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With remarkable advancements in the development of connected and autonomous vehicles (CAVs), the integration of teleoperation has become crucial for improving safety and operational efficiency. However, teleoperation faces substantial challenges, with network latency being a critical factor influencing its performance. This survey paper explores the impact of network latency along with state-of-the-art mitigation/compensation approaches. It examines cascading effects on teleoperation communication links (i.e., uplink and downlink) and how delays in data transmission affect the real-time perception and decision-making of operators. By elucidating the challenges and available mitigation strategies, the paper offers valuable insights for researchers, engineers, and practitioners working towards the seamless integration of teleoperation in the evolving landscape of CAVs.

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Trams are experiencing a resurgence with worldwide network expansion driven by the need for sustainable and efficient cities. Trams often operate in shared or mixed-traffic environments, which raise safety concerns, particularly in hazardous situations. This paper adopts an international, mixed-methods approach, conducted through two interconnected studies in Melbourne (Australia) and Birmingham (UK). The first study involved qualitative interviews, while the second was an experimental study involving a virtual reality (VR) simulator and haptic master controller (i.e., speed lever). In tram operations, master controllers play a critical role in ensuring a smooth ride, which directly influences passenger safety and comfort. The objective was to understand how a master control system, enhanced with additional haptic feedback, could improve tram driver braking performance and perceptions in safety-critical scenarios. Interview results indicate that the use of the emergency brake is considered the final or ultimate choice by drivers, and their driving experience is a moderating factor in limiting its application. Combined with the experimental results, this paper highlights how implementing haptic feedback within a master controller can reduce the performance disparity between novice and experienced tram drivers.

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OBJECTIVE: Using brain haemodynamic responses to measure perceived risk from traffic complexity during automated driving. BACKGROUND: Although well-established during manual driving, the effects of driver risk perception during automated driving remain unknown. The use of fNIRS in this paper for assessing drivers' states posits it could become a novel method for measuring risk perception. METHODS: Twenty-three volunteers participated in an empirical driving simulator experiment with automated driving capability. Driving conditions involved suburban and urban scenarios with varying levels of traffic complexity, culminating in an unexpected hazardous event. Perceived risk was measured via fNIRS within the prefrontal cortical haemoglobin oxygenation and from self-reports. RESULTS: Prefrontal cortical haemoglobin oxygenation levels significantly increased, following self-reported perceived risk and traffic complexity, particularly during the hazardous scenario. CONCLUSION: This paper has demonstrated that fNIRS is a valuable research tool for measuring variations in perceived risk from traffic complexity during highly automated driving. Even though the responsibility over the driving task is delegated to the automated system and dispositional trust is high, drivers perceive moderate risk when traffic complexity builds up gradually, reflected in a corresponding significant increase in blood oxygenation levels, with both subjective (self-reports) and objective (fNIRS) increasing further during the hazardous scenario. APPLICATION: Little is known regarding the effects of drivers' risk perception with automated driving. Building upon our experimental findings, future work can use fNIRS to investigate the mental processes for risk assessment and the effects of perceived risk on driving behaviours to promote the safe adoption of automated driving technology.

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Given the rise of automated vehicles from an engineering and technical perspective, there has been increased research interest concerning the Human and Computer Interactions (HCI) between vulnerable road users (VRUs, such as cyclists and pedestrians) and automated vehicles. As with all HCI challenges, clear communication and a common understanding-in this application of shared road usage-is critical in order to reduce conflicts and crashes between the VRUs and automated vehicles. In an effort to solve this communication challenge, various external human-machine interface (eHMI) solutions have been developed and tested across the world. This paper presents a timely critical review of the literature on the communication between automated vehicles and VRUs in shared spaces. Recent developments will be explored and studies analyzing their effectiveness will be presented, including the innovative use of Virtual Reality (VR) for user assessments. This paper provides insight into several gaps in the eHMI literature and directions for future research, including the need to further research eHMI effects on cyclists, investigate the negative effects of eHMIs, and address the technical challenges of eHMI implementation. Furthermore, it has been underlined that there is a lack of research into the use of eHMIs in shared spaces, where the communication and interaction needs differ from conventional roads.

