23 November: CIECA WEBINAR: Hazard Perception in the Digital Age: Investigating Online Hazard Perception Assessment

PRESENTER: Dr. Petya Ventsislavova, Senior Lecturer in Psychology, Nottingham Trent University 

Online hazard perception assessments offer significant opportunities for driver evaluation and training, both in developed and developing countries. This approach enables us to reach a broad and diverse audience, making it particularly valuable for online training programs where learners can access a variety of hazard perception tests to enhance their skills.

While certain types of hazard perception training for learner drivers are conducted using online platforms such as websites or apps, there has been a lack of extensive research evaluating the effectiveness of online assessments to distinguish between experienced and novice drivers and participants' comprehension of the task. Our aim was to assess whether instructing participants to predict hazards and calibrate risk online could be as effective as in-person assessments conducted in controlled laboratory settings. These tasks were particularly challenging as participants were not just required to react to hazards but to predict them and demonstrate situations awareness, ensuring they were looking in the right place at the right time. They were also required to calibrate the level of risk inherent in each situation and make decisions regarding potential actions.

Several studies were conducted involving different driver groups and a range of scenarios, including hazardous scenarios, non-hazardous ones, and scenarios containing active risky situations. The findings suggested that experienced drivers exhibited better hazard prediction skills compared to novices, especially when they correctly identified the presence of a hazard in the clip. Furthermore, young drivers, especially males, displayed a greater willingness to engage in risky behaviours compared to older drivers.

The newly developed online hazard tests successfully differentiated between experienced and novice driver groups both, in terms of hazard prediction accuracy and drivers' intentions to assume risk. These findings demonstrate the feasibility of creating effective online hazard tests for large-scale testing and training, capable of distinguishing between less-safe novice drivers and safer, more-experienced ones. The implications of these results will be discussed in terms of their connection to the advantages/disadvantages of exploring various approaches to developing hazard test materials, including the use of computer-generated imagery (CGI), and more advanced technologies such as virtual reality (VR).


  • Time: 23 November 2023, 11 am - 12 pm CET
  • Fee: This members-only event is free-of-charge
  • Location: online
  • Working language: English
  • Registration: The deadline for registrations is 12 pm on 22 November 2023