Automated Driving Systems: Understanding Future Collision Patterns

Published: Dec 2017

Citation:

ISBN: 978-1-912433-13-1

Author: T L Robinson, C Wallbank & A Baig

Pages: 54

Reference: PPR851

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Automation of the driving task is becoming more common and automated or self-driving vehicles are increasingly becoming a reality. The development of these vehicles is widely reported in the media. Previous research by KPMG estimated that by 2040 80% of collisions will be avoided through the introduction of automated vehicles. Before the full adoption of automated vehicles, there will be an interim period where traditional and automated vehicles will need to co-exist. During this period, are there likely to be different types of collision? What are the potential risks of a vehicle fleet with a mix of automated and non-automated vehicles?

This document describes the proof of concept of a methodology for assessing the potential effect of introducing automated vehicles on the frequency and types of collision that may occur. The methodology uses in-depth case analysis from the UK Road Accident In-Depth Studies (RAIDS) and vehicle fleet data to estimate the effect on collisions of introducing automated vehicles into the vehicle fleet. Improvements to the methodology and additional resources to provide more robust analysis have been identified.

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