TRL is a key member organisation of the StreetWise consortium, launched in 2017 and funded in part by Innovate UK, the UK’s innovation agency.

StreetWise aims to develop and demonstrate the technology, safety validation methods, insurance and service models required to deliver an automated personal mobility solution, targeted at replacing the urban commuter car.

Led by FiveAI, a UK-based company focused on creating a fully automated, shared transport service for Europe’s cities, the StreetWise consortium also includes transport industry innovators, including Torr Vision Group (part of the University of Oxford), McLaren Applied Technologies, Direct Line Group and Transport for London.

The challenge

Automated vehicles are central to the UK government’s industrial strategy because of the potential they represent for addressing several challenges facing urban areas, including congestion, vehicle emissions, commuting time and costs and road traffic casualties.

Before automated vehicles can be safely and successfully integrated into urban road networks, in-depth track and real-world testing on public highways must be carried out.

To meet the necessary legal requirements to conduct testing on public highways and secure insurance for the trial, a robust safety case must be developed.

Our approach

TRL’s role in the project is to develop the Safety Case for on-road trials of automated vehicle technologies, based on TRL’s extensive experience with developing safety cases for automated vehicle trials. The Safety Case is intended to help manage and reduce potential risks involved in trialling these technologies on the public road. A carefully managed approach to testing in real-world environments is an essential part of developing automated driving systems for deployment in road vehicles.  The abridged Safety Case is published here.

TRL is also closely analysing UK collision data before defining priorities for simulation-based testing. TRL will then curate a database of test scenarios. As a result, TRL will develop a proof of concept for a large-scale scenario database that will facilitate the testing and certification of automated vehicles for use on UK roads.

To facilitate the development of the test scenario database, the project is developing a Scenario Description Language (SDL), which incorporates definitions of both static (i.e. road geometry) and dynamic (vehicles, cyclists, pedestrians etc.). The database will be used to test and validate the performance of automated vehicles, in particular ensuring that they respond accurately and appropriately to a vast range of scenarios encountered on UK roads.

The results

A successful outcome of this project will be the development and demonstration of an automated system, which is globally-competitive, safe, secure and validated to the standard required for a major insurer to underwrite it. It is hoped this will lead to commercial service implementation within 12-18 months of project completion (scheduled for Q1 2020), that will provide cities like London with a clean, safe, convenient and affordable commuting alternative.

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