4 research outputs found
Data for thesis titled: Understanding, developing and evaluating a blended training approach for drivers of automated vehicles which require shared control and human input
Study data for the two studies that were conducted in this thesis in Chapters 9 and 10 and the complete TNA for Chapter 6.</span
What can we learn from Automated Vehicle collisions? A deductive thematic analysis of five Automated Vehicle collisions
There have been a number of high-profile collisions involving Automated Vehicles on the road. Although car manufacturers are making considerable investments into the development of Automated Vehicles, these collisions may deter the public from purchasing and using them. Therefore, solutions need to be developed to prevent these collisions from occurring in the future. One such solution is driver training. A previous literature review identified nine themes which are essential in Automated Vehicle driver training. In this article, a deductive thematic analysis was conducted on five high-profile Automated Vehicle collisions in order to demonstrate the relevance of these themes and to gain insights into how the driver’s behaviour contributed to each collision, thus understand the potential role of training in reducing collisions of this nature. By creating interconnection models for each collision, a consistent pattern emerged. A link was made with the drivers’ attitudes, the accuracy of their mental models and their level of trust in the automation. The automation caused the drivers to become underloaded, which impaired their ability to effectively monitor the automation and the road environment. This could have impaired their situation awareness and their ability to identify and avoid hazards in the path of their vehicle. This analysis suggests that future Automated Vehicle driver training programmes should be multifaceted and cover all nine themes. This analysis has validated these nine driver training themes, so these themes and interconnections can help in the development of a comprehensive training programme for drivers of Automated Vehicles in the future
Challenges for automated vehicle driver training: A thematic analysis from manual and automated driving
Considerable research and resources are going into the development and testing of Automated Vehicles. They are expected to bring society a huge number of benefits (such as: improved safety, increased capacity, reduced fuel use and emissions). Notwithstanding these potential benefits, there have also been a number of high-profile collisions involving Automated Vehicles on the road. In the majority of these cases, the driver’s inattention to the vehicle and road environment was blamed as a significant causal factor. This suggests that solutions need to be developed in order to enhance the benefits and address the challenges associated with Automated Vehicles. One such solution is driver training. As drivers still require manual driving skills when operating Automated Vehicles on the road, this paper applied the grounded theory approach to identify eight “key” themes and interconnections that exist in current manual vehicle driver training. These themes were then applied to the limited literature available on Automated Vehicle driver training, and a ninth theme of trust emerged. This helped to identify a set of training requirements for drivers of Automated Vehicles, which suggests that a multifaceted approach (covering all nine themes and manual and Automated Vehicle driving skills) to driver training is required. This framework can be used to develop and test a training programme for drivers of Automated Vehicles
How can we close the gender data gap in transportation research?
This article is a call to action for Human Factors and Transport Researchers to create a fairer society, by closing the gender data gap. The need for gender equitable research outcomes is put forward, and practical steps to further this goal are provided to ensure gender is considered at all stages of the research lifecycle. The journey of a voluntary task force from a transport research group in the United Kingdom is described. Insights following a review of their own research practice is provided, describing the challenges to, and opportunities for, closing the gender data gap. The need for greater guidance and emphasis on equity within research teams is recognized, and examples of how researchers at different stages of their career can make a difference are provided