基于管理者安全管理行动的高风险企业安全氛围改善

随着系统可靠性的提高,高风险企业超过三分之二的事故原因涉及人的因素。员工不安全行为是系统失效的触发因素,潜藏的社会情境因素(如安全氛围)是“常驻的病原体”,因此探索并改善影响安全行为的社会情境因素是有效提升组织安全的关键。在众多的情境因素中,安全氛围对安全绩效的积极影响已得到充分的文献支持,但对如何改善安全氛围的探索却有限。本项目围绕管理者对安全的承诺这一安全氛围的核心维度,基于信号理论提出直接安全管理行动是体现管理者安全承诺的重要途径,并在探索主管和经理关键安全管理行动对团队和组织安全氛围影响的基础上开展相应的干预研究。具体而言,在团队层面,探索改善主管关键安全管理行动对团队安全氛围提升的有效性;在组织和团队两个层面,探索改善经理的关键安全管理行动对同时提升组织和团队安全氛围的有效性。研究结果预期可以在安全管理实践中推广应用。     

School Counselors' Experiences With Lockdown Drills: A Phenomenological Investigation

Lockdown drills are used in pre-K–12 public schools throughout the country; however, little research exists regarding their impact on students and school staff (Ilk, 2018). Because of school counselors' role in both prevention of and response to school gun violence (American Counseling Association, 2018), we used a phenomenological approach to investigate their experiences with lockdown drills (N = 26). Results included the following three themes: (a) school counselors' sense of duty to follow school protocol, (b) unintended emotional consequences related to lockdown drills, and (c) school counselors navigating complexities. Implications for school counselors and corresponding school procedures are discussed.     

Pedestrians’ road crossing behaviour in front of automated vehicles: Results from a pedestrian simulation experiment using agent-based modelling

The objective of this research is to explore the relation between personal characteristics of pedestrians and their crossing behaviour in front of an automated vehicle (AV). For this purpose, a simulation experiment was developed using Agent-Based Modelling (ABM) techniques. Sixty participants were asked to cross the road in a virtual environment displayed on a computer screen, allowing to record their crossing behaviour when in the presence of AVs and conventional vehicles (CVs). In some experimental configurations, the AVs communicated their intention to continue or not to continue their trajectories through the use of lights. The ABM allowed controlling the behaviour of the vehicles when interacting with the simulated avatar of the respondents. The subjects of the experiment were also asked to fill in a questionnaire about usual behaviour in traffic, as well as attitudes and risk perceptions toward crossing roads. The questionnaire data were used to estimate individual specific behavioural latent variables by means of principal component analysis which resulted in three main factors named: violations, lapses, and trust in AVs. The results of generalized linear mixed models applied to the data showed that besides the distance from the approaching vehicle and existence of a zebra crossing, pedestrians’ crossing decisions are significantly affected by the participants’ age, familiarity with AVs, the communication between the AV and the pedestrian, and whether the approaching vehicle is an AV. Moreover, the introduction of the latent factors as explanatory variables into the regression models indicated that individual specific characteristics like willingness to take risks and violate traffic rules, and trust in AVs can have additional explanatory power in the crossing decisions.     

The influence of alcohol (0.5‰) on the control and manoeuvring level of driving behaviour,finding measures to assess driving impairment: A simulator study

ObjectiveThe influence of psychoactive substances on driving performance and traffic safety has been extensively studied. Research on the influence of alcohol at the control level of behaviour (i.e. automated processes) has been well established and has shown that the ability to operate a vehicle decreases with rising alcohol levels. However, results one level higher at the manoeuvring level (i.e. conscious processes), are inconsistent. The current study aimed to replicate findings on the influence of alcohol on the control level of behaviour and investigate effects on the manoeuvring level in order to find suitable measures to assess driving impairment.MethodThe study was double-blind, placebo-controlled with a counterbalanced treatment order and a two-way crossover design. Thirty participants performed tasks in a driving simulator under the influence of alcohol (0.5‰) and a placebo. In the driving tasks the control level of behaviour (swerving, average speed, and speed variation) was investigated, as well as the manoeuvring level of behaviour (distance to other traffic during an overtaking manoeuvre, reaction time to a traffic light turning amber, and response to a suddenly merging car).ResultsAs expected, alcohol affected the control level of behaviour negatively. Participants swerved more and showed more speed variation after alcohol intake. The manoeuvring level of driving behaviour was also affected by alcohol. The distance to other drivers during an overtaking manoeuvre was smaller under the influence of alcohol. Results on reaction time were however less straightforward. Reaction time increased significantly under the influence of alcohol when reacting to a traffic light but not in reaction to a car unexpectedly merging into traffic. When analysing behaviour in reaction to these different events in more detail it became clear that they were responded to in varying manners, making it difficult to find an average impairment measure.ConclusionsThe deteriorating effect of alcohol at the control level of driving behaviour was replicated, confirming the suitability of the standard deviation of lateral position and the variation in speed as measures of impairment. At the manoeuvring level, the kept distance to the leading car during an overtaking manoeuvre appeared to be a suitable measure to assess impairment as well as reaction time to a traffic light. The current study also confirms the difficulties in evaluating complex driving behaviour and the need for more research on this subject.     

