Source: https://tendernation.io/opportunities/01a13c25-f14d-730e-950a-2186033bc236/rssb2725-trial-of-automated-driver-competence-indicators-using-on-train-data-r closed GB open procedure Suitable for SMEs # RSSB2725 - Trial of Automated Driver Competence Indicators using On Train Data Recorders, to support driver management [Rail Safety and Standards Board Limited](https://tendernation.io/buyers/rail-safety-and-standards-board-limited) Estimated value £170,000 to £180,000 Published 23 Oct 2018 Deadline Closed 28 Nov 2018 ## Who can bid - Buyer says suitable for SMEs The buyer ticked “suitable for SMEs” on the notice. Anyone can still bid. - Open procedure Anyone can submit a full tender; there is no shortlisting stage. [More contracts for small businesses and VCSEs](https://tendernation.io/opportunities/for-small-businesses) ## About this tender ### Background and context The rail industry invests significant amounts of time and money in driver training and in demonstrating driver competence through assessments, including manual analysis of data from On-Train Data Recorders (OTDR). OTDR data can also be used in investigating operational incidents such as signals passed at danger (SPADs), stop shorts, station overruns and wrong side door releases. These activities, which are typically incorporated into a competence management system can be time-consuming to monitor, and therefore incur substantial cost. Additionally, there is presently no agreed industry approach to demonstrating the efficacy of competence management systems in an objective manner. Under the Strategic Partnership established with University of Huddersfield (UOH), a project was carried out to investigate the feasibility of developing of a range of Automated Driver Competency Indicators (ADCIs) based on the automatic analysis of OTDR data. The results of the project were presented at an industry workshop in October 2016, which was jointly hosted by RSSB and UOH and attended by a wide range of industry stakeholders. The general conclusion was that it is possible to derive ADCIs from OTDR data that have the potential to support driver performance management, and a number of preferred metrics were identified. Potential benefits of ADCIs identified included: - Reducing the time taken for driver managers to manually check OTDR data, and the potential to reduce costs in doing so. - Improved visibility and frequency of driver performance - Having more objectivity, and consistency to assessment of driver performance - Capturing data over time, allowing monitoring of trends and precursors - Providing drivers with timely feedback on their performance - Allowing better targeting of competence management focussing on those drivers in need of support Following the workshop, the project and its outcomes were discussed at the cross-industry Data & Risk Strategy Group (DRSG), in September 2017. DRSG recommended that a 'demonstrator project' be carried forward to implementation, in close partnership with a TOC, and involving suppliers and other relevant areas expertise as appropriate. The current specification outlines the proposed way forward for this 'demonstrator project'.   ### Project structure This project aims to develop, trial and demonstrate value from a tool to assist Train Operating Companies (TOCs) with driver competence support and management. To achieve the benefits from the tool, it is important for the ADCIs developed to be guided by the end users - the Train Operating Companies. It is for this reason that RSSB are partnering with both c2c and London North Eastern Railway (LNER), who have agreed to share their data and support the development of the ADCIs through guidance and feedback. Read full description ## CPV classification Research and development services and related consultancy services Source Contracts Finder (UK) [View official notice](https://www.contractsfinder.service.gov.uk/notice/73a46151-79b9-4de0-9df7-9380d9ab40f8) Never miss a tender like this again Get AI summaries, deadline alerts and a bid pipeline for tenders matched to your business. Free to start. 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