Investigating cycling kinematics and braking maneuvers in the real world: e-bikes make cyclists move faster,brake harder,and experience new conflicts

Pedelecs (e-bikes), which facilitate higher speeds with less effort in comparison to traditional bicycles (t-bikes), have grown considerably in popularity in recent years. Despite the large expansion of this new transportation mode, little is known about the behavior of e-cyclists, or whether cycling an e-bike increases crash risk and the likelihood of conflicts with other road users, compared to cycling on t-bikes. In order to support the design of safety measures and to maximize the benefits of e-bike use, it is critical to investigate the real-world behavior of riders as a result of switching from t-bikes to e-bikes.Naturalistic studies provide an unequaled method for investigating rider cycling behavior and bicycle kinematics in the real world in which the cyclist regularly experiences traffic conflicts and may need to perform avoidance maneuvers, such as hard braking, to avoid crashing. In this paper we investigate cycling kinematics and braking events from naturalistic data to determine the extent to which cyclist behavior changes as a result of transferring from t-bikes to e-bikes, and whether such change influences cycling safety.Data from the BikeSAFE and E-bikeSAFE naturalistic studies were used in this investigation to evaluate possible changes in the behavior of six cyclists riding t-bikes in the first study and e-bikes in the second one. Individual cyclists’ kinematics were compared between bicycle types. In addition, a total of 5092 braking events were automatically extracted after identification of dynamic triggers. The 286 harshest braking events (136 cases for t-bike and 150 for e-bike) were then validated and coded via video inspection.Results revealed that each of the cyclists rode faster on the e-bike than on the t-bike, increasing his/her average speed by 2.9–5.0 km/h. Riding an e-bike also increased the probability to unexpectedly have to brake hard (odds ratio = 1.72). In addition, the risk of confronting abrupt braking and sharp deceleration were higher when riding an e-bike than when riding a t-bike.Our findings provide evidence that cyclists’ behavior and the way cyclists interact with other road users change when cyclists switch from t-bikes to e-bikes. Because of the higher velocity, when on e-bikes, cyclists appear to have harder time predicting movements within the traffic environment and, as a result, they need to brake abruptly more often to avoid collisions, compared with cycling on t-bikes. This study provides new insights into the potential impact on safety that a cycling society moving to e-bikes may have, indicating that e-cycling requires more reactive maneuvers than does cycling traditional bicycles and suggesting that any distractive activity may be more critical when riding e-bikes compared to traditional bikes.     

Investigating the effectiveness of perceptual treatments on a crest vertical curve: A driving simulator study

Rural roads are characterized by a high percentage of run-off-the-road accidents and head-on collisions, mainly caused by inappropriate speeds and failure to maintain a proper lateral position along the roadway alignment. Among several road safety treatments, low-cost perceptual measures are considered an effective tool, as they generally increase the risk perceived by drivers, or even alter the drivers’ speed perception, and consequently tempting them to decrease their speeds. Their effectiveness has been widely recognized in a number of studies, especially with respect to road intersections and curves.The overall aim of this study is to investigate the effects of different perceptual treatments on driving speed, along a crest vertical curve of an existing two-lane rural road, in order to identify the most effective measure to reduce speed and define its subsequent implementation in the field. Three perceptual treatments were tested using a driving simulator: white peripheral transverse bars, red peripheral transverse bars and optical speed bars, with each one being painted along the approaching tangent to the crest vertical curve. The effects of these speed-reducing measures were investigated using a sample of forty-four participants, by comparing the driving speeds with those recorded under a baseline condition (without a treatment); these were also used to validate the driving simulator’s speed measurements with those found in the field. Moreover, subjective measures were collected, consisting of the driver’s static evaluation of the desired speed, risk perception and markings comprehension, based on screen shot pictures that represented the simulated configurations of the treatments.The findings demonstrated an overall effectiveness of the perceptual treatments, although only the red peripheral transverse bars were found to significantly reduce the driving speeds (−6 km/h). The analysis of the questionnaire yielded interesting information and demonstrated the importance of performing driving simulation tests for evaluating the effectiveness of perceptual treatments.Finally, the results confirmed the enormous potential of using driving simulators to pinpoint a number of speed-reducing measures, and consequently select the most effective one that reduces cost and promotes safety before its actual implementation in the field.     

