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Supply of a SITS Predictive System

Published

Description

TfL wishes to invite potential suppliers to help shape how it might define, procure and contract for a SITS Predictive System. The purpose of this Prior Information Notice is to notify the market of TfL's intention to carry out early market engagement to assess the current market capabilities and appetite for the requirement, and to provide details of how the early market engagement process is to be conducted. TfL, at any time through this market engagement process and, at its sole discretion, may enter into discussions with respondents to this PIN. Feedback from respondents will assist TfL in understanding the current supply market considerations for the SITS Predictive System and inform the continued development of the procurement strategy for any potential future contract(s). Suppliers wishing to participate in this market engagement process and view all associated documents including the Market Brochure and Market Sounding Questionnaire (MSQ) should send an email to PredictiveCapability@tfl.gov.uk to express interest and provide appropriate contact details. TfL reserves the right to make changes to this advertisement without notice and without reason at any time. Lot 1: The SITS Predictive project is to deliver a software-based system with the capability to forecast the future state of the road network in response to TfL mitigation measures to resolve congestion due to: unplanned incidents; planned events; or road network changes. The key features and capabilities of the future system are: • forecast the state of the transport network for the next 60 minutes (broken down into 10-20 minute intervals) within 5 minutes from the point of request; • cover the whole of London taking account of multiple concurrent incidents and multiple concurrent mitigation strategies; • use different datasets (static, historic and real time) to make decisions and be able to operate whilst accommodating a variety of input data; • select mitigation measures (e.g. traffic signal plan and procedures) based on the incident details and area of interest; • assemble mitigation strategies to be modelled simultaneously (alongside a 'Do Nothing' scenario) and rank them on the basis of user-defined metrics; • ultimately use machine learning/artificial intelligence to build and recommend optimal mitigation strategies on the fly and evolve to take advantage of emerging technologies. • produce results that are valid against the data collected from the field to an agreed TfL standard; • provide outputs (KPIs, speeds, flows etc.) for a user-defined Area of Interest (AOI); • amend the future recommendation of the selected mitigation strategy by assessment based on the accuracy of the selected strategy against actual results (a feedback loop); • connect seamlessly to other SITS components such as the RTO system, Data Service Hub and COV IMS for data input and output; and • provide a user interface for administration, configuration and independent scenario testing. These features enable TfL to keep traffic moving by identifying and deploying evidence base effective responses prior to the impact of disruptions becoming significant and widespread. TfL wishes to engage with the market to help shape how we might define, procure and contract for a new SITS Predictive System. This will be achieved through assessing the current market capabilities and appetite for a SITS Predictive Capability contract. TfL are seeking to explore different options for the procurement, delivery and ongoing operation of the SITS Predictive System. This includes exploring how a machine learning solution might be delivered without first having to deliver a system using established network modelling techniques. As part of the early market engagement to be undertaken, TfL would like interested parties to respond to a Market Engagement Sounding Questionnaire (MSQ). Parties that express their interest will be provided with a Market Brochure containing further details of the SITS Predictive project along with the MSQ and certain other relevant information. Responses to the MSQ should be sent to PredictiveCapability@tfl.gov.uk and are politely requested by no later than Friday 01 November 2024. TfL will endeavour to keep all interested parties updated on future developments with regards to the SITS Predictive project.

Timeline

Publish date

3 months ago

Buyer information

Transport for London

Email:
predictivecapability@tfl.gov.uk

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