Human behaviour is often cited as the primary contributing factor to road accidents, where over 90% of all crashes are attributed to ‘human error’. This implicitly attributes accidents to individual fault, suggesting that such instances could be mitigated by appropriate behaviours. This perspective has also fuelled enthusiasm for (semi-)automated vehicles. However, this is a limited vision for at least two reasons. First, most road users strive to avoid road accidents. Second, fatalities continue to persist with the use of (semi-)automated vehicles and it remains unclear how this will change with increased adoption, if at all. Conversely, modern perspectives to human behaviour suggest that ‘human error’ is a product of its whole setting, making fundamental the study of the relationship between the individual and its working environment. Therefore, a suitable vehicle should enable drivers to act with minimal margin for unintended error with the final goal to design complete human-centred traffic systems. Even if automation can mitigate for driving-related risks, it will present challenges that can only be anticipated by first understanding the cognitive mechanisms that underlie our ability to perform in road traffic systems. To this aim, it is vital that we possess better tools to understand, measure and monitor human behaviour and the corresponding cerebral activity across diverse road scenarios, including those that do not generate overt behaviour.
The emerging field of Neuroergonomics employs unobtrusive methods to understand how the individual responds to its environment before generating appropriate responses. More importantly, it can also explain why responses might not be generated in the first place. Nowadays, both commercial and custom made portable and wearable devices allow to measure behaviour and neurophysiological activity, such as eye tracking, electroencephalography (EEG), functional near-infrared spectroscopy (fNIRS), electrocardiogram (ECG), galvanic skin response (GSR) and respiration, making it feasible to learn more about behavioural and neural mechanisms that underlie human perceptual, cognitive, and motor functioning in everyday traffic scenarios. Such tools can provide new knowledge about human capabilities in terms of behaviour, cognition, intention, perception, emotion, decision making, attention and cognitive workload, and aid and expand our understanding of how road users navigate complex traffic environments and negotiate with other road users. This approach is growing in importance, in the wake of increasing vehicle automation that limits explicit driving behaviour.
This Research Topic calls for submissions that cover modelling, behavioural and neurophysiological measures applied to pedestrians, cyclists, riders and drivers of conventional as well as (semi-)automated vehicles and environments. In addition, we welcome insights from basic research and other domains of vehicle systems that can contribute to the development of a safe human-centric road traffic system. Submissions can be any article type that covers neuroscientific methods and techniques as well as behavioural and neuroimaging analysis approaches to investigate cognitive mechanisms in actively behaving road users, either in virtual reality, driving simulator or field settings.
Human behaviour is often cited as the primary contributing factor to road accidents, where over 90% of all crashes are attributed to ‘human error’. This implicitly attributes accidents to individual fault, suggesting that such instances could be mitigated by appropriate behaviours. This perspective has also fuelled enthusiasm for (semi-)automated vehicles. However, this is a limited vision for at least two reasons. First, most road users strive to avoid road accidents. Second, fatalities continue to persist with the use of (semi-)automated vehicles and it remains unclear how this will change with increased adoption, if at all. Conversely, modern perspectives to human behaviour suggest that ‘human error’ is a product of its whole setting, making fundamental the study of the relationship between the individual and its working environment. Therefore, a suitable vehicle should enable drivers to act with minimal margin for unintended error with the final goal to design complete human-centred traffic systems. Even if automation can mitigate for driving-related risks, it will present challenges that can only be anticipated by first understanding the cognitive mechanisms that underlie our ability to perform in road traffic systems. To this aim, it is vital that we possess better tools to understand, measure and monitor human behaviour and the corresponding cerebral activity across diverse road scenarios, including those that do not generate overt behaviour.
The emerging field of Neuroergonomics employs unobtrusive methods to understand how the individual responds to its environment before generating appropriate responses. More importantly, it can also explain why responses might not be generated in the first place. Nowadays, both commercial and custom made portable and wearable devices allow to measure behaviour and neurophysiological activity, such as eye tracking, electroencephalography (EEG), functional near-infrared spectroscopy (fNIRS), electrocardiogram (ECG), galvanic skin response (GSR) and respiration, making it feasible to learn more about behavioural and neural mechanisms that underlie human perceptual, cognitive, and motor functioning in everyday traffic scenarios. Such tools can provide new knowledge about human capabilities in terms of behaviour, cognition, intention, perception, emotion, decision making, attention and cognitive workload, and aid and expand our understanding of how road users navigate complex traffic environments and negotiate with other road users. This approach is growing in importance, in the wake of increasing vehicle automation that limits explicit driving behaviour.
This Research Topic calls for submissions that cover modelling, behavioural and neurophysiological measures applied to pedestrians, cyclists, riders and drivers of conventional as well as (semi-)automated vehicles and environments. In addition, we welcome insights from basic research and other domains of vehicle systems that can contribute to the development of a safe human-centric road traffic system. Submissions can be any article type that covers neuroscientific methods and techniques as well as behavioural and neuroimaging analysis approaches to investigate cognitive mechanisms in actively behaving road users, either in virtual reality, driving simulator or field settings.
