1,721,017 research outputs found
Human factors considerations in the design and development of highly automated driving systems
No full textIncreasing levels of automation within the driving task has seen the driver’s role change from an active operator to one of a passive monitor. However, systems design has been plagued by criticism for failing to acknowledge the new role of the driver within the system network. To further our understanding of the driver’s role within an automated driving system, the theory of Distributed Cognition was adopted. Distributed Cognition provides a useful framework for the investigation of task partitioning between multiple system agents. A novel Systems Design Framework has been developed as part of this thesis that utilises both qualitative and quantitative research methodologies within the Distributed Cognition paradigm. The framework is divided into two phases, the first phase requires an understanding of how individual system agents function to create models that show how these components share information using Operator Sequence Diagrams whilst empirical methods were used to validate these models in the second phase (e.g. Verbal Protocol Analysis and Network Analysis). These extension methodologies were useful in highlighting a number of design weaknesses, beyond the modelled technological components, that required modification to improve overall system design. The Systems Design Framework has been successfully applied to assist Systems Engineers with a foundation to design and conduct research into the human factors implications of different levels of automation within driving
Keep the driver in control: automating automobiles of the future
No full textAutomated automobiles will be on our roads within the next decade but the role of the driver has not yet been formerly recognised or designed. Rather, the driver is often left in a passive monitoring role until they are required to reclaim control from the vehicle. This research aimed to test the idea of driver-initiated automation, in which the automation offers decision support that can be either accepted or ignored. The test case examined a combination of lateral and longitudinal control in addition to an auto-overtake system. Despite putting the driver in control of the automated systems by enabling them to accept or ignore behavioural suggestions (e.g. overtake), there were still issues associated with increased workload and decreased trust. These issues are likely to have arisen due to the way in which the automated system has been designed. Recommendations for improvements in systems design have been made which are likely to improve trust and make the role of the driver more transparent concerning their authority over the automated system
What the crash dummies don't tell you: The interaction between driver and automation in emergency situations
No full textSystems design is plagued by criticism for failing to adequately define the role of the human within the system as a whole. Autonomous Emergency Braking (AEB) systems automate elements of the driving task by warning the driver of a collision risk and, if necessary, applying the brakes to reduce collision impact. As with all automated technologies, questions remain over whether or not AEB fundamentally changes the driving task by affecting the ways in which the driver interacts with vehicle systems. In order to address these concerns, Operator Sequence Diagrams have been developed to provide an insight into the roles of the driver and vehicle sub-systems in an emergency situation using the distributed cognition approach
Contrasting models of driver behaviour in emergencies using retrospective verbalisations and network analysis
No full textAutomated assistance in driving emergencies aims to improve the safety of our roads by avoiding or mitigating the effects of accidents. However, the behavioural implications of such systems remain unknown. This paper introduces the driver decision-making in emergencies (DDMiEs) framework to investigate how the level and type of automation may affect driver decision-making and subsequent responses to critical braking events using network analysis to interrogate retrospective verbalisations. Four DDMiE models were constructed to represent different levels of automation within the driving task and its effects on driver decision-making. Findings suggest that whilst automation does not alter the decision-making pathway (e.g. the processes between hazard detection and response remain similar), it does appear to significantly weaken the links between information-processing nodes. This reflects an unintended yet emergent property within the task network that could mean that we may not be improving safety in the way we expect.Practitioner Summary: This paper contrasts models of driver decision-making in emergencies at varying levels of automation using the Southampton University Driving Simulator. Network analysis of retrospective verbalisations indicates that increasing the level of automation in driving emergencies weakens the link between information-processing nodes essential for effective decision-making.<br/
What the drivers do and don’t tell you: using verbal protocol analysis to investigate driver behaviour in emergency situations
