Do early birds share their worms? How prosocial behaviour and empathy vary across the day

Social behaviours have been proposed to follow circadian patterns across the course of the day, but empirical support is mixed. As a within-subject test of circadian effects on everyday behaviour, we conduct an experience-sampling study with a near-representative population of 285 Americans (7405 observations). Prosocial behaviour and empathy were both somewhat more frequent in the morning (d = 0.08). However, these non-linear patterns only described morning-type participants; evening-types had consistent (and lower) rates of prosocial behaviour and empathy across time-of-day. These patterns were explained by morning-types reporting more social opportunities earlier in the day. These findings suggest that small, within-subject diurnal effects on social behaviour occur in daily life, and that some circadian effects may be driven by situation selection.     

被动性社交网站使用与青少年体像烦恼的关系:体像比较和体像自我差异的中介作用

为探讨被动性社交网站使用和青少年体像烦恼的关系,基于社会比较理论和自我差异理论,采用被动性社交网站使用问卷、社交网站体像比较量表、理想体像问卷和体像烦恼量表,对789名初、高中生进行调查。结果表明：（1）被动性社交网站使用对青少年体像烦恼具有显著的正向预测作用;（2）体像比较和体像自我差异能在被动性社交网站使用和体像烦恼的关系中起中介作用;（3）在被动性社交网站使用与体像烦恼的关系中,女生的体像比较和体像自我差异起并行中介作用,而对男生而言,体像比较和体像自我差异起链式中介作用。研究结果表明被动性社交网站使用不仅能直接影响青少年的体像烦恼,还可通过体像比较和体像自我差异的间接作用对青少年体像烦恼产生影响,且中介路径存在性别差异。     

Intraindividual variability in driving simulator parameters of healthy drivers of different ages

Intraindividual variability is a fundamental behavioural characteristic of aging but has been examined to a very limited extent in driving. This study investigated intraindividual variability in driving simulator measures in healthy drivers of different ages using the coefficient of variation (COV) as a variability measure. Participants were healthy volunteers who were regular drivers, who were divided into a “young” group, a “middle-aged” group, and an “old” group. They drove in two environments (rural, 72 drivers; urban, 60 drivers), under conditions of moderate and high traffic load, without and with distraction (conversation). Significant differences in COV were observed in the rural condition for headway distance and lateral position as a function of traffic load, with high traffic (without and with distraction) resulting in increased COV of headway and decreased COV of lateral position. Significant differences in COV were observed in the urban condition for headway distance only, with high traffic (without and with distraction) resulting in increased COV of headway. No age effects were found for any of the driving conditions. The results indicate that traffic load affected headway distance and lateral position in opposite directions in all three age groups: high traffic resulted in increased variability of headway in both rural and urban conditions but in decreased variability of lateral position in the rural conditions compared to moderate traffic irrespective of distraction. The study indicates that driving conditions affect the intraindividual variability of driving measures in selective ways, which may be linked to the extent of automatization of the driving variables and to adaptive changes to traffic condition challenges.     

Adaptations in driver deceleration behaviour with automatic incident detection: A naturalistic driving study

Traffic congestion and crash rates can be reduced by introducing variable speed limits (VSLs) and automatic incident detection (AID) systems. Previous findings based on loop detector measurements have revealed that drivers reduce their speeds while approaching traffic congestion when the AID system is active. Notwithstanding these behavioural effects, most microscopic traffic flow models assessing the impact of VSLs do not describe driver response accurately.This study analyses the main factors that influence driver deceleration behaviour while approaching traffic congestion with and without VSLs. The Dutch VSL database was linked to the driver behaviour data collected in the UDRIVE naturalistic driving study. Driver engagement in secondary tasks and glance behaviour were extracted from the video data. Linear mixed-effects models predicting the characteristics of deceleration events were estimated.The results show that the maximum deceleration is high when approaching a slower leader, when driving at high speeds and short distance headways, and close to the beginning of traffic congestion. The minimum time headway is short when driving at high speeds and changing lanes. Certain drivers showed higher decelerations and shorter time headways than others. Controlled for these main factors, smaller maximum decelerations were found when the VSLs were present and visible, and when the gantries were within close proximity. These factors could be incorporated into microscopic traffic simulations to evaluate the impact of AID systems on traffic congestion more realistically. Further research is needed to clarify the link between engagement in secondary tasks, glance behaviour and deceleration behaviour.     