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One major challenge for automated cars is to not only be safe, but also secure. Indeed, connected vehicles are vulnerable to cyberattacks, which may jeopardize individuals' trust in these vehicles and their safety. In a driving simulator experiment, 38 participants were exposed to two screen failures: silent (i.e., no turn signals on the in-vehicle screen and instrument cluster) and explicit (i.e., ransomware attack), both while performing a non-driving related task (NDRT) in a conditionally automated vehicle. Results showed that objective trust decreased after experiencing the failures. Drivers took over control of the vehicle and stopped their NDRT more often after the explicit failure than after the silent failure. Lateral control of the vehicle was compromised when taking over control after both failures compared to automated driving performance. However, longitudinal control proved to be smoother in terms of speed homogeneity compared to automated driving performance. These findings suggest that connectivity failures negatively affect trust in automation and manual driving performance after taking over control. This research posits the question of the importance of connectivity in the realm of trust in automation. Finally, we argue that engagement in a NDRT while riding in automated mode is an indicator of trust in the system and could be used as a surrogate measure for trust.

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The concept of vehicle automation ceases to seem futuristic with the current advancement of the automotive industry. With the introduction of conditional automated vehicles, drivers are no longer expected to focus only on driving activities but are still required to stay alert to resume control. However, fluctuations in driving demands are known to alter the driver's mental workload (MWL), which might affect the driver's vehicle take-over capabilities. Driver mental workload can be specified as the driver's capacity for information processing for task performance. This paper summarizes the literature that relates to analysing driver mental workload through various in-vehicle physiological sensors focusing on cardiovascular and respiratory measures. The review highlights the type of study, hardware, method of analysis, test variable, and results of studies that have used physiological indices for MWL analysis in the automotive context.

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Human factors research can play an important role in the successful design of infrastructure to support future mobility. Through engaging users and stakeholders early in the design process we can gain insights before the physical environments are built. This paper presents data from a truly novel application of Virtual Reality (VR), where user experience and wayfinding were evaluated within an emerging future transport infrastructure to support urban air mobility (UAM) - the urban airport (aka vertiports). Urban airports are located in city centres where drones or 'flying cars' would land and take off from. Previous quantitative studies have investigated passenger experience in traditional airports using field observation and surveys, but this paper is the first to present qualitative research on user experience in this emerging mobility infrastructure using an immersive VR environment. Twenty participants completed a series of six scenarios aimed at understanding customer 'exciters' and 'pain points' within an urban airport. Results and recommendations from this empirical research will help inform the design of all future mobility infrastructure solutions, through improving user experience before the infrastructure is physically deployed. Finally, this paper highlights the benefits of engaging users at an early stage of the design process to ensure that future transport infrastructure will be accessible, easy to navigate and a pleasure to use.

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This research paper explores the impact of cognitive load on drivers' physiological state and driving performance during an automated driving to manual control transition scenario, using a driving simulator. Whilst driving in the automated mode, cognitive load was manipulated using the "N-Back" task, which participants engaged with via a visual display. Results suggest that non-optimal levels of workload during the automated driving conditions impair driving performance, especially lateral control of the vehicle, and the magnitude of this impairment varied with increasing cognitive load. In addition to these findings, the present paper introduces a novel method for determining stabilisation times of both driver state and driving performance indicators following a transition of vehicle control. Using this method we demonstrate that mean and standard deviation of lane position impairments were found to take longer to stabilise following transition to manual driving following a higher level of cognitive load during the automated driving period, taking up to 22 s for driving performance to normalise after take-over. In addition, heart rate parameters take between 20 and 30 s to stabilise following a planned take-over request. Finally, this paper demonstrates how the magnitude of cognitive load can be estimated in context of automated driving using physiological measures, captured by consumer electronic devices. We discuss the impact our findings have on the design of SAE Level 3 systems. Relevant suggestions are provided to the research community and automakers working on future implementation of vehicles capable of conditional automation.

