How do principles for human-centred automation apply to Disruption Management Decision Support?

While automation of signal and route setting is routine, the use of automation or decision support in disruption management processes is far less common. Such support offers significant advantages in optimising re-planning of both timetable and resources (crew and rolling stock), and has value in offering a 'shared view' of re-planning across the many actors manage disruption. If this vision is to be realised, however, disruption management decision support and automation must adhere to proven principles for effective human-agent cooperation. This paper synthesises data from a programme of work to understand user requirements for automated disruption support tools. It then compares these outputs with two frameworks for human-centred automation - one general (Klein et al's [2004] ten challenges for automation) and one transport specific (Balfe et al’s [2012] principles for transport automation). Emergent design requirements include the need for iterative modification of rescheduling parameters throughout a disruption, visibility of the reasoning behind options, accountability remaining in the hands of disruption controllers, and the need for the automated disruption support tools to take a multi-dimensional view of disruption that varies depending on the event encountered. The paper reflects on the practical utility of high-level design principles for automated disruption support tools

How do principles for human-centred automation apply to Disruption Management Decision Support?

While automation of signal and route setting is routine, the use of automation or decision support in disruption management processes is far less common. Such support offers significant advantages in optimising re-planning of both timetable and resources (crew and rolling stock), and has value in offering a 'shared view' of re-planning across the many actors manage disruption. If this vision is to be realised, however, disruption management decision support and automation must adhere to proven principles for effective human-agent cooperation. This paper synthesises data from a programme of work to understand user requirements for automated disruption support tools. It then compares these outputs with two frameworks for human-centred automation - one general (Klein et al's [2004] ten challenges for automation) and one transport specific (Balfe et al’s [2012] principles for transport automation). Emergent design requirements include the need for iterative modification of rescheduling parameters throughout a disruption, visibility of the reasoning behind options, accountability remaining in the hands of disruption controllers, and the need for the automated disruption support tools to take a multi-dimensional view of disruption that varies depending on the event encountered. The paper reflects on the practical utility of high-level design principles for automated disruption support tools

How do principles for human-centred automation apply to Disruption Management Decision Support?

While automation of signal and route setting is routine, the use of automation or decision support in disruption management processes is far less common. Such support offers significant advantages in optimising re-planning of both timetable and resources (crew and rolling stock), and has value in offering a 'shared view' of re-planning across the many actors manage disruption. If this vision is to be realised, however, disruption management decision support and automation must adhere to proven principles for effective human-agent cooperation. This paper synthesises data from a programme of work to understand user requirements for automated disruption support tools. It then compares these outputs with two frameworks for human-centred automation - one general (Klein et al's [2004] ten challenges for automation) and one transport specific (Balfe et al’s [2012] principles for transport automation). Emergent design requirements include the need for iterative modification of rescheduling parameters throughout a disruption, visibility of the reasoning behind options, accountability remaining in the hands of disruption controllers, and the need for the automated disruption support tools to take a multi-dimensional view of disruption that varies depending on the event encountered. The paper reflects on the practical utility of high-level design principles for automated disruption support tools

An empirical study of the variability in the composition of British freight trains

As part of the broader sustainability and economic efficiency agenda, European transport policy places considerable emphasis on improving rail’s competitiveness to increase its share of the freight market. Much attention is devoted to infrastructure characteristics which determine the number of freight trains which can operate and influence the operating characteristics of these trains. However, little attention has been devoted to the composition of the freight trains themselves, with scant published data relating to the practicalities of this important component of system utilisation and its impacts on rail freight viability and sustainability. This paper develops a better understanding of the extent to which freight train composition varies, through a large-scale empirical study of the composition of British freight trains. The investigation is based on a survey of almost 3,000 individual freight trains, with analysis at four levels of disaggregation, from the commodity groupings used in official statistics down to individual services. This provides considerable insight into rail freight operations with particular relevance to the efficiency of utilisation of trains using the available network paths. The results demonstrate the limitations of generalising about freight train formations since, within certain commodity groupings, considerable variability was identified even at fairly high levels of disaggregation

Analysis of a Train-operating Company’s Customer Service System during Disruptions:Conceptual Requirements for Gamifying Frontline Staff Development

This paper provides an account of an action research study into the systemic success factors which help frontline staff react to and recover from a rail service disruption. This study focuses on the effective use of information during a disruption to improve customer service, as this is a priority area for train-operating companies (TOCs) in Great Britain. A novel type of systems thinking, known as Process-Oriented Holonic Modelling (PrOH), has been used to investigate and model the ‘Passenger Information During Disruption’ (PIDD) system. This paper presents conceptual requirements for a gamified learning environment; it describes ‘what’; ‘how’ and ‘when’ these systemic success factors could be gamified using a popular disruption management reference framework known as the Mitigate, Prepare, React and Recover (MPRR) framework. This paper will interest managers of and researchers into customer service system disruptions, as well as those wishing to develop new gamified learning environments to improve customer service systems

Implementation of a graphical prototype for a train driver advisory system

In the past decade, Driver Advisory System (DAS) has become to a very emerging topic. There are several Driver Advisory Systems existing in the market. Those systems’ goals are to increase punctuality and decrease energy consumption by implementing several algorithms. A study – “Solutions to the Problem of Inconsistent Plans in Railway Traffic Operation” which is conducted by Division of Visual Information and Interaction Department of Information Technology, Uppsala University. In this study, there is a part called train Driver Advisory System mainly focuses on human factors/usability. A project implemented a graphical prototype of a train driver advisory system for evaluation purposes. The difference between this DAS system with other DAS systems is to achieve human factors/usability better and support train drivers better. In this thesis report, important theoretical aspects about human-machine interface design related with the train DAS graphic user-interface (GUI) design and the development methodology used in this project were described. All components of this train Driver Advisory System were described and requirements were analysed. The train DAS development process was described, especially the system architecture and how the system was implemented

Implementation of a graphical prototype for a train driver advisory system

In the past decade, Driver Advisory System (DAS) has become to a very emerging topic. There are several Driver Advisory Systems existing in the market. Those systems’ goals are to increase punctuality and decrease energy consumption by implementing several algorithms. A study – “Solutions to the Problem of Inconsistent Plans in Railway Traffic Operation” which is conducted by Division of Visual Information and Interaction Department of Information Technology, Uppsala University. In this study, there is a part called train Driver Advisory System mainly focuses on human factors/usability. A project implemented a graphical prototype of a train driver advisory system for evaluation purposes. The difference between this DAS system with other DAS systems is to achieve human factors/usability better and support train drivers better. In this thesis report, important theoretical aspects about human-machine interface design related with the train DAS graphic user-interface (GUI) design and the development methodology used in this project were described. All components of this train Driver Advisory System were described and requirements were analysed. The train DAS development process was described, especially the system architecture and how the system was implemented