社会与工程心理学研究室知识库

随着民用航空市场的迅猛发展和航线流量的快速增长，空中交通管制员的负荷也日益增长。由于管制员负荷对航空安全和运行效率都有直接影响，所以如何有效减少管制员的工作负荷成为学术界和工业界所共同关注的话题。传统研究主要聚焦于在个体水平上预测和减少管制员的工作负荷，然而，在实际作业中，高负荷管制员可以通过向低负荷管制员请求后援支持，以在团体层面上达到动态优化负荷的目的，但至今少有研究涉足这一领域。什么因素会影响管制员的后援行为，什么方法可以促使管制员提供更加有效的后援？本研究将针对这一问题，结合实际管制过程进行重点研究。

通过分析文献中对非管制员后援行为的研究，结合针对专家管制员的访谈研究，我们提出影响后援行为的一个初步模型：后援被请求方对自己负荷的知觉和对后援请求的合理性评价是两个重要的近端预测因素，而后援被请求者的任务负荷、请求者的任务负荷、待交接飞机的就近降落需求和后援请求所使用的沟通风格将是远端预测因素。为了验证并完善这一模型，我们在空管模拟器（ATC Simulator）上开发了一系列基于平行进近管制的扇区间后援任务，并招募了职业管制员完成相应任务。在此任务中，被试将作为其中一个扇区的管制员，负责指挥自己扇区内飞机；而负责平行扇区的另一名管制员则会在任务进行到某个时刻时，请求将本应由其管理的某架飞机移交给被试，被试将结合当时外界和自身的情况，做出是否接受这架飞机（既提供后援）的判断。

实验1 操纵了三个任务水平变量（被请求者的任务负荷、请求者的任务负荷和待交接飞机的就近降落需求），测量了两个可能的中介变量（被请求者对后援请求合理性的评价和任务中的心理负荷）。多层线性模型 (HLM) 的分析结果显示：（1）三个任务变量（被请求者的任务负荷、请求者的任务负荷和待交接飞机的就近需求）都显著预测了管制员的后援意愿和后援决策；（2）被请求者对后援请求合理性的评价中介了任务变量对后援的影响；（3）管制员当前心理负荷变量没有显著效应，这可能是因为，在后援决策中扮演重要角色的不是管制员当前的心理负荷，而是其对未来心理负荷的预期。因此，实验2 增加了对预期心理负荷的测量。HLM 结果首先验证了三个任务变量对管制员后援意愿和后援决策的显著预测效应，和被请求者对后援请求合理性评价的中介效应；更重要的是，被请求者对未来心理负荷的预期显著预测了后援意愿和后援决策，并且中介了任务水平变量对后援的影响。在实验3 中，我们操纵了请求者任务负荷和待交接飞机就近需求这两个任务水平变量（被请求者的任务负荷恒为中等），和表达紧迫和解释就近需求这两个通讯风格变量。结果显示，请求者任务负荷和是否表达紧迫的通讯风格的交互作用显著，待交接飞机的就近需求和是否解释就近需求的通讯风格的交互作用显著。当通讯风格真实匹配任务情况的时候，被请求者对后援请求做出了最积极的反馈。由于现有数据表明存在大量未获解释的个体差异变异，因此实验4 通过合并实验1 和实验2 的数据，探讨如何得到有效解释这些个体间变异。

总体来说，本研究首先为管制员心理负荷管理提供了新的研究视角，其次，本研究初步揭示了影响管制员提供后援行为的核心心理因素；最后，本研究为如何更好地提升管制员的后援行为提供了新的观点。

With the rapid increase of the air traffic, the task load of air traffic controllers is reaching a new high. Since controllers’ mental workload is linked with both safety and efficiency of aviation, both researchers and practitioners are seeking novel methods to prevent overload. While most previous studies adopted an individual focused approach, controllers’ workload can also be effectively managed by redistributing individual task-load at a group level, yet this area has not been fully explored. In this study we focused on the backup behaviors between two parallel final approach sectors, which is a typical and important form of ATC cooperation. This research intended to understand the factors that can promote the cross-backup behaviors.

Based on previous studies on general backup behaviors and experts interviews with professional controllers in our pilot study, we proposed a preliminary model of air controllers’ cross-sector backup decision: both backup providers’ workload and perceived legitimacy of backup requests worked as proximal predictors, while backup requesters’ task-load, backup providers’ task-load, the close-landing demands of the to-be-hand-over aircraft, and the communication style of backup requesters worked as distal predictors. To validate this model, three further studies were conducted. We invited licensed controllers to perform simulated final approach scenarios on a medium-fidelity ATC simulation platform. They had to decide whether to accept a hand-over request made by a controller working in the neighboring sector.

In study 1, three task-level distal factors (participants’ task load, requesters’ task load, and the close-landing demands of the to-be-hand-over aircraft) were manipulated and two proximal factors (participants’ workload and evaluations of the legitimacy of backup requests) were measured. HLM analysis firstly showed that task-level variables all significantly predicted backup decisions. Controllers were more willing to accept the request when they were under low pressure, when their colleagues were at higher pressure and when the aircraft had a close-landing demand. As for two proximal factors, participants’ perceived legitimacy of requests mediated the relationships between task-level variables and backup decisions. However, participants’ perceived workload did not mediate the impact of task variables on backup outcomes as expected. We proposed that it was controllers’ anticipations of future workload, not controllers’ perceptions of immediate workload, that played a key role. In study 2, participants’ anticipated workload were measured in addition to the other two proximal factors. HLM analyses suggested that the both perceived legitimacy and anticipated workload were mediators between task-level variables and backup decisions. In study 3, with participants’ own task-load being controlled at a constant level, two task-level features (requestors’ task-load and the close-landing demands of the to-be-hand-over aircraft) and backup requestors’ communication styles (expressions of anxiety and explanations of the close-landing demands) were manipulated. Study 3-A found a significant interaction between requesters’ task-load and anxiety expression, suggesting backup behaviors were more likely to be offered if the requester expressed the urgency when his/her task-load was really high. Study 3-B found a significant interaction between close-landing demands and purpose explanation, suggesting backup behaviors were more likely to be offered when a real close-landing demand of the to-be-hand-over aircraft is being explained. The results suggested that participants gave the most positive feedbacks when the communication styles authentically matched task-level features. In study 4, we combined the data from study 1 and study 2 to understand the large portion of between-individual variations that has been effectively explained. HLM results showed that, after controlling for the effects of task-level variables and job experience, job satisfaction turned out to have a unique positive effect on backup behaviors and also interacted with task-level variables (participants’ task-load and requesters’ task-load) in predicting backing up behaviors.

In summary, this research adopted a new approach to understand the workload management of air traffic controllers and identified key psychological factors that can influence controllers’ cross-sector backup behaviors for the first time.