Distressed in the queue? Psychophysiological and behavioral evidence for two alternative car-following techniques

BackgroundNature offers numerous examples of animal species exhibiting harmonious collective movement. Unfortunately, the motorized Homo sapiens sapiens is not included and pays a price for it. Too often, drivers who simply follow other drivers are caught in the worst road threat after a crash: congestions. In the past, the solution to this problem has gone hand in hand with infrastructure investment. However, approaches such as the Nagoya Paradigm propose now to see congestion as the consequence of multiple interacting particles whose disturbances are transmitted in a waveform. This view clashes with a longlasting assumption ordering traffic flows, the rational driver postulate (i.e., drivers’ alleged propensity to maintain a safe distance). Rather than a mere coincidence, the worldwide adoption of the safety-distance tenet and the worldwide presence of congestion emerge now as cause and effect. Nevertheless, nothing in the drivers’ endowment impedes the adoption of other car-following (CF) strategies. The present study questions the a priori of safety-distance, comparing two elementary CF strategies, Driving to keep Distance (DD), that still prevails worldwide, and Driving to keep Inertia (DI), a complementary CF technique that offsets traffic waves disturbances, ensuring uninterrupted traffic flows. By asking drivers to drive DD and DI, we aim to characterize both CF strategies, comparing their effects on the individual driver (how he drives, how he feels, what he pays attention to) and also on the road space occupied by a platoon of DD robot-followers.MethodsThirty drivers (50% women) were invited to adopt DD/DI in a driving simulator following a swinging leader. The design was a repeated measures model controlling for order. The CF technique, DD or DI, was the within-subject factor. Order (DD-DI / DI-DD) was the between-subjects factor. There were four blocks of dependent measures: individual driving performance (accelerations, decelerations, crashes, distance to lead vehicle, speed and fuel consumption), emotional dimensions (measures of skin conductance and self-reports of affective states concerning valence, arousal, and dominance), and visual behavior (fixations count and average duration, dwell times, and revisits) concerning three regions of the driving scene (the Top Rear Car –TRC- or the Bottom Rear Car –BRC- of the leading vehicle and the surrounding White Space Area -WSA). The final block concerned the road space occupied by a platoon of 8 virtual DD followers.ResultsDrivers easily understood and applied DD/DI as required, switching back and forth between the two. Average speeds for DD/DI were similar, but DD drivers exhibited a greater number of accelerations, decelerations, speed variability, and crashes. Conversely, DI required greater CF distance, that was dynamically adjusted, and spent less fuel. Valence was similar, but DI drivers felt less aroused and more dominant. When driving DD visual scan was centered on the leader’s BRC, whereas DI elicited more attention to WSA (i.e., adopting wider vision angles). In spite of DI requiring more CF distance, the resulting road space occupied between the leader and the 8th DD robot was greater when driving DD.     

On-to-off-path gaze shift cancellations lead to gaze concentration in cognitively loaded car drivers: A simulator study exploring gaze patterns in relation to a cognitive task and the traffic environment

Appropriate visual behaviour is necessary for safe driving. Many previous studies have found that when performing non-visual cognitive tasks, drivers typically display an increased amount of on-path glances, along with a deteriorated visual scanning pattern towards potential hazards at locations outside their future travel path (off-path locations). This is often referred to as a gaze concentration effect. However, what has not been explored is more precisely how and when gaze concentration arises in relation to the cognitive task, and to what extent the timing of glances towards traffic-situation relevant off-path locations is affected. To investigate these specific topics, a driving simulator study was carried out. Car drivers’ visual behaviour during execution of a cognitive task (n-back) was studied during two traffic scenarios; one when driving through an intersection and one when passing a hidden exit. Aside from the expected gaze concentration effect, several novel findings that may explain this effect were observed. It was found that gaze shifts from an on-path to an off-path location were inhibited during increased cognitive load. However, gaze shifts in the other direction, that is, from an off-path to an on-path location, remained unaffected. This resulted in on-path glances increasing in duration, while off-path glances decreased in number. Furthermore, the inhibited off-path glances were typically not compensated for later. That is, off-path glances were cancelled, not delayed. This was the case both in relation to the cognitive task (near-term) and the traffic environment (far-term). There was thus a general reduction in the number of glances towards situationally relevant off-path locations, but the timing of the remaining glances was unaffected. These findings provide a deeper understanding of the mechanism behind gaze concentration and can contribute to both understanding and prediction of safety relevant effects of cognitive load in car drivers.     