Effective coordination in medical emergency teams: The moderating role of task type

Coordination in health care action teams is an important factor in clinical performance and patient safety. Implementing a high-fidelity in situ simulation study, we investigated the performance-relevant effects of task distribution, provide information without request (PIWR) and closed-loop communication (CLC) in 68 medical emergency teams (METs) composed of fully qualified clinicians. We differentiated between two task types: algorithm-driven and knowledge-driven tasks. We assigned two different emergency tasks to each task type. We proposed not only a direct relationship between the three coordination behaviours and clinical performance, but also a moderating role for the type of task. Only CLC was related to performance and also moderated by task type. There was no relationship between the coordination behaviours task distribution and PIWR and performance. We discuss the differential effects of the three coordination behaviours on performance and emphasize the importance of the task in team research. In particular, we highlight theoretical and practical implications.     

Testing extrinsic and intrinsic motivation as explanatory variables for the safety climate–safety performance relationship among long-haul truck drivers

The paper tests the proposition that the organizational climate-behavior relationship is based primarily on extrinsic motivation induced by climate perceptions. Using safety climate as exemplar, the effect of climate-induced extrinsic motivation was compared with that of engagement-induced intrinsic motivation on safety behavior and subsequent injury outcomes. Using a sample of long-haul truck drivers representing lone employees, (individual-level) safety climate perceptions and employee engagement predicted safety behavior, which mediated their effect on subsequently measured road injury outcomes. Consistent with meta-analytic evidence suggesting a non-symmetric compensatory relationship between extrinsic and intrinsic motivation, high safety climate undermined the effect of engagement on safety behavior with the reverse being true under low safety climate. This resulted in a moderation effect of engagement on the strength of relationship between climate perceptions and safety behavior. Theoretical and practical implications for climate, engagement, and lone work research are discussed.     

The estimation of vehicle speed and stopping distance by pedestrians crossing streets in a naturalistic traffic environment

The ability to estimate vehicle speed and stopping distance accurately is important for pedestrians to make safe road crossing decisions. In this study, a field experiment in a naturalistic traffic environment was conducted to measure pedestrians’ estimation of vehicle speed and stopping distance when they are crossing streets. Forty-four participants (18–45 years old) reported their estimation on 1043 vehicles, and the corresponding actual vehicle speed and stopping distance were recorded. In the speed estimation task, pedestrians’ performances change in different actual speed levels and different weather conditions. In sunny conditions, pedestrians tended to underestimate actual vehicle speeds that were higher than 40 km/h but were able to accurately estimate speeds that were lower than 40 km/h. In rainy conditions, pedestrians tended to underestimate actual vehicle speeds that were higher than 45 km/h but were able to accurately estimate speeds ranging from 35 km/h to 45 km/h. In stopping distance estimation task, the accurate estimation interval ranged from 60 km/h to 65 km/h, and pedestrians generally underestimated the stopping distance when vehicles were travelling over 65 km/h. The results show that pedestrians have accurate estimation intervals that vary by weather conditions. When the speed of the oncoming vehicle exceeded the upper bound of the accurate interval, pedestrians were more likely to underestimate the vehicle speed, increasing their risk of incorrectly deciding to cross when it is not safe to do so.     