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Everyone can be susceptible to motion sickness (except those with complete loss of labyrinth function) and around one in three are known to be servery susceptible. Motion sickness can be experienced in many domains, including car travel, on a boat, using virtual reality headsets and simulator use amongst others. It is expected that due to potential designs and use cases, self-driving cars will increase motion sickness onset likelihood and severity for many car travellers. Besides medication, there are limited methods through which one can actively reduce their motion sickness susceptibility. This research develops a novel visuospatial training tool and explores the effect of visuospatial training on motion sickness. With a combined sample of 42 participants split between driving simulator trials (n = 20), and on-road trials (n = 22) baseline visuospatial skills and motion sickness were first measured. After a 14-day training period where participates completed 15-min of pen and paper tasks per day, it was found that visuospatial skills improved by 40%. This increase in visuospatial ability was shown to be directly responsible for a reduction in motion sickness by 51% in the simulator (with a 60% reduction in participant dropouts) and a 58% reduction in the on-road trial. This research has successfully identified a new method to reduce motion sickness susceptibility and the impact of these findings have wide reaching implications for motion sickness research, especially in the field of self-driving vehicles.

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The aim of this research is to investigate whether visual feedback alone can affect a driver's trust in an autonomous vehicle, and in particular, what level of feedback (no feedback vs. moderate feedback vs. high feedback) will evoke the appropriate level of trust. Before conducting the experiment, the Human Machine Interfaces (HMI) were piloted with two sets of six participants (before and after iterations), to ensure the meaning of the displays can be understood by all. A static driving simulator experiment was conducted with a sample of 30 participants (between 18 and 55). Participants completed two pre-study questionnaires to evaluate previous driving experience, and attitude to trust in automation. During the study, participants completed a trust questionnaire after each simulated scenario to assess their trust level in the autonomous vehicle and HMI displays, and on intention to use and acceptance. The participants were shown 10 different driving scenarios that lasted approximately 2 minutes each. Results indicated that the 'high visual feedback' group recorded the highest trust ratings, with this difference significantly higher than for the 'no visual feedback' group (U = .000; p = <0.001 < α) and the 'moderate visual feedback' group (U = .000; p = <0.001 < α). There is an upward inclination of trust in all groups due to familiarity to both the interfaces and driving simulator over time. Participants' trust level was also influenced by the driving scenario, with trust reducing in all displays during safety verses non-safety-critical situations.

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Motion sickness (MS) is known to be a potentially limiting factor for future self-driving vehicles - specifically in regards to occupant comfort and well-being. With this as a consideration comes the desire to accurately measure, track and even predict MS state in real-time. Previous research has considered physiological measurements to measure MS state, although, this is mainly measured after an MS exposure and not throughout exposure(s) to a MS task. A unique contribution of this paper is in the real-time tracking of subjective MS alongside real-time physiological measurements of Electrodermal Activity (EDA) and skin temperature. Data was collected in both simulator-based (controlled) and on-road (naturalistic) studies. 40 participants provided at total of 61 data sets, providing 1603 min of motion sickness data for analysis. This study is in agreement that these measures are related to MS but evidenced a total lack of reliability for these measures at an individual level for both simulator and on-road experimentation. It is likely that other factors, such as environment and emotional state are more impactful on these physiological measures than MS itself. At a cohort level, the applicability of physiological measures is not considered useful for measuring MS accurately or reliably in real-time. Recommendations for further research include a mixed-measures approach to capture other data types (such as subject activity) and to remove contamination of physiological measures from environmental changes.

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Customer-facing train crew members have to follow strict procedures to guarantee that trains are safe and run on time. They are also responsible for revenue protection and customer care. Human factors and ergonomics research are instrumental to understand the safety-critical aspects and improve work. We bring user experience research and personas to describe how train crew perceive their routines and how new technology may impact them. We conducted 7 hours of interviews and 30 hours of shadowing observations with the train crew (N = 22) to provide an understanding of who are they and to define their experiences. We present the crew's current routines and created two personas to represent them. One is slightly reluctant to adopt the proposed technology, whereas the other is more accepting. Results indicate how such technology may affect crew work ergonomics and experiences, and suggest which valuable aspects should be maintained, for example the positive interactions with passengers. Practitioner summary: This study investigated the work routines of the customer-facing train crew. Interviews and shadowing were conducted with 22 crew from a large operator in the UK. Personas were created to represent them. Results show their preferred activities and how these would be affected by the introduction of new technology. Abbreviations: CH; customer host (onboard catering staff); DOO: driver-only operation; ETA: estimated time of arrival; PTI: platform-train interface; TM: train manager (onboard customer-facing authority); UCD: user-centred design; UX: user experience.