Integrated mindfulness-based intervention: Effects on mindfulness skills,cognitive interference and performance satisfaction of young elite badminton players

ObjectivesMindfulness- and acceptance-based interventions (MABI) in sport settings need further development and validation to fulfil the desired outcomes related to sport performance. The current study aimed to design and implement a MABI integrated into the badminton training of young elite players (MBI programme), and to investigate its impact on sport performance-related outcomes.DesignTwo stages: (a) design and implementation of the MBI programme, and (b) evaluation using a mixed methods approach.MethodParticipants were young elite badminton players, assigned either to the 8-week MBI programme (n = 18; M_age = 16.22), or the 8-week placebo programme (n = 11; M_age = 16.64). Participants completed pre- and post-intervention measures of mindfulness skills, cognitive interference, and performance satisfaction. Social validation interviews were conducted with MBI participants to collect their overall perceptions of the programme.ResultsMANCOVA indicated a large intervention effect on the main outcome variables (partial η² = 0.58). The results of univariate ANCOVAs showed that post-intervention awareness, performance worries and task-irrelevant thoughts differed significantly across the groups. In addition, follow-up t-tests provided additional information regarding changes from pre- to post-intervention among the MBI and control groups separately. Social validation data gave further insights into what athletes had retained and applied from the MBI programme.ConclusionsContrasting results highlighted the need to better explore mindfulness mechanisms in MABI and the way they are inter-related, in order to strengthen changes in sport performance-related outcomes.     

Everyday risk taking as a function of regulatory focus

Uncertainty is an inherent aspect of everyday life. However, faced with uncertainty, some individuals take risks more eagerly than others. Regulatory focus theory may explain such differences because risky behavior may arise naturally from the eagerness of promotion focused individuals, while safe behavior may arise naturally from the vigilance of prevention focused individuals. A highly relevant real-life context for studying risk is mobility, as engaging in traffic inherently carries uncertainty about negative outcomes. We present two studies showing a direct link between regulatory focus and risky behavior going beyond traditional laboratory approaches. In both naturalistic speeding behavior (Study 1) and simulated risk taking (Study 2) promotion focus was positively, and prevention focus was negatively related to actual risky behavior.     

Traffic safety climate attitudes of road users in Germany

This paper validates traffic safety climate attitudes based on a representative sample of road users of all travel modes. We use the German version of the Traffic Climate Scale (TCS) which was applied in a large-scale road safety survey in 2010. A total of 1680 people were surveyed. The sample is representative for socio-demographic characteristics and travel mode choice in Germany. Factor analysis reveals a three-factor structure of traffic safety climate with the factor ‘External affective demands’ describing emotional engagement in traffic, the factor ‘Internal requirements’ representing individual skills and abilities to successfully participate in traffic, and the factor ‘Functionality’ describing requirements for a functional traffic system. The less emotionally demanding and the more functional traffic is perceived to be, the safer people feel in traffic. External affective demands are consistently related to the perception of others’ driving/riding style but not to one’s own, whereas internal requirements are consistently related to one’s own driving/riding style but not to the perception of others. There is no relation between traffic safety climate and accidents or near accidents. Contrary to our expectations, a positive traffic safety climate is associated with more secondary tasks while driving and traffic violations. Behavioural control beliefs may mediate the traffic climate–traffic behaviour relationship. The results are discussed with reference to attitude research and the theory of planned behaviour in particular.     

Introducing naturalistic cycling data: What factors influence bicyclists’ safety in the real world?

Presently, the collection and analysis of naturalistic data is the most credited method for understanding road user behavior and improving traffic safety. Such methodology was developed for motorized vehicles, such as cars and trucks, and is still largely applied to those vehicles. However, a reasonable question is whether bicycle safety can also benefit from the naturalistic methodology, once collection and analyses are properly ported from motorized vehicles to bicycles. This paper answers this question by showing that instrumented bicycles can also collect analogous naturalistic data. In addition, this paper shows how naturalistic cycling data from 16 bicyclists can be used to estimate risk while cycling. The results show that cycling near an intersection increased the risk of experiencing a critical event by four times, and by twelve times when the intersection presented some form of visual occlusion (e.g., buildings and hedges). Poor maintenance of the road increased the risk tenfold. Furthermore, the risk of experiencing a critical event was twice as large when at least one pedestrian or another bicyclist crossed the bicyclist’s trajectory. Finally, this study suggests the two most common scenarios for bicycle accidents, which result from different situations and thus require different countermeasures. The findings presented in this paper show that bicycle safety can benefit from the naturalistic methodology, which provides data able to guide development and evaluation of (intelligent) countermeasures to increase cycling safety.     