Safety–critical events in everyday cycling – Interviews with bicyclists and video annotation of safety–critical events in a naturalistic cycling study

Research in cycling safety seeks to better understand bicycle-related crashes and injuries. The present naturalistic cycling study contributes to this research by collecting data about bicyclists’ behavior and impressions of safety–critical situations, information unavailable in traditional data sources (e.g., accident databases, observational studies). Naturalistic data were collected from 16 bicyclists (8 female; M = 39.1 years, SD = 11.4 years) who rode instrumented bicycles for two weeks. Bicyclists were instructed to report all episodes in which they felt uncomfortable while riding (subjective risk perception), even if they didn’t fall. After data collection, the bicyclists were interviewed in detail regarding their self-reported safety–critical events. Environmental conditions were also recorded via video (e.g., road surface, weather). In total, 63 safety–critical events (56 non-crashes, 7 crashes) were reported by the bicyclists, mainly due to interactions with other road users – but also due to poorly maintained infrastructure. In low-visibility conditions, vehicle-bicycle and bicycle-bicycle events were the most uncomfortable for the bicyclists. Self-reported pedestrian–bicycle events primarily consisted of pedestrians starting to cross the bicycle path without looking. With one exception, all crashes found in the study belonged to poorly maintained road and infrastructure. In particular, construction work or obstacles in the bicycle path were reported as uncomfortable and annoying by the bicyclists. This study shows how naturalistic data and bicyclists’ interviews together can provide a more informative picture of safety–critical situations experienced by the bicyclist than traditional data sources can.     

患者和家属参与患者安全的概念演变及临床意义

运用Rodgers演化概念分析法对患者和家属参与患者安全概念的演化、替代术语和相关术语、前因变量、结果、概念属性、定义、典型案例进行分析。概念属性包含过程、行为及环境3个领域,4个重要特征分别为个性化、获取、投入及治疗联盟,其前因变量为患者的疾病、健康信息或护理协调的混乱、新政策号召的尝试。结果包括保障患者安全、减少医疗费用和确定最佳做法。澄清患者和家属参与患者安全的概念有助于提高医护人员对其的重视与了解,为临床的实践和研究提供参考和理论依据。

     

Safer driver responses at intersections with green signal countdown timers

Traffic signal countdown timers (TSCTs) are innovative, practical, and cost effective technologies with the potential to improve safety at signalized intersections. The purpose of these devices is to assist motorists in decision-making at signalized intersections by providing them with real-time signal duration information. This study examines US driver responses in the presence of a green signal countdown timer (GSCT) and the implications those responses have on intersection safety. A driving simulator study was conducted to record driver responses to virtual GSCTs. Fifty-five participants (32 male and 23 female) responded to 1100 simulated traffic signals, half of which had GSCTs. A predictive model was developed and validated to estimate the change in driver’s probability to stop at different distances from the stop line in the presence of a GSCT. The presence of a GSCT increased average driver stopping probability in the dilemma zone by 13.10%, while decreasing average driver deceleration rates by 1.50 ft/s². These results suggest that GSCTs may contribute to improved intersection safety in the US.     

团队决策及其影响因素

随着组织结构的变化,团队决策为越来越多的组织所采用。该文将团队决策的研究范式概括为以下四类：社会决策图式（social decision scheme, SDS）、信息取样模型（information sampling model）、项目排序任务（ranking item task）团队以及组织中以安全优先的团队（safety priority team）;并从影响团队决策的因素,提高团队决策质量的策略等角度分别对四类团队决策的研究进行探讨,在此基础上本文对未来研究进行了展望     

道德领导与员工建言：一个调节-中介模型的构建与检验

近年来, 研究者就如何激发员工公开讲出自己的观点、意见和问题进行了大量的探索。其中, 道德领导对员工建言的效应受到了越来越多研究的关注。在以往研究的基础上, 本研究构建了一个调节-中介模型以探讨道德领导影响员工建言的中介心理机制及其边界条件。根据社会交换理论和社会信息加工理论, 本文分别提出两种不同的中介变量-- 责任知觉和心理安全感-- 来解释道德领导与员工建言之间的关系。在此基础上, 本研究进一步假设权力距离会正向调节变量之间的间接关系。通过对某一零售企业239名员工的两阶段调查, 我们对以上研究假设进行了检验, 结果总体上支持了本研究的理论预期。本研究的发现有利于我们了解道德领导影响建言行为的心理机制, 指导管理者采取有针对性的措施, 以期有效地管理企业中的员工建言行为。