestions based on these findings are provided.","behaviors; human factors; Malta; Netherlands; pedestrians; perceived exertion; walking","en","journal article","","","","","","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.","","2023-11-08","","","Transport and Planning","","",""
"uuid:01e9e6e1-8540-4893-ad3c-a4b57207ca0d","http://resolver.tudelft.nl/uuid:01e9e6e1-8540-4893-ad3c-a4b57207ca0d","Impacts of the COVID-19 Pandemic on Bikeshare Usage by Rider Membership Status Across Selected U.S. Cities","Vo, Tung (University of South Florida Tampa); Barbour, N.M. (TU Delft Transport and Logistics); Palaio, Lori (Johnson & Johnson); Maness, Michael (University of South Florida Tampa)","","2023","Bikesharing is a popular transportation mode for people to commute, for leisurely travel, or for recreation purposes in their daily tasks. Throughout 2020, the COVID-19 pandemic had significant impacts on bikeshare usage in the United States. Previous studies show that the pandemic negatively affected bikeshare activity patterns. To examine the effects of the pandemic on bikeshare behavior across membership types, this study investigated trip volume-and trip duration patterns of both members and nonmembers of five bikeshare systems across the United States. The results showed that member ridership significantly decreased throughout the pandemic, but nonmember ridership tended to be stable. It was also found that trip durations increased across both groups throughout the pandemic. Additionally, inferences were made to determine the level of support for a reversion to prepandemic normality as the pandemic progressed and reopening occurred in phases. The findings from this study could benefit bikeshare agencies in developing postpandemic recovery strategies.","bicycle transportation; bicycles; bikesharing; human factors; modeling and forecasting; pedestrians","en","book chapter","SAGE Publications","","","","","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.","","2023-04-17","","","Transport and Logistics","","",""
"uuid:d3290b1b-c55d-4039-b83f-e83d88c8cf41","http://resolver.tudelft.nl/uuid:d3290b1b-c55d-4039-b83f-e83d88c8cf41","“☑ Fairness Toolkits, A Checkbox Culture?” On the Factors that Fragment Developer Practices in Handling Algorithmic Harms","Balayn, A.M.A. (TU Delft Web Information Systems); Yurrita Semperena, M. (TU Delft Human Information Communication Design); Yang, J. (TU Delft Web Information Systems); Gadiraju, Ujwal (TU Delft Web Information Systems)","","2023","Fairness toolkits are developed to support machine learning (ML) practitioners in using algorithmic fairness metrics and mitigation methods. Past studies have investigated practical challenges for toolkit usage, which are crucial to understanding how to support practitioners. However, the extent to which fairness toolkits impact practitioners’ practices and enable reflexivity around algorithmic harms remains unclear (i.e., distributive unfairness beyond algorithmic fairness, and harms that are not related to the outputs of ML systems). Little is currently understood about the root factors that fragment practices when using fairness toolkits and how practitioners reflect on algorithmic harms. Yet, a deeper understanding of these facets is essential to enable the design of support tools for practitioners. To investigate the impact of toolkits on practices and identify factors that shape these practices, we carried out a qualitative study with 30 ML practitioners with varying backgrounds. Through a mixed within and between-subjects design, we tasked the practitioners with developing an ML model, and analyzed their reported practices to surface potential factors that lead to differences in practices. Interestingly, we found that fairness toolkits act as double-edge swords — with potentially positive and negative impacts on practices. Our findings showcase a plethora of human and organizational factors that play a key role in the way toolkits are envisioned and employed. These results bear implications for the design of future toolkits and educational training for practitioners and call for the creation of new policies to handle the organizational constraints faced by practitioners.","practices; organisational factors; human factors; fairness toolkits; algorithmic harms; algorithmic fairness","en","conference paper","Association for Computing Machinery (ACM)","","","","","","","","","","Web Information Systems","","",""
