Exploring the bullying behaviours experienced by South African domestic workers

This article phenomenologically explores the nature of bullying behaviours as experienced by domestic workers in South Africa. Participants were a convenience sample of 10 black female domestic workers (age range = 27 to 53 years, work experience = 3 to 26 years). The domestic workers responded to an unstructured interview on their experience of work place bullying. Data were analysed using thematic analysis. Findings suggest that bullying is prevalent in domestic work and is perpetrated by both sexes and all races. Bullying behaviours were categorised into verbal bullying (belittlement, deception and false accusations) and non-verbal bullying (intimidation and excessive control, disregard for basic needs and wellbeing, disregard for employment legislation). Bullying behaviours towards domestic workers are explained by the historical socioeconomic disempowerment of domestic workers and a socio-legal system inaccessible to those with disadvantages.     

Somatoform dissociation in eating-disordered patients

This study investigated the role of somatoform dissociation in eating disorders and pathological eating behaviour, relative to the established association of eating pathology with psychological dissociation. The participants were 131 women with DSM-IV diagnoses of anorexic or bulimic disorders and 75 women who had no such disorder. Each woman completed measures of psychological and somatoform dissociation, as well as a measure of bulimic attitudes. The current presence or absence of specific bulimic behaviours was identified during the clinical interview. Levels of both forms of dissociation were higher in the women who had diagnoses of disorders with a bulimic component (bulimia nervosa; anorexia nervosa of the binge/purge subtype) than in the non-clinical or restrictive anorexic women. Somatoform dissociation showed particularly strong links with the presence of bulimic behavioural features (excessive exercise, laxative abuse, diet pill abuse, diuretic abuse) and with bulimic attitudes. The formulation and treatment of cases where there are bulimic features is likely to be enhanced by the assessment of somatoform dissociation.     

Public acceptance of driver state monitoring for automated vehicles: Applying the UTAUT framework

Driver state monitoring (DSM) systems aim to measure driver/occupant state, considering factors such as fatigue, workload, attentiveness, and wellbeing. They are influential for some vehicles on the road today, but as we move towards higher levels of automation their use is expected to become even more important. Uncertainty around public perception of these systems is a potentially limiting factor, with potential concerns for privacy, data storage, perceived utility, and reliability amongst other things posing potential threats. A survey was conducted based on the Universal Theory of Acceptance and Use of Technology (UTAUT) framework, which collected 311 individual responses to explore the acceptability of this technology in specific relation to conditionally and partially automated vehicles. This paper identified that the factors of effort expectancy, performance expectancy, social influence, and attitudes towards using new technology are all positively related to overall behavioural intention, whereas anxiety is negatively related. Other demographic influences are discussed, and recommendations made for future research and marketing/implementation of DSM systems to ensure acceptance by future users.     

Challenges for automated vehicle driver training: A thematic analysis from manual and automated driving

Considerable research and resources are going into the development and testing of Automated Vehicles. They are expected to bring society a huge number of benefits (such as: improved safety, increased capacity, reduced fuel use and emissions). Notwithstanding these potential benefits, there have also been a number of high-profile collisions involving Automated Vehicles on the road. In the majority of these cases, the driver’s inattention to the vehicle and road environment was blamed as a significant causal factor. This suggests that solutions need to be developed in order to enhance the benefits and address the challenges associated with Automated Vehicles. One such solution is driver training. As drivers still require manual driving skills when operating Automated Vehicles on the road, this paper applied the grounded theory approach to identify eight “key” themes and interconnections that exist in current manual vehicle driver training. These themes were then applied to the limited literature available on Automated Vehicle driver training, and a ninth theme of trust emerged. This helped to identify a set of training requirements for drivers of Automated Vehicles, which suggests that a multifaceted approach (covering all nine themes and manual and Automated Vehicle driving skills) to driver training is required. This framework can be used to develop and test a training programme for drivers of Automated Vehicles.     

Reducing optimism bias in the driver’s seat: Comparing two interventions

Optimism bias combined with sensation-seeking and risky driving have been proposed to be the main contributing factors to young drivers’ involvement in road traffic collisions. The present study aimed to evaluate how two brief interventions, one based on an unambiguous definition of “good” driving and the other on a hazard perception test, might reduce young drivers’ optimism bias. One hundred and twenty-eight university students were randomly allocated to one of three groups: standard definition, hazard perception or control. Measures evaluating optimism bias were completed before and after the intervention, and questions regarding their sensation-seeking and past risk-taking tendencies were asked at follow-up. Both brief interventions reduced optimism bias levels, but hazard perception had the strongest effect. The effectiveness of the two interventions also differed across individuals depending on their sensation-seeking and past risky driving tendencies. The results provide evidence for the effectiveness of brief interventions to reduce optimism bias.     

