TRANSITION: Transport safety in automated vehicles

Lead Research Organisation: University of Leeds
Department Name: School of Psychology

Abstract

Driver error is a major contributor to many road accidents: there were 194,477 reported road casualties in the UK in 2014 (with an estimated valuation of £16.3 billion; Department for Transport, Reported Road Casualties Great Britain: 2014, Annual Report), and the most commonly recorded factor was the "driver/rider failed to look properly" (DfT, 2014), with four of the five most frequently reported contributory factors involving "driver error or reaction". In this context the increased use of Automated Vehicles (AVs) that can control the vehicle and monitor and respond to road conditions without regular driver input has the potential to dramatically reduce road death. A major concern, however, is that many AVs require human supervision, and despite our lack of understanding how human drivers interact with AVs there are already AV systems that are available for purchase and are being used on the roads (e.g. Tesla). In order to safely implement AV systems we need to understand the capabilities and limitations of drivers re-engaging steering control from AV systems under a variety of conditions.

Project TRANSITION will use sophisticated laboratory-based measures (including advanced vehicle simulators) to examine drivers re-engaging with the vehicle after a period of AV control. We will determine the capability of drivers regaining steering control under conditions that simulate various types of visual and cognitive load (e.g. driving at night, and/or when looking away at a satellite navigation system). These findings will be used to identify situations where drivers are particularly vulnerable to making steering errors, and develop the TRANSITION model of AV-Human transitions that will inform improvements to the design and implementation of AV systems.

This project is critical to improve AV systems to ensure they safely manage AV-human transitions, and to develop more effective human-machine interfaces between drivers and their vehicles. Whilst there has been widespread coverage of the development of fully automated vehicles, it is unlikely that full-automation will quickly become the norm. Indeed 'driverless' vehicles are already technologically possible, but there are significant barriers to adoption, and the prevalent view is that the human driver will remain the primary controller of the vehicle for some time. There are a number of reasons for this, including driving in regions where automation is not possible (e.g. poor GPS coverage, inaccurate mapping or poor road demarcation), needing the human to control the vehicle when automatic systems fail, and not least because some drivers will continue to purchase vehicles that allow them to be in control for some periods. In this context, understanding the best way to ensure safe interactions between human and AVs remains a high priority.

Planned Impact

The main purpose of this project is to determine the capabilities and limitations of drivers re-engaging control of Automated Vehicles (AVs). The impact of the research will be to use this understanding to ensure that widespread use of AVs does not lead to large numbers of road casualties. Various impact activities have been budgeted as outlined in the Justification of Resources. Ensuring this impact is realised requires close cooperation between academic and industrial collaborators as well as relevant stakeholders. We envisage that the project will have an impact in two primary non-academic domains: i) policy and legislation and ii) automobile software.

i) Policy and Legislation - Arup are included as consultants for this project to provide their expertise performing stakeholder consultations across a variety of governmental and commercial sectors (e.g. European Commission, Department for Transport, Highways England, PACTS, SMMT, European Cyclists Federation, CLEPA, ACEA, Volvo and Daimler Group, International Road Transport Union, FIA, Transport and Environment and ETSC). Successful impact will be marked by the TRANSITION findings being cited in policy documents governing the functioning of AVs (e.g. minimum system capabilities required for safe AV-Human transitions) or their use (e.g. allowed and disallowed driver activity while in automated driving modes of different levels).

ii) Automobile Software - The project will lead to the generation of the TRANSITION computational model that could be implemented and sold by a University spin out company or licensed to automotive manufacturers or suppliers for integration within automobile development processes and/or real-time AV systems. The University of Leeds has a strong track record of securing patents and commercialising research findings and the Research and Innovation Service will provide central support for these activities during this project.

The project also has an advisor based in Volvo Cars (Victor) who will act as a crucial route for ensuring there is impact of the scientific findings within industry (via various international scientific and working groups e.g. NWI ISO 17488, Transportation Research Board, European Working Group on Driver Distraction). Broader dissemination will take place within the two workshops that will include participants from invited stakeholder groups: the Automotive Council, road safety charities such as BRAKE and RoSPA, and relevant representatives from the Highways Agency, Department for Transport, Transport for London and the Institute of Advanced Motorists. We will promote our research to local communities and the general public via two exhibits: 1) The Leeds Festival of Science: Leeds has a well-established festival which attracts thousands of school children and members of the public. 2) The Science Museum's Antenna space. In addition our findings will be presented at both national and international conferences, and published in open access journals in order to reach the broadest audience of academics and commercial interests in the sector.
 