No full textAlthough task analysis of pedestrian detection can provide us with useful insights into how a driver may behave in emergency situations, the cognitive elements of driver decision-making are less well understood. To assist in the design of future Advanced Driver Assistance Systems, such as Autonomous Emergency Brake systems, it is essential that the cognitive elements of the driving task are better understood. This paper uses verbal protocol analysis in an exploratory fashion to uncover the thought processes underlying behavioural outcomes represented by hard data collected using the Southampton University Driving Simulator
Driver-centred vehicle automation: using network analysis for agent-based modelling of the driver in highly automated driving systems
No full textTo the average driver, the concept of automation in driving infers that they can become completely 'hands and feet free'. This is a common misconception, however, one that has been shown through the application of Network Analysis to new Cruise Assist technologies that may feature on our roads by 2020. Through the adoption of a Systems Theoretic approach, this paper introduces the concept of driver-initiated automation which reflects the role of the driver in highly automated driving systems. Using a combination of traditional task analysis and the application of quantitative network metrics, this agent-based modelling paper shows how the role of the driver remains an integral part of the driving system implicating the need for designers to ensure they are provided with the tools necessary to remain actively in-the-loop despite giving increasing opportunities to delegate their control to the automated subsystems. Practitioner Summary: This paper describes and analyses a driver-initiated command and control system of automation using representations afforded by task and social networks to understand how drivers remain actively involved in the task. A network analysis of different driver commands suggests that such a strategy does maintain the driver in the control loop
Driving aviation forward: contrasting driving automation and aviation automation
No full textTechnological solutions incorporating automated functionality have been seen as tools that can be used to reduce human error in both aviation and driving environments whilst bringing about improvements to operational safety and reduced accident rates. Historically, aviation has led the way, but over recent years, developments in the field of driving automation have accelerated rapidly. This paper looks more closely at what aviation may now learn from driving by assessing the underlying motivations and use of automation within their respective fields, as well as the differing design philosophies used to implement such systems
Discovering Driver-vehicle Coordination Problems in Future Automated Control Systems: Evidence from Verbal Commentaries
No full textAbstractA critical question being asked by many vehicle manufacturers is what actually happens when the driver finds themselves being “hands and feet free” within their vehicles. This small exploratory case study was used to investigate the possible functionality of a Driver-Initiated Command and Control System of Automation. Verbalizations and subjective reports of mental workload and stress revealed evidence of different driver-vehicle coordination problems (i.e. mode error and automation surprise) based upon driver familiarity in driving with the system engaged
25 Years of road safety: The journey from thinking humans to systems-thinking
No full textResearch into road safety has evolved from individual level component analysis to a much broader, systemic approach that acknowledges the fusion of ‘socio’ and ‘technical’ system elements. Over the past four decades, Professor Neville Stanton has contributed to over 179 journal articles, book chapters and conference papers in the field of road safety. The journey from ‘thinking humans’ to ‘systems thinking’ is demonstrated in this paper through the novelapplication of the Risk Management Framework (RMF) to the categorisation of research activities. A systematic review of Neville’s contributions to the field of road safety demonstrates that over the years, his research activities have evolved from investigating single technological or human performance aspects in isolation (e.g., in-vehicle information design and workload) through to the holistic analysis of much broader systems (e.g., investigating road safety as a whole). Importantly, this evolution goes hand in hand with a change in the focus and emphasis of recommendations for improvements to safety. Goingforward, Neville has helped pave the way for fundamental changes and improvements to be made to road safety systems around the world
Leaps and shunts: designing pilot decision aids on the flight deck using Rasmussen’s ladder
No full textWhen designing a new pilot decision aid for the flight deck, it is important to understand ‘how’ pilots make decisions in abnormal operating scenarios so that we can ensure they are provided with appropriate support. This paper provides a decision ladder analysis of an aircraft engine oil leak using data collected from six commercial airline pilot interviews. Traditionally, decision-making models are used reactively as a means to explore why things go wrong. However, we explore whether these models can also be used prospectively. Our analysis yields a number of possible design implications for the design of a pilot decision aid on the flight deck
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