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Technological developments present diverse opportunities to modernise services for the rail industry. Systems can be implemented to improve passengers' experiences, but these may also affect the experiences of crew working on board trains. This first-of-a-kind research extends the concept of customer journey mapping as a design tool to understand the experiences of train crew. To produce these crew journey maps, interviews and user observation methods were adopted (N = 22). Results show that two main negative touchpoints for the crew occur at the platform-train interface and during revenue protection activities. This paper presents an innovative methodological contribution around journey mapping to better understand rail experiences, but revolving around the crew rather than the expected consumer experience. We conclude this paper proposing requirements for technological systems and indicate opportunities for the design of systems to generate human-centred improvements for the working practices and experiences of train crew.

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Partially automated vehicles present interface design challenges in ensuring the driver remains alert should the vehicle need to hand back control at short notice, but without exposing the driver to cognitive overload. To date, little is known about driver expectations of partial driving automation and whether this affects the information they require inside the vehicle. Twenty-five participants were presented with five partially automated driving events in a driving simulator. After each event, a semi-structured interview was conducted. The interview data was coded and analysed using grounded theory. From the results, two groupings of driver expectations were identified: High Information Preference (HIP) and Low Information Preference (LIP) drivers; between these two groups the information preferences differed. LIP drivers did not want detailed information about the vehicle presented to them, but the definition of partial automation means that this kind of information is required for safe use. Hence, the results suggest careful thought as to how information is presented to them is required in order for LIP drivers to safely using partial driving automation. Conversely, HIP drivers wanted detailed information about the system's status and driving and were found to be more willing to work with the partial automation and its current limitations. It was evident that the drivers' expectations of the partial automation capability differed, and this affected their information preferences. Hence this study suggests that HMI designers must account for these differing expectations and preferences to create a safe, usable system that works for everyone.

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OBJECTIVE: This study investigates the influence of shoe type (sneakers and safety boots), age, and gender on the perception of haptic pulse feedback provided by a prototype accelerator pedal in a running stationary vehicle. BACKGROUND: Haptic feedback can be a less distracting alternative to traditionally visual and auditory in-vehicle feedback. However, to be effective, the device delivering the haptic feedback needs to be in contact with the person. Factors such as shoe type vary naturally over the season and could render feedback that is perceived well in one situation, unnoticeable in another. In this study, we evaluate factors that can influence the subjective perception of haptic feedback in a stationary but running car: shoe type, age, and gender. METHOD: Thirty-six drivers within three age groups (≤39, 40-59, and ≥60) took part. For each haptic feedback, participants rated intensity, urgency, and comfort via a questionnaire. RESULTS: The perception of the haptic feedback is significantly influenced by the interaction between the pulse's duration and force amplitude and the participant's age and gender but not shoe type. CONCLUSION: The results indicate that it is important to consider different age groups and gender in the evaluation of haptic feedback. Future research might also look into approaches to adapt haptic feedback to the individual driver's preferences. APPLICATION: Findings from this study can be applied to the design of an accelerator pedal in a car, for example, for a nonvisual in-vehicle warning, but also to plan user studies with a haptic pedal in general.