Evaluating pedestrian interaction preferences with a game theoretic autonomous vehicle in virtual reality

Localisation and navigation of autonomous vehicles (AVs) in static environments are now solved problems, but how to control their interactions with other road users in mixed traffic environments, especially with pedestrians, remains an open question. Recent work has begun to apply game theory to model and control AV-pedestrian interactions as they compete for space on the road whilst trying to avoid collisions. But this game theory model has been developed only in unrealistic lab environments. To improve their realism, this study empirically examines pedestrian behaviour during road crossing in the presence of approaching autonomous vehicles in more realistic virtual reality (VR) environments. The autonomous vehicles are controlled using game theory, and this study seeks to find the best parameters for these controls to produce comfortable interactions for the pedestrians. In a first experiment, participants’ trajectories reveal a more cautious crossing behaviour in VR than in previous laboratory experiments. In two further experiments, a gradient descent approach is used to investigate participants’ preference for AV driving style. The results show that the majority of participants were not expecting the AV to stop in some scenarios, and there was no change in their crossing behaviour in two environments and with different car models suggestive of car and last-mile style vehicles. These results provide some initial estimates for game theoretic parameters needed by future AVs in their pedestrian interactions and more generally show how such parameters can be inferred from virtual reality experiments.     

On-road study investigating the mode of feedback delivery on young drivers’ speed management

Feedback has been shown to be instrumental in learning. Refining how it is delivered in driver training has the potential to reduce crash risk. Therefore, the aim of the present study was to examine the effect of the medium in which feedback is delivered (verbal, written, graphical) on young drivers’ speed management behaviour. Sixty young drivers, randomly allocated to one of four feedback groups (i.e., Control, Verbal feedback, Written feedback, and Graphical feedback) completed one training and two test drives using an instrumented vehicle on-road. After the first (baseline) drive, participants were provided feedback about the number of times they exceeded the speed limit, their maximum speed, as well as the financial penalties associated with such driving behaviour, and safety implications. The content of feedback remained the same for all training groups, except for the manner in which the feedback was presented. Verbal feedback was provided verbally by the researcher; written feedback on paper; and graphical feedback using a series of graphs on a computer screen. Control received no such intervention. Two test drives followed, one immediate post-training, and the second one week post-training. Feedback, irrespective of medium improved young drivers’ speed management. Verbal and graphical feedback yielded the greatest reduction in speeding behaviour, with graphical feedback having the most impact in the two speed zones under examination (50 km/h & 80 km/h). Control showed the poorest speed management behaviour in all drives. These findings have important implications for the development of a new approach to improve young drivers’ speed management behaviour.     

Evaluating the effectiveness of Didi ride-hailing security measures: An integration model

Security is one of the most critical factors influencing individuals’ mobility. Ensuring security along ride-hailing trips is also a fundamental challenge to service providers. After two cases of rape and homicide, Didi has rectified measures again to meet passengers’ need for security. However, there are few scientific findings concerning the impact of Didi rectified measures on personal perception of security. This study aims to explore critical latent factors that affect individuals’ intentions to use or reuse ride-hailing after the rectification of security measures. This paper examines individuals’ usage intentions by integrating and expanding both the Technology Acceptance Model (TAM) and the Theory of Planned Behavior (TPB). Research results suggest that perceived security, security risk, and government credibility are correlated with the intentions to use or reuse ride-hailing. Importantly, perceived security and security risk both have a direct impact on behavioral intentions from a different perspective. In contrast, government credibility has an indirect effect. Hence, a mediating effect test is conducted. Government credibility could indirectly influence behavioral intention by affecting trust. Finally, this study verifies that the effectiveness of security measures could be evaluated and improved by studying the influence of latent factors on the intentions to use or reuse ride-hailing.     

Driver conflict response during supervised automation: Do hands on wheel matter?