Smartphone Use While Driving: An Investigation of Young Novice Driver (YND) Behaviour

Road traffic collisions are the leading cause of death for those between the ages of 15–29, according to the World Health Organisation. This study investigates one of the primary reasons for the high fatality rate amongst Young Novice Drivers (YNDs) – their use of smartphones while driving. We gathered responses from a representative sample of YNDs on their behaviour while driving using an updated version of the ‘Behaviour of Young Novice Drivers Scale’. Survey responses totalled 700 YNDs situated throughout Germany. From these responses, we examined the prevalence of certain driving behaviours that are described as ‘distracting’ and compared these driving behaviours to the respondents’ use of specific smartphone features. The responses report that music-related activities (e.g. changing music on a smartphone) are most common amongst YNDs. Speaking on the phone is seldom-reported, although more males than females indicated engagement in this behaviour. We further carried out a correlation analysis and correspondence analysis. On that basis we found that those who report speaking on a smartphone are significantly more likely to engage in driving behaviours with potentially fatal consequences, such as speeding and driving while impaired by prohibited substances (drugs, alcohol). We propose that the results could be used by policymakers for public information implications and to tailor financial penalties for those engaging in smartphone behaviours that are linked to harmful driving behaviours. In addition, our findings can also be used in a Usage-based Insurance (UBI) context to financially incentivise safer driving.     

Effects of the cross-section on the driver’s behaviour approaching bicycle crossroads

This paper reports on the results of field surveys conducted at the approaching section of two bicycle crossroads in urban environment. The crossing roads are characterised by different cross-sections (one-lane and two-lane configurations) having a same marking scheme. The aim of the surveys was to evaluate the effectiveness of the specific marking scheme for the two different cross-sections and to provide relevant insight to improve the cyclist safety, based on the observed drivers’ behaviours. More specifically, the data analysis was aimed at: (i) studying the yielding behaviour of the drivers on the two bicycle configurations and evaluating the effects of the observed vehicle dynamics constraints in approaching phases; (ii) analysing drivers’ braking during the interaction with cyclist; (iii) defining a logistic regression model for predicting the drivers’ likelihood of yielding as a function of the variables describing his behaviour and the cross-section configurations. Results have stressed out a more critical driver yielding behaviour and braking performance when approaching the bicycle crossroad on the two-lane configuration. The logistic regression model have pointed out the cross-section variable to have the strongest effect on the logit of drivers yielding, determining a significant reduction of the likelihood of yielding if the interaction driver-cyclist occurs in the two-lane configuration. Overall, the obtained outcomes highlight a higher risk exposure of the cyclist crossing the two-lane configuration. The obtained outcomes imply that the same marking scheme on the two different cross-section configurations is inappropriate. It fails to induce proper driver behaviour when he/she approaches the bicycle crossing on the two-lane configuration in order to limit the cyclist's risk exposure to the values observed on the one-lane configuration. Eventually, several measures and recommendations have been defined to reduce the risk conditions identified in two-lane configuration.     

Analysis of the occurrence and severity of vehicle-pedestrian conflicts in marked and unmarked crosswalks through naturalistic driving study