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The use of haptic feedback is currently an underused modality in the driving environment, especially with respect to vehicle manufacturers. This exploratory study evaluates the effects of a vibrotactile (or haptic) accelerator pedal on car driving performance and perceived workload using a driving simulator. A stimulus was triggered when the driver exceeded a 50% throttle threshold, past which is deemed excessive for economical driving. Results showed significant decreases in mean acceleration values, and maximum and excess throttle use when the haptic pedal was active as compared to a baseline condition. As well as the positive changes to driver behaviour, subjective workload decreased when driving with the haptic pedal as compared to when drivers were simply asked to drive economically. The literature suggests that the haptic processing channel offers a largely untapped resource in the driving environment, and could provide information without overloading the other attentional resource pools used in driving. PRACTITIONER SUMMARY: Overloaded or distracted drivers present a real safety danger to themselves and others. Providing driving-related feedback can improve performance but risks distracting them further; however, giving such information through the underused haptic processing channel can provide the driver with critical information without overloading the driver's visual channel.

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Road transport is a significant source of both safety and environmental concerns. With climate change and fuel prices increasingly prominent on social and political agendas, many drivers are turning their thoughts to fuel efficient or 'green' (i.e., environmentally friendly) driving practices. Many vehicle manufacturers are satisfying this demand by offering green driving feedback or advice tools. However, there is a legitimate concern regarding the effects of such devices on road safety--both from the point of view of change in driving styles, as well as potential distraction caused by the in-vehicle feedback. In this paper, we appraise the benchmarks for safe and green driving, concluding that whilst they largely overlap, there are some specific circumstances in which the goals are in conflict. We go on to review current and emerging in-vehicle information systems which purport to affect safe and/or green driving, and discuss some fundamental ergonomics principles for the design of such devices. The results of the review are being used in the Foot-LITE project, aimed at developing a system to encourage 'smart'--that is safe and green--driving.

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Military personnel carry their equipment in load carriage systems (LCS) which consists of webbing and a Bergen (aka backpack). In scientific terms it is most efficient to carry load as close to the body's centre of mass (CoM) as possible, this has been shown extensively with physiological studies. However, less is known regarding the kinetic effects of load distribution. Twelve experienced load carriers carried four different loads (8, 16, 24 and 32 kg) in three LCS (backpack, standard and AirMesh). The three LCS represented a gradual shift to a more even load distribution around the CoM. Results from the study suggest that shifting the CoM posteriorly by carrying load solely in a backpack significantly reduced the force produced at toe-off, whilst also decreasing stance time at the heavier loads. Conversely, distributing load evenly on the trunk significantly decreased the maximum braking force by 10%. No other interactions between LCS and kinetic parameters were observed. Despite this important findings were established, in particular the effect of heavy load carriage on maximum braking force. Although the total load carried is the major cause of changes to gait patterns, the scientific testing of, and development of, future LCS can modify these risks.

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The 3-D gait analysis of military load carriage is not well represented, if at all, within the available literature. This study collected 3-D lower limb kinematics and spatiotemporal parameters in order to assess the subsequent impact of carrying loads in a backpack of up to 32 kg. Results showed the addition of load significantly decreased the range of motion of flexion/extension of the knee and pelvic rotation. Also seen were increases in adduction/abduction and rotation of the hip and pelvis tilt. No changes to ankle kinematics were observed. Alterations to the spatiotemporal parameters of gait were also of considerable interest, namely, an increase in double support and a decrease in preferred stride length as carried load increased. Analysing kinematics during military or recreational load carriage broadens the knowledge regarding the development of exercise-related injuries, while helping to inform the human-centred design process for future load carrying systems. The importance of this study is that limited available research has investigated 3-D lower limb joint kinematics when carrying loads.

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OBJECTIVE: Limited research has been conducted into the effect of load carriage on discomfort and injuries. This study aimed to determine the skeletal discomfort for part-time soldiers who completed a 1-hour field march carrying 24 kg. METHODS: A postmarch comfort questionnaire was completed by 127 participants, with exercise withdrawals and postmarch injuries also recorded. RESULTS: The foot was subjectively rated as the most uncomfortable skeletal region. Females reported hip discomfort to be significantly greater than males. The military experience of participants had no difference on the mean perceived comfort ratings of any of the measured regions. Finally, only one participant withdrew from the exercise, with no participants reporting a load carriage injury in the 2 to 3 days proceeding the exercise CONCLUSIONS: This study concludes that although a 1-hour period of load carriage causes noteworthy discomfort it is not sufficient to result in noncompletion of a military exercise or cause injury.

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