Securing appropriate driver responses to conflicts is essential in automation that is not perfect (because the driver is needed as a fall-back for system limitations and failures). However, this is recognized as a major challenge in the human factors literature. Moreover, in-depth knowledge is lacking regarding mechanisms affecting the driver response process. The first aim of this study was to investigate how driver conflict response while using highly reliable (but not perfect) supervised automation differ for drivers that (a) crash or avoid a conflict object and (b) report high trust or low trust in automation to avoid the conflict object. The second aim was to understand the influence on the driver conflict response of two specific factors: a hands-on-wheel requirement (with vs. without), and the conflict object type (garbage bag vs. stationary vehicle). Seventy-six participants drove with highly reliable but supervised automation for 30 min on a test track. Thereafter they needed to avoid a static object that was revealed by a lead-vehicle cut-out. The driver conflict response was assessed through the response process: timepoints for driver surprise reaction, hands-on-wheel, driver steering, and driver braking. Crashers generally responded later in all actions of the response process compared to non-crashers. In fact, some crashers collided with the conflict object without even putting their hands on the wheel. Driver conflict response was independent of the hands-on-wheel requirement. High-trust drivers generally responded later than the low-trust drivers or not at all, and only high trust drivers crashed. The larger stationary vehicle triggered an earlier surprise reaction compared to the garbage bag, while hands-on-wheel and steering response were similar for the two conflict object types. To conclude, crashing is associated with a delay in all actions of the response process. In addition, driver conflict response does not change with a hands-on-wheel requirement but changes with trust-level and conflict object type. Simply holding the hands on the wheel is not sufficient to prevent collisions or elicit earlier responses. High trust in automation is associated with late response and crashing, whereas low trust is associated with appropriate driver response. A larger conflict object trigger earlier surprise reactions.     

Sexual activity while driving: A content analysis of media reports

Sexual activity while driving fits the definition of distracted driving because it involves the diversion of attention away from the driving task. However, this risky driving behaviour has received little attention compared to other distracted driving activities. To address the lack of research on sexual activity while driving, the internet was searched from April to June 2020 for media reports in which sexual activities occurred within the cabin of a moving vehicle, taking specific note of: gender, the presence of others, time of day, use of substances, the nature of the circumstances surrounding the incident, and whether crashes had occurred. A total of 106 unique and verified cases were identified from 2004 to 2020. The reports involved 76 male (71.7%) and 30 female drivers (28.3%), and there were 43 (40.5%) serious incidents that involved a crash and 23 fatalities (21.7%). In 17 (16.0%) incidents their vehicle hit another car, and a pedestrian or cyclist was hit in 3 (2.8%) incidents. The risk of a serious incident was higher during oral sex or intercourse than solitary activities (i.e. masturbation). A total of 63 (59.5%) mild incidents (without crashes or fatalities) were identified, in which reports included accounts by witnesses or police regarding sexual activity while driving. Given the potential seriousness of incidents, this topic deserves further research to better understand the prevalence and safety implications of sexual activity while driving.     

Correlations of multiple rider behaviors with self-reported attitudes,perspectives on traffic rule strictness and social desirability

Powered Two-Wheeler (PTW) riders constitute a very vulnerable group of road users, while riding a PTW is considerably more dangerous than using any other motor vehicle. Behavioral issues have been identified major moderating factors to PTW crashes, as riders display great variability in their attitudes towards road safety. Τhe aim of this paper is to present a thorough, overarching structure of relationships correlating various unsafe stated PTW rider behaviors (riding after alcohol consumption, speeding, helmet use and texting) with several self-reported attitude parameters and factors regarding rider perspectives on traffic rule strictness and social desirability. A structural equation model (SEM) was developed using data from the ESRA2 survey, which provided a broad sample encompassing 5,958 respondent riders from 32 countries. Numerous statistical relationships were discovered and quantified correlating the four examined unsafe rider behaviors with eight latent unobserved variables. All covariances between unsafe behaviors were found to be positive and statistically significant, indicating that a rider who will engage more frequently in every single one of the four examined unsafe riding behaviors is more likely to also engage in all the others as well.