TASCC: Human Interaction: Designing Autonomy in Vehicles (HI:DAV)

Lead Research Organisation: University of Southampton
Department Name: Faculty of Engineering & the Environment


Cars that can drive themselves have been predicted for some time, but they are nearly with us. Highly automated vehicles are likely to be on public roads within the next ten years. The largest gap in our understanding of vehicle automation is how drivers will react to this new technology and how best to design the driver-automation interaction. Our project will answer these questions by studying a wide range of drivers with different driving experience in simulators, or test-tracks and in road going vehicles.

We will start by modeling driver behaviour in our laboratories in order to help us design inclusive, user-centered, interfaces with vehicle automation. We plan to learn from different situations where automation is already used (such as the Boeing versus Airbus design approach of 'soft' and 'hard' automation). Then we will test the designs out in our driving simulator (which comprises a Jaguar XJ connected to computers with large projectors and screens). We will test drivers of different ages, gender, experience and capabilities, in a range of scenarios (e.g., different road types and environmental conditions) with different automation systems (e.g., autonomous driving, auto 'valet' parking, adaptive vehicle personalization, off-road assistance) and different interfaces (which we will design).

Our design approach will personalise the driver interfaces to the widest range of drivers possible (e.g., wide ranges of age and driving experience). We want the driver-automation interfaces to be intuitive and the necessary responses to be obvious. We design so that the system adapts to you, not you having to adapt to the system. We will also monitor driver behaviour over successive weeks of use. This will help us to understand how drivers learn to respond to the automation over time. We will be studying how control of the vehicle is handed back and forth between the automation and the driver. We are also interested to know what the driver is doing when the vehicle is under automated control. To help in this understanding, we will be monitoring the driver physiological and psychological states. The idea is to use this information to adapt the automation to the driver and the situation, so that performance of the system is optimised. This will enhance safety to the benefit of the driver and other road users.

The studies will progress from the simulator to the test-track, as our interaction and interface designs evolve with testing. On the test-track we can record driver behaviour physiological and psychological states to see what further changes are needed and whether the automation can be even more highly tailored to the situation. As the research progresses we will take the revised designs into road going vehicles for the final set of tests. These tests will be used to validate the designs and prepare them for delivery into production vehicles. At the end of the research, we will be able to provide JLR with the design methods and well as the designs themselves. This means that they will be able use the methods we have provided to design new systems into the future.

During the course of the research the Universities of Cambridge and Southampton will be working closely with JLR engineers to ensure that the UK remains at the forefront of technological innovation in vehicle automation. We will have answered the questions about how drivers will react to this new technology and how best to design the driver-automation interaction. The success of vehicle automation design will be on designing appropriate interactions and interfaces that support the driver. Our research will be essential to that success.

Planned Impact

Jaguar Land Rover
JLR will benefit in terms of the interfaces and interaction designs that can be placed into production vehicles. We will work closely with JLR to ensure that the cutting-edge insights into designing autonomy together with the associated methods and interfaces are shared as soon as they are available. Secondment opportunities at the Universities of Cambridge and Southampton will be offered throughout the project so that they can work alongside the researchers on the project. Workshops will be held with JLR engineers to train them in the methods. A project website will be hosted. It will contain case studies, methods, and research findings for JLR and the research teams to use. At the end of the project JLR will be equipped with design guidance, design methods, final prototype adaptive interfaces and experience of working with world-leading Human Factors Engineering researchers. This will equip JLR with all the necessary expertise to help them move towards a fully autonomous car.

Vehicle Manufacturing Supply Chain
UK economic growth depends on maintaining a world-leading position in automotive research and development. Features, such as vehicle automation, are vital in this respect. The addressable market size would initially be on JLR products - approximately 400,000+ cars per year, with the majority taking autonomous driving technologies. The global car market is much bigger and, with autonomous driving systems in cars growing significantly, this technology could become a defining basis of the autonomous driving interface.

Automotive Standards Organisations
The findings from the research will inform Automotive Standards Organisations about the limits of driver performance which need to be observed in design. Such limits are likely to include the nature of the handover tasks from driver to vehicle and back again, the timeliness of driver interventions, driver state monitoring and the degree of driver engagement/disengagement with different types of automation. The research would also be able to deliver templates for driver-automation interaction and interface strategies together with recommended methods and guidelines for vehicle automation.

Wider Society
The inclusive design focus will assist in driving mobility for all. This will help to support and assist the mobility of older drivers and help in maintaining their independence and quality of life. Congestion can be reduced with automated vehicles by re-routing to avoid busy roadways and smoother driving to avoid the 'snaking' that can occur with manually operated vehicles. Automated vehicles can help to the driver to reduce emissions and achieve better fuel economy through smoother acceleration and deceleration profiles. Automation can also help to reduce driver stress by smoothing out the peaks and troughs of driving workload. Finally, an accident reduction is anticipated through automated driving supporting driver situation awareness in both longitudinal and lateral control, as well as taking-over if the driver fails to cope in an emergency. The automotive specific findings could be generalisable to other field such as aviation, nuclear and rail.


10 25 50
Description Jaguar Land Rover 
Organisation Jaguar Land Rover
Country United Kingdom 
Sector Private 
PI Contribution Collaborating with Jaguar Land Rover on the development of new driver interfaces for vehicle automation. We have already tested competitor products in Tesla and Mercedes.
Collaborator Contribution We have already tested competitor products in Tesla and Mercedes.
Impact Reports to JLR on project progress
Start Year 2016