"uuid:4f14241e-efd0-41bd-9b60-40f0303fb928","http://resolver.tudelft.nl/uuid:4f14241e-efd0-41bd-9b60-40f0303fb928","Alert Alchemy: SOC Workflows and Decisions in the Management of NIDS Rules","Vermeer, M. (TU Delft Organisation & Governance); Kadenko, N.I. (TU Delft Organisation & Governance); van Eeten, M.J.G. (TU Delft Organisation & Governance); Hernandez Ganan, C. (TU Delft Organisation & Governance); Parkin, S.E. (TU Delft Organisation & Governance)","","2023","Signature-based network intrusion detection systems (NIDSs) and network intrusion prevention systems (NIPSs) remain at the heart of network defense, along with the rules that enable them to detect threats. These rules allow Security Operation Centers (SOCs) to properly defend a network, yet we know almost nothing about how rules are created, evaluated and managed from an organizational standpoint. In this work, we analyze the processes surrounding the creation, management, and acquisition of rules for network intrusion detection. To understand these processes, we conducted interviews with 17 professionals who work at Managed Security Service Providers (MSSPs) or other organizations that provide network monitoring as a service or conduct their own network monitoring internally. We discovered numerous critical factors, such as rule specificity and total number of alerts and false positives, that guide SOCs in their rule management processes. These lower-level aspects of network monitoring processes have generally been regarded as immutable by prior work, which has mainly focused on designing systems that handle the resulting alert flows by dynamically reducing the number of noisy alerts SOC analysts need to sift through. Instead, we present several recommendations that address these lower-level aspects to help improve alert quality and allow SOCs to better optimize workflows and use of available resources. These recommendations include increasing the specificity of rules, explicitly defining feedback loops from detection to rule development, and setting up organizational processes to improve the transfer of tacit knowledge.","human factors; interviews; NIDS rules; security operation centers; SOC","en","conference paper","Association for Computing Machinery (ACM)","","","","","","","","","","Organisation & Governance","","",""
"uuid:a8f31c69-661a-4a9d-bc16-9338c46f8254","http://resolver.tudelft.nl/uuid:a8f31c69-661a-4a9d-bc16-9338c46f8254","Shared control versus traded control in driving: a debate around automation pitfalls","de Winter, J.C.F. (TU Delft Human-Robot Interaction); Petermeijer, S.M. (Royal Netherlands Aerospace Centre NLR); Abbink, D.A. (TU Delft Human-Robot Interaction)","","2022","A major question in human-automation interaction is whether tasks should be traded or shared between human and automation. This work presents reflections—which have evolved through classroom debates between the authors over the past 10 years—on these two forms of human-automation interaction, with a focus on the automated driving domain. As in the lectures, we start with a historically informed survey of six pitfalls of automation: (1) Loss of situation and mode awareness, (2) Deskilling, (3) Unbalanced mental workload, (4) Behavioural adaptation, (5) Misuse, and (6) Disuse. Next, one of the authors explains why he believes that haptic shared control may remedy the pitfalls. Next, another author rebuts these arguments, arguing that traded control is the most promising way to improve road safety. This article ends with a common ground, explaining that shared and traded control outperform each other at medium and low environmental complexity, respectively. Practitioner summary: Designers of automation systems will have to consider whether humans and automation should perform tasks alternately or simultaneously. The present article provides an in-depth reflection on this dilemma, which may prove insightful and help guide design. Abbreviations: ACC: Adaptive Cruise Control: A system that can automatically maintain a safe distance from the vehicle in front; AEB: Advanced Emergency Braking (also known as Autonomous Emergency Braking): A system that automatically brakes to a full stop in an emergency situation; AES: Automated Evasive Steering: A system that automatically steers the car back into safety in an emergency situation; ISA: Intelligent Speed Adaptation: A system that can limit engine power automatically so that the driving speed does not exceed a safe or allowed speed.","automated driving; driverless cars; function allocation; human factors; Human-automation interaction; human-robot interaction; shared control; traded control","en","journal article","","","","","","","","","","","Human-Robot Interaction","","",""
