Training implications for drivers of automated vehicles
Lead Research Organisation:
University of Southampton
Department Name: Sch of Engineering
Abstract
The IAM system of vehicle control (IPSGA: Information, Position, Speed, Gear,
Acceleration) was developed for manually driven vehicles but the nature of
driving is changing from active control to passive monitoring and supervision
with Automated Vehicles (AVs). Prof Stanton has previously managed a research
project funded by the IAM to validate the IPSGA coaching system (Stanton et al,
2007a; Walker et al, 2009). This is a natural extension of that work. The aim of
this research is to design, develop, test and validate a new system of automated
vehicle control, to supplement IPSGA. It is not a question of if AVs will be seen on
public roads but rather when, therefore it is essential that we train drivers to
adapt to the changing nature of the task.
Acceleration) was developed for manually driven vehicles but the nature of
driving is changing from active control to passive monitoring and supervision
with Automated Vehicles (AVs). Prof Stanton has previously managed a research
project funded by the IAM to validate the IPSGA coaching system (Stanton et al,
2007a; Walker et al, 2009). This is a natural extension of that work. The aim of
this research is to design, develop, test and validate a new system of automated
vehicle control, to supplement IPSGA. It is not a question of if AVs will be seen on
public roads but rather when, therefore it is essential that we train drivers to
adapt to the changing nature of the task.
Organisations
People |
ORCID iD |
| Neville Stanton (Primary Supervisor) | |
| Siobhan Merriman (Student) |
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| EP/R513325/1 | 01/10/2018 | 30/09/2023 | |||
| 2282832 | Studentship | EP/R513325/1 | 01/10/2019 | 30/09/2022 | Siobhan Merriman |
| Description | The aim of this award was to design, develop, test and validate a new training programme for drivers of Automated Vehicles (AVs), to supplement IAM RoadSmart's current system of vehicle control for manual vehicles. The work funded through this award helped to identify nine key themes in driver training for AVs. These themes were applied to currently deployed training programmes and five AV collisions to demonstrate the relevance of these themes to AVs and driver training. A Training Needs Analysis was conducted to establish the tasks and competencies that drivers need to safely operate an AV system for motorways and dual carriageways. This Training Needs Analysis was then used to develop an online video-based training resource and a training package for the safe activation of the AV. Online and driving simulator evaluation studies demonstrated short-term benefits of these training programmes over no training (better activation decisions and behaviours) and the current training method for AVs (owner's manuals: better knowledge, reduced mental demand). Therefore, the work funded through this award helped to design, develop, test and validate a training programme for drivers of AVs, thereby meeting the original aims and objectives of this award. |
| Exploitation Route | Academics could extend this work by conducting a longitudinal evaluation to see whether there are any long-term benefits of the training programmes over no training and owner's manuals. Additionally, it is not a question of if AVs will be seen on public roads but rather when, so the findings and insights from this work can be used by training organisations to develop effective training programmes so that drivers operate future AV systems safely and appropriately on the road. |
| Sectors | Transport |
| Description | The findings from this award have had both academic and non-academic impacts. In 2022, the findings from this award were submitted as written evidence for the Transport Committee's Consultation on Self-Driving Vehicles, in particular in relation to the progress of research and trials in the UK and abroad. Additionally, from 2020-2022, three presentations were presented to academics and industry experts involved in Transport, Human Factors and driver training, which sparked discussions on the future needs and training programmes for drivers of AVs. |
| First Year Of Impact | 2022 |
| Sector | Education,Transport |
| Impact Types | Policy & public services |
| Description | Contributed to a Government Policy Consultation on Self-Driving Vehicles |
| Geographic Reach | National |
| Policy Influence Type | Contribution to a national consultation/review |
| URL | https://committees.parliament.uk/work/6795/selfdriving-vehicles/publications/written-evidence/ |