External communication of automated vehicles in mixed traffic: Addressing the right human interaction partner in multi-agent simulation

The urban traffic system is most likely to change in the next years to a mixed traffic with human drivers, vulnerable road users, and automated vehicles. In the past, the development of external communication approaches for automated vehicles focused on scenarios where an automated vehicle communicates with either a pedestrian or a human driver. However, interactions with more than one traffic partner are more realistic. Therefore, a study with 42 participants was conducted with a multi-agent simulation in which an automated vehicle interacted simultaneously with two participants, a pedestrian and a driver of a manual vehicle. In this study, two main scenarios were investigated in order to evaluate the safety and efficiency of the interactions and to determine whether the human road users feel correctly addressed. In one scenario, the pedestrian had to cross the road in front of the automated and the manual vehicle, which were approaching from different sides. In the other, the manual vehicle had to drive through a bottleneck in front of the oncoming automated vehicle, while the pedestrian had to cross the road after both vehicles passed. The communication approach of the automated vehicle consisted of implicit signals using a speed profile and lateral offset within its lane, and explicit signals using an external human–machine interface. The results of the study show that no collisions were observed in terms of safety and no significant negative effects on efficiency were measured. However, in contrast to single agent interactions, a majority of participants felt wrongly addressed in situations where the automated vehicle signals the right-of-way to the other human road user. It can be concluded that the communication approach of the automated vehicle needs to be modified in order to address certain road users more clearly.     

Why male adolescent bicyclists perform risky stunts? A qualitative study

Stunts are one of the main reasons for traffic accidents, particularly among male adolescent bicyclists (ABs). Nonetheless, there are limited data about the theoretical framework of its contributing factors. Moreover, the theoretical frameworks explaining the factors contributing to other risky behaviors have not been used in the area of risky bicycle stunts. The aim of this qualitative study was to explore the factors contributing to risky stunts among male ABs in Iran. This qualitative study was conducted from September 2019 to December 2020 using conventional content analysis. Participants were 29 male ABs purposively selected from Isfahan, Iran. Data were collected through eighteen interviews with sixteen ABs and three focus group discussions with thirteen ABs. Data analysis was conducted concurrently with data collection through conventional qualitative content analysis. The mean of participants’ age was 16.4 ± 1.1 years. Factors contributing to their engagement in risky stunts were grouped into three main themes, namely predisposing personal factors (such as risk underestimation, perceived superiority, sensation seeking, emotional condition, and previous stunt-related experiences), reinforcing social factors (such as supportive social norms and weaknesses of traffic regulations), and environmental conditions (such as time conditions and structural factors). This study provides a new classification of the facilitators to risky stunts among male ABs and reveals new facilitators to these stunts, namely perceived superiority and police non-deterrent reactions to stunts. Therefore, programs on the improvement of safe bicycling should focus not only on perceptual and emotional factors and correction of false perceived superiority through education, but also on social norms and beliefs, regulations, and environmental factors.     

Using generalized additive (mixed) models to analyze single case designs

This article shows how to apply generalized additive models and generalized additive mixed models to single-case design data. These models excel at detecting the functional form between two variables (often called trend), that is, whether trend exists, and if it does, what its shape is (e.g., linear and nonlinear). In many respects, however, these models are also an ideal vehicle for analyzing single-case designs because they can consider level, trend, variability, overlap, immediacy of effect, and phase consistency that single-case design researchers examine when interpreting a functional relation. We show how these models can be implemented in a wide variety of ways to test whether treatment is effective, whether cases differ from each other, whether treatment effects vary over cases, and whether trend varies over cases. We illustrate diagnostic statistics and graphs, and we discuss overdispersion of data in detail, with examples of quasibinomial models for overdispersed data, including how to compute dispersion and quasi-AIC fit indices in generalized additive models. We show how generalized additive mixed models can be used to estimate autoregressive models and random effects and discuss the limitations of the mixed models compared to generalized additive models. We provide extensive annotated syntax for doing all these analyses in the free computer program R.     

Professional drivers’ fatigue as a problem of the modern era

ObjectiveAll around the world numerous studies have been carried out and indicated that 20–50% of commercial vehicle accidents occur because of fatigue. Professional drivers represent an important category of drivers who are present in traffic on a daily basis transporting passengers or goods and their responsibility is at a very high level. These drivers are most exposed to the impact of fatigue. The review of the literature has provided three main factors which can influence the onset of fatigue: sleep factors, work factors, health factors. The main aim of this study was to determine the influence of the three main factors of fatigue between bus and truck drivers in the Republic of Serbia.MethodsThe survey has been conducted among bus and truck drivers who are employed in transportation companies across the Republic of Serbia. The research consists of collecting and analyzing bus and truck drivers’ answers according to the above mentioned factors which influence the occurrence of fatigue.ResultsIn this study we have found that circadian rhythm, sleep and work factors have an impact on drivers’ fatigue. On the other side, time of going to sleep has no impact on the quality of sleep and on fatigue. The results show that if the drivers work over the legal limit, they are 3 times more likely to sleep less than 6 h in 24 h and if they sleep less than 6 h, it is likely that the poor quality of their sleep will be 8 times higher. The poor quality of sleep reduces driver performance, and therefore increases the risk of accidents.Conclusions2 of 3 investigated factors have an impact on the occurrence of fatigue. The third factor, health factor, should be examined in more detail, and other elements should be analysed in order to determine their influence on the fatigue.