Transition to Remote Train Control: Challenges and Best Practices for Collaboration in the Digital Age

The advent of automation has precipitated profound transformations across numerous industries, significantly altering their operational paradigms. It has been claimed that automation in the railway sector is still in its embryonic stage, but it holds the potential to perform crucial tasks (Besinovic et al., 2022). Currently, the escalating imperative for railway organizations to recalibrate and transform their operations has arisen in light of societal pressures (Singh et al., 2021). One possibility to tackle these challenges is the introduction of Automatic Train Operations (ATO). However, the use of ATO in an open-world railway context may encounter challenges. Alternative approaches are being explored, such as Highly Assisted Driving, which includes RTC (Gadmer et al., 2022). While RTC offers solutions to certain issues, it also introduces complexities that necessitate careful consideration. For instance, RTC has been observed to exacerbate the monotony of train driving, leading to detrimental effects on drivers' attention (Anceaux et al., 2019) and it has been found to increase the cognitive workload for various stakeholders (Gadmer et al., 2022). Consequently, it is imperative to assess the specific needs and business requirements associated with the implementation of RTC. The primary objective of this paper is to identify and communicate the consequences associated with the deployment of RTC to decision makers and stakeholders involved. The scope of these consequences encompasses benefits, costs, as well as managerial barriers related to RTC. We assessed previous studies on the effects of RTC on issues such as challenges, staffing requirements, service capacity and reliability. The identified initiatives yielded valuable insights into the obstacles associated with RTC and we provided best practices to address barriers and navigate the changes in the work context for various stakeholders. The scope of the collected studies includes all types of track-based transport. The identified research encompasses cases studies, literature reviews, empirical and conceptual papers. This study is related to the flagship project FP2 R2DATO under the Europe’s Rail Joint Undertaking. The project aims to grasp the opportunity offered by digitalization and automation of rail operations.

RTC generates major impacts in the railway industry, since the dynamics of collaboration among stakeholders is transformed due to team members required to engage in endeavors with a machine agent (Pacaux-Lemoine, Gadmer and Richard, 2020). The remote operator, being separated from the train, lacks the capacity to autonomously gather environmental information and respond to it and in the absence of direct access to the train real time conditions, he/she becomes dependent on an advisory system. This system will gather information, conduct thorough analyses and formulate predictive outputs regarding the driving process, which will serve as inputs for the remote operator actions (Pacaux-Lemoine, Gadmer and Richard, 2020). This creates multiples challenges for railway organizations. It was found that remote operators exhibit delayed signal detection, attributed to the combined effects of system latency and engine response latency, making interpretation challenging (Paglia et al., 2021).

Furthermore, the operator’s ability to cooperate and interact with assistance systems is severely impaired by the fact that their needs and exigencies are rarely assessed (Gadmer et al., 2021). Karvonen et al. (2011) conducted a study to assess the effects of metro automation on train drivers and explored strategies to leverage their expertise in enhancing the automation process. They identified that disregarding the responsibilities and knowledge held by the drivers during the transition towards ATO could yield adverse impacts on service quality and create safety issues. Since it is frequently assumed that former drivers will transition to the role of remote operator, it is critical to comprehend their responsibilities and activities to specify the modifications that must be applied so that RTC can be attained (Gadmer, Pacaux-Lemoine and Richard, 2021). Traditionally, train drivers represent the first layer of operational resilience since they are the first one to perceive, communicate and act upon any irregularity (Brandenburger and Naumann, 2018). Thus, even if RTC holds the potential to augment the resilience of operations by supervising, controlling, and intervening remotely in cases of disruptions, new operational strategies must be developed to truly attain this potential (Gadmer et al., 2022). When introducing RTC, organizations need to define how and when the authority to make decision regarding the control of the train is going to switch from one entity to another. This transitional process is incremental in nature since it will entail deliberations and investigations involving multiple stakeholders (Gadmer et al., 2022). For example, the driver may need to perform physical tasks during unforeseen events, such as an evacuation. In that situation, the duties assigned to the driver includes engaging with traffic control to strategize the optimal approach and communicate it to the passengers (Jansson, Olsson and Fröidh, 2023).

In brief, the introduction of RTC significantly impacts the railway industry. Collaboration dynamics are perturbed as team members engage with automated machine agents. While RTC has the potential to enhance operational resilience, novel strategies must be developed to fully capture this benefit. The transition of decision-making authority requires careful planning and stakeholder involvement. The next section will outline the project management best practices to respond to these challenges and ensure a smooth transition towards RTC.