Predictors of perceived road collision/incident risk among horse users: A survey study from Norway

Although horse users in traffic are a vulnerable road user group, traffic safety problems among them are scantly examined by previous research. The main aim of the present study was to examine the role of some demographic variables, traffic safety attitudes, and level of knowledge about rules and regulations applying to horse use in traffic for predicting perceived road collision/incident risk in a sample of horse users in Norway. An online survey was conducted to collect data from a total of 1733 horse users including horse riders and drivers of horse-drawn sulky, wagon or sled. The respondents accessed the survey via a link put to the website of the Norwegian Horse Centre, which is in contact with many different horse user environments in Norway. The majority of the respondents were female and between the ages of 18–30. A multiple regression analysis was conducted to examine the predictors of the perceived collision/incident risk involving other motor vehicles. Results showed that traffic safety attitudes among horse users were the strongest predictor of the perceived collision/incident risk. In particular, horse users reported a negative attitude towards the other road users (e.g. drivers) indicating that they perceive the other road users’ actions and approaches as the biggest source of risk in road traffic. The level of knowledge about the rules and regulations applying to horse use, especially in walking and cycling lane, was relatively low among the respondents. However, knowledge about rules and regulations did not appear as a strong predictor of the perceived collision/incident risk. Results indicate the need to increase road users, especially drivers’, awareness about the problems and needs of horse users in traffic.     

A diary study of distracted driving behaviours

The introduction and uptake of technology within road vehicles has readily advanced the capabilities and the functions that the driver of a road vehicle has available to them. While this has benefited the drivers’ productivity and entertainment behind the wheel, it has also heightened the possibility for distraction. Research into driver distraction to date has identified how technologies inside the vehicle may be used ineffectively and can compromise the safety of the road transport system. Yet, the factors that drivers state impact on their decision to engage with distracting technologies are less well known. This paper presents the first diary study into driver distraction. The study asked drivers to record all technological distractions that they engaged with across a 4-week period, as well as interactions that they ignored or choose not to engage with. The diary entries include the technologies drivers interacted with and the conditions surrounding this, as well as external factors that drivers cited to influence their decision to interact. Primarily, factors relating to the task itself were found to be of most importance to the drivers’ decision to engage. Differences were also found in how drivers stated they compensated for any engagement with distracting tasks. This has important consequences for the design and integration of technological devices into the vehicle. The novel application of the method offers insights into the naturalistic conditions surrounding drivers’ involvement with distracting technologies. The method is also reviewed on its applicability to the study of driver distraction.     

The perception of bicycle crashes with and without motor vehicles: Which crash types do older and middle-aged cyclists fear most?

Several studies have focused on the perceived risk of bicycle crashes (irrespective of crash types) and concluded that cycling near high volumes of motor vehicles deters people from cycling. The perceived risk of bicycle crash types (with or without motor vehicles) has not yet been studied. Cyclists, both in countries with low and high levels of cycling participation, are substantially more likely to sustain severe injuries in single-bicycle crashes than in bicycle-motor vehicle crashes. This questionnaire study sets out to compare which bicycle crash types are perceived to cause most hospitalizations among cyclists. The study comprised cyclists over 55 years in the Netherlands, and over 40 years in the Belgian regions of Flanders (a region with high cycling participation), Brussels and Wallonia (regions with low cycling participation). The majority of cyclists (60%) perceive bicycle-motor vehicle crashes cause most hospitalizations among cyclists. This percentage is greatest in the areas of Brussels and Wallonia and lowest in the Netherlands. Cyclists who were involved in a bicycle-motor vehicle crash themselves are more likely to regard this crash type as the most common cause of hospitalizations among cyclists, while cyclists over 60 years who were involved in a crash without a motor vehicle are more likely to perceive that crash type as the most common cause. The smaller perception bias in the study areas with higher cycling participation – particularly the Netherlands and to a somewhat lesser degree Flanders – is probably due to bicycle infrastructure being more separated from high-speed motor traffic, leaving cyclists less exposed. The outcomes show that cyclists underestimate the likelihood of severe injuries due to single-bicycle crashes. New interventions should raise the awareness of the risk of single-bicycle crashes and provide solutions to avoid such crashes.     

Pedestrian detection using a moving camera: A novel framework for foreground detection

While background subtraction techniques have been widely applied to detect moving objects in a video stream captured by a static camera, detecting moving objects using a moving camera still represents a challenging task. In this context, pedestrian detection using a camera placed on the top of a vehicle’s windshield has been rarely investigated. This is mainly due to the background ego-motion. Since the scene captured by the camera seems in motion, it is very difficult to distinguish the moving pedestrians from the others that belong to the static part of the scene. For this reason, a compensation step is needed to suppress the ego-motion. This paper presents a study on the main challenges facing pedestrian detection systems as well as methods proposed to handle these challenges. A novel trajectory classification framework for detecting pedestrians even in challenging real-world environments is proposed. The proposed method models the background motion between two consecutive frames in order to compensate the camera motion. Then, it defines a classification process that differentiates between the background and the foreground in the frame. Using the defined foreground, we consequently identify the presence of pedestrians in the scene. The proposed method was validated on a public benchmark dataset: CVC-14 containing both visible and far infrared video sequences in day and night times. Experimental results confirm the effectiveness of the proposed approach in capturing the dynamic aspect between frames and therefore detecting the presence of pedestrians in the scene.     

Differences in cycling performance of Dutch and non-Dutch students in the Netherlands

Thirty-seven young adult participants completed a bicycle ride through the city of Groningen. Behaviour of Dutch and non-Dutch cyclists was compared in three conditions: on a control track (i.e. a one-way bicycle path), on a complex intersection, and on a roundabout. Basic bicycle control of the two groups did not differ, neither did reported invested mental effort. However, non-Dutch participants made more serious errors in the experiment and reported to have had more crashes previous to the experiment. It is concluded that the performance of non-Dutch cyclists who continue cycling upon arrival in a new country, does not differ on the control level, but at the higher manoeuvre level more performance errors were observed in the non-Dutch group.