BackgroundAlthough many studies have been conducted on the safety of pedestrian crossings, few researches have been focused on drivers' behavior in unmarked crosswalk and marked crosswalk areas. Considering that statistics of pedestrian accidents are not the same in the two types of crossing area, based on the last report of the World Health Organization, it is very critical to evaluate driver yielding behavior to determine the differences in the actions of drivers when encountering pedestrians in the two areas.MethodsThis study was conducted based on surrogate measures of safety (SMoS) collected through a Naturalistic Driving Study on 52 participants in Iran. The study was carried out from April 2017 to April 2018 using the installation of cameras in the private vehicle of the participants. The analysis of the recorded films showed that 956 conflicts have occurred in unmarked crosswalks and 392 conflicts in marked crosswalks, respectively.ResultsA model was developed for driver yielding behavior using binary logistic regression, and showed that yielding rates in unmarked crosswalsk were about fifty percent of the yielding rates in marked crosswalks. Based on the model, it is indicated that the aggressive behavior of pedestrians during the crossing, such as running, zigzag and diagonal crossing, as well as the late detection of pedestrians by drivers resulting from high-speed driving in the unmarked crossing areas, will reduce the yielding behavior rate. Also, using the Swedish traffic conflicts technique, the severity of the conflicts was classified into four general categories: encounter, potential, slight, and serious conflict, through 30 different levels on the basis of conflicting speed and time to the accident. The results showed that pedestrians behavior during conflicts of the group “encounter” and drivers’ behavior during conflicts of the groups of “potential”, “slight” and “serious”, were the principal factors in preventing collision through an evasive maneuver. The results showed that increasing the level of conflict severity, which indicates an increase of the conflicting speed and a decrease of the time remaining to point of a possible collision with pedestrian, causes drivers to yield a harsh-maneuver to prevent collision. Soft-maneuvers such as deceleration and acceleration, as well as harsh-maneuvers such as changing the lane/stop during conflicts were most driver yielding behavior during conflict groups of slight and serious. According to the results of the analysis, the behavior of drivers in marked crossing areas is better than in the unmarked crossing area, leading to safer crossing for pedestrians.ConclusionsThis study suggests that the significant differences in driver yielding behavior in the two areas is due to the late detection of pedestrians by drivers and also the less proper action by them in unmarked crosswalk areas. Thus, the probability of accidents in Unmarked Crossing areas is higher than in marked crossing areas. Consequently, the design of improved advanced driver assistance systems to identify the risk of pedestrian accident may improve the driver yielding behavior and thus increase the safety of pedestrians.     

Visualizing the autonomous vehicle’s maneuvers – Does an ecological interface help to increase the hedonic quality and safety?

This paper examines whether ecological speed information describing ongoing driving maneuvers during automated driving enhances the hedonic quality and driving safety immediately after a driving takeover. Visualizing maneuvers and trajectories has already proven effective. However, planned acceleration and deceleration in an automated vehicle have not yet been investigated. Therefore, this paper assesses how an automated vehicle’s speed control information might be presented by an ecological interface. Besides a possible increase in the hedonic quality, this information might enhance safe behavior of the human driver when it comes to a takeover. To assess these two aspects, 43 drivers participated in a dynamic driving simulator study. Using a within-subject design, two scenarios were used to compare an ecological interface, dynamically visualizing speed changes, to a conventional pop-up interface, using pop-up icons to visualize speed changes. The experimental results indicate that ecological feedback and conventional pop-up feedback do not differ regarding the hedonic quality, which was reflected by the state anxiety, usefulness, and satisfaction with the overall human-machine interface (HMI). Nonetheless, the post-hoc questionnaire on situational awareness showed a significantly lower rating for the ecological interface which may be the result of a more automatic and subconscious processing of the information given. Analyzing the takeover performance, the initial takeover time was comparably low for both interfaces. However, concerning safety, the ecological interface significantly enhanced the lateral control after takeover, and the drivers looked at the vehicle mirrors significantly earlier. In conclusion, the results show that the information given by the ecological interface may help drivers cope with a sudden takeover in a faster and more controlled way. Future applications of these findings might serve to enhance the acceptance and safety of semi-autonomous vehicles by implementing ecological interfaces.     

Exploring the benefits of conversing with a digital voice assistant during automated driving: A parametric duration model of takeover time

Vehicle automation allows drivers to disengage from driving causing a potential decline in their alertness. One of the major challenges of highly automated vehicles is to ensure a timely (with respect to safety and situation awareness) takeover in such conditions. For this purpose, the current study investigated the role of an in-vehicle digital voice-assistant (VA) in conditionally automated vehicles, offering spoken discourse relating specifically to contextual factors, such as the traffic situation and road environment. The study involved twenty-four participants, each taking two drives (counterbalanced): with VA and without VA, in a driving simulator. Participants were required to takeover vehicle control following the issuance of a takeover request (TOR) near the end of each drive. A parametric duration model was adopted to find the key factors determining takeover time (TOT). Paired comparisons showed higher alertness and higher active workload (mean NASA-TLX rating) during automation when accompanied by the VA. Paired t-test comparison of gaze behavior prior to takeover showed significantly higher instances of checking traffic signal, roadside objects, and the roadway during the drive with VA, indicating higher situation awareness. The parametric model indicated that the VA increased the likelihood of making a timely takeover by 39%. There was also some evidence suggesting that male drivers are likely to resume control 1.21 times earlier than female drivers. The study findings highlight the benefits of adopting a digital voice assistant to keep the drivers alert and aware about the recent traffic environment in partially automated vehicles.