"uuid:c0a0b934-bbfb-47ee-af00-989ad9e51e20","http://resolver.tudelft.nl/uuid:c0a0b934-bbfb-47ee-af00-989ad9e51e20","Promoting Physical Wellbeing in the Workplace: Providing Working Adults with a Tool to Reduce their Sedentary Behavior","Adar, M.E. (Student TU Delft); de Bruin, R. (TU Delft Applied Ergonomics and Design); Keyson, D.V. (TU Delft Design Conceptualization and Communication)","","2022","Whether it is from the office-office or the home office, creating a physical work environment is essential for both improving work performance as well as for the physical and mental wellbeing of employees. But as jobs are becoming increasingly less active, and working adults are spending almost a third of their lives in the office, most of their time is now spent sitting behind a desk. This time in sedentary behavior is increasing rapidly on a global scale and has become a great area of concern, as research has proven that this behavior is linked to an increase in all-cause mortality. To reduce the sedentary nature of the workplace, many companies are now replacing the standard desk with sit-stand desks (SSDs). SSDs are height adjustable desks that allow the user to work in either a sitting position or a standing position. Unfortunately, even as more companies are implementing these desks in their workspace, many studies indicate that there is a lack of utilization among working adults, with many only transitioning the desks to a standing position once a month or less.This paper presents a user-centered design project examining how to reduce the long-term sedentary behavior of desk-based working adults by motivating them to utilize their SSDs to make more transitions between sitting and standing. The project involved an agile design approach based on a cyclic process where a range of design techniques and research methods were used to look deeper into the practices and habits of working adults and better understand why this lack of use occurs and how it can be changed. These design techniques and research methods include a literature study, auto-ethnographical research, and 11 interviews with both active and non-active SSD users. An analysis of the differences between active and non-active users,led to the hypothesis that to reduce the SB of desk-based working adults, the use of SSDs in the workplace should be normalized by ensuring that working adults understand the benefits and proper use of SSDs while also offering the key tools: (1) reminders of when to transiting between sitting & standing; (2) social support; (3) awareness of effects on body & mind ; (4) task-based transitions. . This hypothesis was then used to initiate an empirical research through design process. Through this process, the final concept, BMDesk Application and Controller, was created. The BMDesk showcases an interactive digital platform and controller which utilizes the previously defined design opportunities to aid desk-based working adults in becoming more in tune with their physical and mental state while also providing them with the support they need to reduce their long-term sedentary behavior by utilizing their SSDs. The platform provides the user with an interactive tool that (1) gives them control over setting up their workday and defining how many sit-stand transitions they want to make and how long they want to remain in each position; (2) triggers a light reminder indicating to the user when it is time to check in and (3) provides a step-by-step body and mind self-evaluation included in the digital application; (4) based on the self-evaluation, the application provides a personalized tip and option to “learn more” about how the user can alter their position to relieve them of any physical or mental pain they are experiencing; (5) allows the user to choose if they actually want to change position and provides an additional reminder after a preset amount of time in the case they do not switch; (6) uses a two-way LED infrared sensor to automatically track the number of transitions and how long the user is in each position; and (7) allows the user to connect with the coworkers or friends to setup challenges or select times to standup together.","human factors; Workplace wellbeing; Sedentary behaviour; Sit-stand desks; Behavior change","en","conference paper","AHFE","","","","","","","","","","Applied Ergonomics and Design","","",""
"uuid:039573c9-80bc-4137-ab24-2894339e3a41","http://resolver.tudelft.nl/uuid:039573c9-80bc-4137-ab24-2894339e3a41","Behavioral-Based Pedestrian Modeling Approach: Formulation, Sensitivity Analysis, and Calibration","Hamdar, Samer Hani (The George Washington University); Talebpour, Alireza (Texas A and M University); D’sa, Kyla (The George Washington University); Knoop, V.L. (TU Delft Transport and Planning); Daamen, W. (TU Delft Transport and Planning); Treiber, Martin (Technische Universität Dresden)","","2022","Pedestrians are among the travelers most vulnerable to collisions that are associated with high fatality and injury rates. The increasing rate of urbanization and mixed land-use construction make walking (along with other non-motorized travel) a predominant transportation mode with a wide variety of behaviors expected. Because of the inherent safety concerns seen in pedestrian transportation infrastructures, especially those with conflicting multimodal movements expected (crosswalks, transit platforms, etc.), it is important that pedestrian behavior is modeled as a risk-taking stochastic behavior that may lead to errors and thus collision formation. In previous work, the complexity and cost associated with building pedestrian models