IT services: consulting, software development, Internet and support

Tender description

As part of its Surface intelligent transport system (SITS) programme, Transport for London (TfL) is now preparing to undertake a project to deliver predictive capability and is seeking market feedback in relation to potential solutions. The objective of the SITS predictive capability project is to deliver a system that can predict the future state of London’s transport network and estimate the impact of incidents on the network for a future time horizon as quickly as possible, taking into account the current network state. Simultaneously, the system will also be able to forecast the outcome of manually defined mitigation strategies and rank them on the basis of user defined key performance indicators (KPIs), as well as have the capability to generate its own optimal response strategies. The ultimate aim is for effective responses to incidents to be implemented before road network disruptions become significant and widespread. Further detail is provided at Section II.2.4) below. SITS is TfLs response to growing pressures upon the capacity of London's road network and the need to deliver the Healthy Streets Approach through encouragement of sustainable, active, safe and efficient travel. SITS will allow TfL to prioritise people who are walking, cycling and using buses, and will also provide the capability for TfL to unlock significant additional capacity on the road network. SITS will be delivered across four main projects: 1) Real time optimiser (RTO); 2) Common operational view incident management system (COV IMS); 3) Data and analytics — involves: (a) data hub; and (b) data roadmap; and 4) Predictive capability. The RTO, COV IMS and data and analytics projects are already underway and TfL now wishes to commence work on predictive capability. To assist with this, as permitted by Regulation 40 of the Public Contracts Regulations 2015, TfL is seeking market feedback in relation to potential solutions that may be capable of predicting the future state of the road network. Such solutions would forecast the likely outcome of an incident over a future time horizon and generate optimal response strategies, which can then be manually or automatically applied, so that an effective response could be implemented before disruptions become significant and widespread. The term ‘incident’ is used to describe situations where the road network state is different to normal for one or more transport modes. Traffic collisions (random events) and roadworks (planned events) are some prominent examples of an ‘incident’. TfL is looking for an innovative solution and wishes to explore all available technologies. TfL is open to working with suppliers to develop ideas with potential, or to adapt solutions to meet its requirements, and is keen to hear from organisations that already have, or are capable of developing, technology able to solve the problem characterised by: — variable demand fluctuating throughout day/week/year, — complex transport network catering for multiple modes (pedestrians, cyclists, buses, taxis, cars, etc.), — multiple, simultaneous incidents that may have combined effects due to spatial proximity, and — multiple datasets (historic or live feeds) that potentially could be conflicting or of low accuracy.