## 2 Theoretical Background, Related Work, and Hypotheses  
### Foundations of Automation Trust in ATS Systems  
Trust is a fundamental concept across numerous domains, including social psychology, where the study of interpersonal trust provides valuable insights for defining automation trust [15]. Empirical research has revealed significant similarities between automation trust and interpersonal trust [16]. For instance, human reactions to technology often mirror reactions to other humans [17], and the dynamics of trust in complex environments show strong parallels between interpersonal and automation contexts [18]. Several studies have identified the core features of automation trust within human-automation partnerships [19; 20; 21]. First, trust requires a delegator (e.g., the operator) to grant trust, a trustee (e.g., the automation system) to receive trust, and a task with potential risks [22]. Second, the trustee must be motivated to perform the task, typically driven by the designer's intended use of the system. Finally, the possibility of task failure introduces uncertainty and risk. In this study, we adopt the widely accepted definition of automation trust by [PERSON] and [PERSON] as follows: \"the attitude that an agent will help achieve individual goals in situations characterized by uncertainty and vulnerability\" [23]. Empirical research further highlights that trust in automation is influenced by the following three main dimensions: the automation system, the operator, and the environment [24]. The human-machine interface serves as the critical link between operators and automation systems. Transparency, a key aspect of interface design, determines the operator's ability to comprehend, perceive, and anticipate the automation system's behavior [25]. Higher transparency enables operators to maintain better performance and trust, especially when the automation system encounters abnormalities [26]. Empirical studies in human-machine collaboration have consistently shown that interface transparency directly influences operators' trust in automation agents [27]. In the context of automated decision making, providing transparency about the logic behind system recommendations has been found to improve the accuracy of automation use without increasing decision time or subjective workload [28]. However, excessive transparency, such as detailed visualizations of decision outcomes, may lead to faster but less accurate decisions [29]. For ATS systems, interface transparency reflects the extent to which dispatchers can review historical records, understand current system status, and predict future trends [30; 31; 32]. As the primary tool for decision making and information access, the perceived transparency of the ATS system over time is likely to shape dispatchers' trust in automation, forming the basis of Hypothesis 1 in this study. Automation trust is inherently human-centered, with operator factors playing a pivotal role in its formation [33]. Research has consistently shown that operators' familiarity with the capabilities and limitations of their systems significantly influences their trust levels [34; 35; 36]. This finding has been replicated in safety-critical domains, such as spacecraft rendezvous and docking missions [37]. Dispatchers, whose roles demand high operational skills, system knowledge, and experience [38], are particularly affected by their understanding of automation systems. For example, a study using observational methods found that railway signalers' trust in automation was heavily influenced by their comprehension of the system [39]. In summary, a holistic understanding of the ATS system is essential for building trust in it (Hypothesis 2a of this study). Additionally, a transparent interface serves as a crucial bridge between dispatchers' system knowledge and the current system status (Hypothesis 2b of this study). In safety-critical fields such as subway dispatching, environmental risks are mitigated primarily through system safety redundancies [40].