in a cognitive-based environment weighted down the construction of simulation tools that can capture pedestrian-involved collisions, including those seen in shared space environments. In this paper, a tool that will help evaluate the safety of pedestrian traffic is initiated: an extended modeling framework of pedestrian walking behavior is adopted while incorporating different physiological, physical, and decision-making elements. The focus is on operational decisions (i.e., path choices defined by longitudinal and lateral trajectories) with a pre-specified set of origins and destinations. The model relies on the prospect theory paradigm where pedestrians evaluate their acceleration and directional alternatives while considering the possibility of colliding with other ‘‘particles.’’ Using a genetic algorithm method, the new model is calibrated using detailed trajectory data. This model can be extended to model the interactions between a variety of different modes that are present in different mixed land-use environments.","analysis; bicycles; human factors; modeling and forecasting; pedestrians; safety; simulation","en","journal article","","","","","","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.","","2022-06-04","","","Transport and Planning","","",""
"uuid:872a3271-c38a-4495-a75e-650b3b9dad42","http://resolver.tudelft.nl/uuid:872a3271-c38a-4495-a75e-650b3b9dad42","The Persuasive Automobile: Design and Evaluation of a Persuasive Lane-Specific Advice Human Machine Interface","van Gent, P. (TU Delft Transport and Planning); Farah, H. (TU Delft Transport and Planning); Nes, Nicole Van (SWOV Institute for Road Safety Research); van Arem, B. (TU Delft Transport and Planning)","","2020","Traffic congestion is a major societal challenge. By advising drivers on the optimal lane to drive, traffic flow can be improved, and congestion reduced. In this paper we describe the development of a lane-specific advice Human Machine Interface (HMI). Persuading drivers to follow an advice that is beneficial to the traffic situation, but may not be immediately beneficial to the drivers themselves, is challenging. In this paper we define persuasive elements to encourage drivers to follow the lane-specific advices. We then describe the interface design process, followed by its evaluation using a driving simulator study. In the simulator study, the effect of two types of persuasion are evaluated: a competitive variant where drivers could earn points and compete with others, and a cooperative variant where real-time information on the number of compliant drivers was available. Participants drove in the simulator on two days. Between days, the treatment groups viewed a Web-portal showing their performance and encouragement from an avatar. Those in the competitive and cooperative groups followed significantly more advices (117 and 111) than those in the control group (89). No significant differences were visible between competitive and cooperative groups. The differences between groups only emerged on the second day.","Driving simulator; human factors; human machine interface; intelligent vehicles; persuasive technology","en","journal article","","","","","","","","","","","Transport and Planning","","",""
"uuid:55a87f3b-c138-4d99-ad65-8acfd55f984b","http://resolver.tudelft.nl/uuid:55a87f3b-c138-4d99-ad65-8acfd55f984b","A Conceptual Model for Persuasive In-Vehicle Technology to Influence Tactical Level Driver Behaviour","van Gent, P. (TU Delft Transport and Planning); Farah, H. (TU Delft Transport and Planning); Nes, Nicole Van (SWOV Institute for Road Safety Research); van Arem, B. (TU Delft Transport and Planning)","","2019","Persuasive in-vehicle systems aim to intuitively influence the attitudes and/or behaviour of a driver (i.e. without forcing them). However, the challenge in using these systems in a driving setting, is to maximise the persuasive effect without infringing upon the driver's safety. This paper proposes a conceptual model for driver persuasion at the tactical level (i.e., driver manoeuvring level, such as lane-changing and car-following). The main focus of the conceptual model is to describe how to safely persuade a driver to change his or her behaviour, and how persuasive systems may affect driver behaviour. First, existing conceptual and theoretical models that describe behaviour are discussed, along with their applicability to the driving task. Next, we investigate the persuasive methods used with a focus on the traffic domain. Based on this we develop a conceptual model that incorporates behavioural theories and persuasive methods, and which describes how effective and safe driver persuasion functions. Finally, we apply the model to a case study of a lane-specific advice system that aims to reduce travel time delay and traffic congestion by advising some drivers to change lanes in order to achieve a better distribution of traffic over the motorway lanes.