As illustrated by the implementation of RTC, the integration of new technologies is reshaping the work context of projects, as well as project management processes. The impact of these processes will be predominantly experienced by project team members, thus, project managers and organizational leaders must acknowledge the challenges it entails and take appropriate actions (Manerwick and Manerwick, 2020). Zimmer (2019) contends that digitalization cannot be accomplished through a single comprehensive effort, but rather necessitates the undertaking of diverse digitalization projects across all organizational levels. This means that railway organization must not pursue RTC independently, but create a conducive environment that fosters stakeholder learning, as they will be required to explore new alternatives, reallocate resources, and cultivate new capabilities and routines (Brady and Davies, 2016). When establishing a project teams composed of human and machine agents, Ngereja and Hussein (2021) assert that top management support is crucial, as it necessitates displaying leadership through financial means by investing in training, fostering a collaborative culture, encouraging employees to seek assistance, and supporting mentoring programs for both managers and employees. The formulation of these teams implies that top-down definition of roles of team members must be substitute by an evolutive bottom-up approach that is driven by the team, which entails frequent change management (Manerwick and Manerwick, 2020). Coordination between team members and managers will be essential to enable the coupling of human and machines (Schneider et al., 2021).

To achieve this coordination, throughout the course of the transformation, stakeholders’ exigencies must be prioritized and accentuated. It is thus fundamental that organizations identify internal and external stakeholders that are most affected by their digitalization endeavors, as well as a complete understanding of the impacts on their roles, needs and expectations (Papavasilou and Gorod, 2022). When introducing RTC, stakeholders and more precisely train drivers need to be involved and considered at each phase of the project. Papavasilou and Gorod (2022) suggest consulting them by organizing co-design session and by engaging in beta and pilot testing, as well as obtaining feedback post implementation and to adjust accordingly. These efforts should also be supported with consultation by experts who will analyze stakeholders’ roles and evaluate emerging needs at each stage of the project, while establishing a clear and structured engagement and communication channel between the project team and the managers (Papavasilou and Gorod, 2022). By doing so, railway organizations will align the goals of RTC with the interests and needs of train drivers and other stakeholders. Collecting and analyzing emerging exigencies throughout the progression of the project as the potential to facilitate the adjustment process in response to technological and environmental changes (Romualdo da Costa Filho and Penha Ferreira da Silva, 2021).

This was observed by Karvonen and colleagues (2011) who attested that drivers have unique abilities to react in metro environment. Therefore, when introducing automation, new arrangements have to be made to compensate the lost vantage point of drivers. The arrangements include properly understanding their roles in order to determine how can an automated system fulfill them, especially since these types of systems excel only at handling monotonous tasks, which do not require complex problem-solving skills (Karvonen et al., 2011). On that matter, Jansson, Olsson and Fröidch (2023) found that multiples roles of the drivers are currently not addressed in the conventional grade of automation levels description. They consequently introduce a revised model with six main areas where the driver has a substantial role: Detect, Report, Inspect, Adjust, Manage passengers, and Respond to train orders. By analyzing and understanding each of these areas, railway operators and infrastructure managers can implement the arrangements described by Karvonen et al. (2011) to tackle the challenges associated with deploying ATO and capture the benefits (Jansson, Olsson and Fröidch, 2023). Rio Tinto exemplified this process with their AutoHaul project, which is a driverless heavy haul long distance train operation. A remote team performs activities that were previously drivers’ tasks. They monitor the onboard status of the trains and process all notifications, the objective is to switch from drivers to pilots (Yusuf et al., 2020).

In pursuance of the deployment of automated metro, Denisenkov, Denisenkova and Polyakova (2020) developed a six stages implementation model that optimizes business processes and improves the quality of transportation services by guiding the introduction of digital technologies. The first two stages relate to technical aspects, such as updating the infrastructure. In the third stage, the organization start utilizing advanced technologies, which requires forming implementation strategies, creating support teams, updating documentation and training personnel. The fourth stage focuses on Automated Business Process Management Systems, which involves working groups with relevant internal and external stakeholders. Stage five involves adapting business processes through audit, leading to restructuring and updated documentation. Stage six introduces a unified system for real-time business process management using digital technologies, resulting in improved safety, efficiency, and passenger experience for metro systems (Denisenkov, Denisenkova and Polyakova, 2020). This model is in line with project management literature that suggest that including a broad range of stakeholders into the decision-making processes implies that several business procedures will be transformed and, thus, project managers that will oversee the implementation of RTC will have to rejuvenate their skills to adequately support the new organizational approach (Manerwick and Manerwick, 2021). The implementation of RTC is reshaping project environments and processes in the railway industry, which primarily affects project team members, necessitating proactive actions from organizational leaders, since digitalization requires a multifaceted approach across organizational levels.

RTC impacts various aspects of the railway sector, such as collaborative dynamics, operational resilience, and stakeholder involvement. The adoption of RTC mandates the thorough analysis of collaborative strategies in light of coordination between human and machine agents. While RTC holds the potential to bolster operational resilience, its optimal utility necessitates the formulation of novel project management practices, the change in decision-making processes entails careful planning and the active participation of multiple stakeholders. The engagement of train drivers is cardinal in shaping the implementation process. Recognizing their distinctive competencies and responsibilities is pivotal for transitioning to automation. Successful deployment relies upon an evolved project management paradigm that focuses on bottom-up delineation of roles and continual change management. By resolving these considerations, railway organizations can successfully implement RTC and capitalize on its transformative capacity.