Resilient interactions between cyclists and drivers, and what does this mean for automated vehicles?

The road transport system is a complex sociotechnical system that relies on a number of formal and informal rules of the road to ensure safety and resilience. Interactions between vulnerable road users and drivers often includes informal communication channels that are tightly linked to social norms, user expectations and the environmental context. Automated vehicles have a challenge in being able to communicate and respond to these informal rules of the road, therefore additional technologies are required to better support vulnerable road users.

Training for the safe activation of Automated Vehicles matters: Revealing the benefits of online training to creating glaringly better mental models and behaviour.

Automated Vehicle (AV) systems are expected to reduce the frequency and severity of on-road collisions. Unless drivers have an appropriate mental model for the capabilities and limitations of the automation, they may not activate the automation safely or appropriately on the road, potentially leading to a collision. As such, a training package (L4DTP) was developed to improve drivers' decisions and behaviour when activating an AV system and this was evaluated in a between-subjects simulator experiment.

A new approach for Training Needs Analysis: A case study using an Automated Vehicle.

Considerable resources are invested each year into training to ensure trainees have the required competencies to safely and effectively perform their tasks/jobs. As such, it is important to develop effective training programmes which target those required competencies. One method that can be used at the start of the training lifecycle to establish the tasks and competencies that are required for a task/job and is considered an important activity to perform when developing a training programme is a Training Needs Analysis (TNA).

'Please sort these voice recordings into 2 identities': Effects of task instructions on performance in voice sorting studies.

We investigated the effects of two types of task instructions on performance on a voice sorting task by listeners who were either familiar or unfamiliar with the voices. Listeners were asked to sort 15 naturally varying stimuli from two voice identities into perceived identities. Half of the listeners sorted the recordings freely into as many identities as they perceived; the other half were forced to sort stimuli into two identities only.

Breaking voice identity perception: Expressive voices are more confusable for listeners.

The human voice is a highly flexible instrument for self-expression, yet voice identity perception is largely studied using controlled speech recordings. Using two voice-sorting tasks with naturally varying stimuli, we compared the performance of listeners who were familiar and unfamiliar with the TV show . Listeners organised audio clips of speech with (1) low-expressiveness and (2) high-expressiveness into perceived identities.