Effects of Automated Systems on Safety (EASY)

This work is intended to examine how some of the new Advanced Driver Assistance Systems, that are envisaged by the car manufacturers, will affect safety. Currently, the most advanced assistance system on the market is Adaptive Cruise Control (ACC) which automates the task of car following. ACC is particularly designed for motorways, but it can also be used on rural and even urban roads. It has deliberate limitations, in that it cannot deal with situations requiring severe braking and in that the ACC forward radar cannot detect stationary objects. The car manufacturers plan to extend the capability of ACC so that it can handle most forward situations. They also plan to provide lane keeping systems which will automate the lateral control of a vehicle (i.e. steering), once again particularly for motorway driving. The combination of longitudinal and lateral control will produce a situation in which a large part of the driving task is automated. As a consequence, there is a risk that drivers will no longer feel a need to pay attention to the road and traffic environment, and therefore may not be aware of impending risk. They may also lose track of when manual control has been resumed, e.g. on exiting from a motorway, and therefore be slower in responding when required to brake or steer.This project will conduct a systematic evaluation of drivers' performance and safety awareness as they experience increasingly greater automation of the driving task. The major tool for this work will be the new driving simulator at the University of Leeds, which will have a complex motion base to provide gravitational feel to the drivers. The forces experienced by the driver in accelerating, braking and steering will be as realistic as possible. The simulator will also use the most up-to-date techniques for image animation to create a fully immersive environment, in which the sensation of driving is as realistic as possible.The initial set of experiments will be designed to identify any safety-related problems that result from driving in a semi-automated vehicle. A wide range of drivers will used, with the major factors in their selection being age, gender and trust in automation. Having identified the problems, a second set of experiments will focus on solutions to those problems, i.e. on ways in which driver alertness and awareness can be enhanced. The results are intended to provide guidance to those governmental organisations that are planning to use new driver assistance systems to increase road capacity and safety. They are also intended to lead to better design of new products by the vehicle manufacturers.