Description This project examines how humans drivers engage with automated vehicles (during 'Transitions' of control). We established international links (Dr Lappi, U.Helsinki; Dr Mars, LS2N, Nantes) and with these collaborators we have published an explanatory framework for understanding control transitions based on models of human steering control. This framework can be summarised as a perceptual-motor loop that requires i) calibration and ii) gaze and steering coordination. We identified that currently the success of transitions are often measured using reaction times, however, the perceptual-motor mechanisms underpinning steering quality remain relatively unexplored. Modelling the coordination of gaze and steering, and the calibration of perceptual-motor control will be crucial to ensure safe and successful transitions out of automated driving. This conclusion poses a challenge for future research on AV-Human transitions. We are currently collecting and writing up data from project Transition that addresses these challenges in order to provide an understanding of human behaviour which will be sufficient to capture the essential characteristics of drivers re-engaging control of their vehicle.
Exploitation Route Our proposed explanatory framework can provide a guide for investigating specific components of human control of steering, and potential routes to improving manual control recovery.
Sectors Digital/Communication/Information Technologies (including Software)

Transport

 
Description One of the research papers produced during the project (Mole et al. 2017) has been cited in a report to the European Commission, Directorate-General for Mobility and Transport. The aim of the report is to provide strategic and practical advice to DG MOVE on the policy-related actions required to address disruptive digital developments, particularly the transition to automated driving and its effects on driver behaviour and performance. The final report was published in 2020 - https://data.europa.eu/doi/10.2832/431870
First Year Of Impact 2020
Sector Transport
Impact Types Policy & public services

 
Title Highly Controlled Laboratory Experiments (pilot) 
Description We report on three studies that adopt a highly controlled experimental approach to investigate transitions out of automated driving. In these studies groups of participants experienced many repeated short trials (20s) of driving on curves, which consisted of an initial period of automation followed by a quick system-initiated transition to manual control by the human driver. The behavioural focus is on the primary factors determining steering control in the first few seconds after transitions out of automated driving. In the first two studies we examined how steering was affected by where a driver was looking (gaze direction) both before and after automation (Pilot1), and the driver's level of perceptual-motor calibration to their environment (Pilot2). In the last study we report both steering and gaze behaviours under varying levels of an auditory distraction task (Pilot3). Due to some simulator issues that were uncovered after testing (Supplementary Materials) there was greater noise in these data than we consider ideal. We have, however, extensively analysed these data and believe that the findings nevertheless represent a useful and valid scientific contribution. The headline findings are: The direction of where you look during the seconds before a transition may influence how you steer during manual control immediately after automation. Active control of steering appears to be necessary for drivers to adapt steering control in response to altered environmental conditions (in our experiments an increase in speed). Increased cognitive load led to gaze sampling that was more concentrated and steering that was smoother but more erroneous. In our particular scenario, however, any potential interaction with automation was unclear. 
Type Of Material Database/Collection of data 
Year Produced 2018 
Provided To Others? Yes  
Impact These data/analyses form the basis of 3 papers submitted to "Driving Assessment 2019" (https://drivingassessment.uiowa.edu/2019-conference) Modelling of the 'CogLoad' data is underway and a paper is in preparation (as of 1/3/2019) 
URL https://osf.io/yzgra/
 
Description Literature review and expert workshop - Department for Transport 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Policymakers/politicians
Results and Impact An expert workshop with industrial, policymakers and academic partners with an expertise in driver distraction, to inform further research by the UK DfT
Year(s) Of Engagement Activity 2022
 
Description QUADRAE engagement 
Form Of Engagement Activity A formal working group, expert panel or dialogue
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact An initial visit to Chalmers University of Technology in Sweden led to regular meetings between the Transition team and project QUADRAE (Quantitative Driver Behaviour Modelling for Active Safety Assessment Expansion; running from 2016-01-01 - 2019-12-31; managed by Mats Petersson). Our projects were found to have complimentary research questions (applied to different driving domains) so an understanding was reached to ensure sharing of research plans and findings during these projects.
Year(s) Of Engagement Activity 2017,2018
URL https://www.saferresearch.com/projects/quadrae
 
Description Volvo Cars 
Form Of Engagement Activity A formal working group, expert panel or dialogue
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Industry/Business
Results and Impact Four members of the Transition team visited Volvo Cars in Gothenberg on a "fact finding mission". We disseminated our research findings, which were warmly received, and investigated ways in which our planned research would be most useful for the automotive industry.
Year(s) Of Engagement Activity 2018