NDLI: How do principles for human-centred automation apply to disruption management decision support?

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How do principles for human-centred automation apply to disruption management decision support?

Content Provider	Semantic Scholar
Author	Golightly, David Dadashi, Nastaran
Copyright Year	2016
Abstract	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.
Starting Page	150
Ending Page	156
Page Count	7
File Format	PDF HTM / HTML
DOI	10.1109/ICIRT.2016.7588725
Alternate Webpage(s)	http://eprints.nottingham.ac.uk/34276/1/golightly_ieee_icirt_accepted.pdf
Alternate Webpage(s)	https://doi.org/10.1109/ICIRT.2016.7588725
Journal	2016 IEEE International Conference on Intelligent Rail Transportation (ICIRT)
Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article

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