Projects / Programmes
Modelling driver's situational awareness
| Code |
Science |
Field |
Subfield |
| 2.06.00 |
Engineering sciences and technologies |
Systems and cybernetics |
|
| Code |
Science |
Field |
| 2.02 |
Engineering and Technology |
Electrical engineering, Electronic engineering, Information engineering |
Situational awareness (SA), driving performance, driver behaviour, automated vehicles, invehicle information systems (IVIS), human-machine interaction (HMI), attentional resources, advanced driver assistance system (ADAS).
Researchers (1)
| no. |
Code |
Name and surname |
Research area |
Role |
Period |
No. of publicationsNo. of publications |
| 1. |
37510 |
PhD Kristina Stojmenova Pečečnik |
Telecommunications |
Head |
2021 - 2023 |
104 |
Organisations (1)
Abstract
One of the centre interests in the automotive industry over the last few decades has been focused on the development of a fully automated vehicle, often referred to also as an autonomous vehicle. One of the main needs (followed by economic and environmental arguments) behind the desire to develop a driverless vehicle has emerged due to the numerous research and real data revealing the human factor as a contributor to 95% of all road accidents, with driving behaviour being identified as the most significant one. While it is expected that road safety increases with each higher level of automation, the available data suggests that human driving behaviour in semi-automated vehicles may be a weak link in their contribution to road safety. Decreased engagement in the driving task results in reduced levels of situational awareness (knowing what is going on around you). Situational awareness (SA) has an important role in any process of dynamic human decision making as it provides the state of knowledge needed for making effective decisions and taking appropriate actions. SA is a cognitive construct and as such is tightly related to other cognitive theories such as cognitive workload, attention and memory. When observed for the dynamic task of driving on the other hand, it is highly influenced by (and influences back) driver behaviour. All of these relationships have influenced the development of a theoretical model of driver’s SA, upon which a number of assessment methods trying to capture every aspect of SA have been developed. The main problem that this project addresses is that most of these measures focus on different aspects of SA and individually provide limited information on the overall SA of the operator. Furthermore, a lot of them cannot be applied in the dynamic environment of the vehicle, or their design is too intrusive and does not enable ecologically reliable assessment in vehicle. Therefore, this project has two main objectives: 1) development of a model of driver’s SA based on the driving performance, that takes into consideration the characteristics of the driving environment and the task of driving, and 2) development and evaluation of a HMI design that will help the driver maintain continuous SA in different levels of automation. Quantification of the level of SA could be used to derive probabilities of human decisions in the vehicle, which can have great safety impacts in different levels of automated vehicles. Exploratory data analysis will be used to corelate data from physiological, subjective, behavioural and performance metrics of SA with real driving performance, collected in a simulated environment using a high-fidelity driving simulator. The analysis will involve multi-factor correlation analysis to determine which factors tend to have dependencies. This model will explain how each driving performance indicator is associated with the overall SA and provide further information on the relationships with each of the SA levels (perception, comprehension and prediction). This model will enable real time monitoring of SA and identification of driver’s decreased levels of it. By identification of the effects of reduced SA, a solution that prevents them can be created. New HMI design that uses appropriate visual, auditory and tactile cues in order to maintain or restore any potential loss of SA will be proposed. Such design that will help the driver maintain SA can contribute to preventing decreases in SA in automated vehicles, which can further impact safety and comfort of the driver.
