Driver fatigue and stress significantly contribute to higher number of car accidents worldwide. Although, different detection approaches have been already commercialized and used by car producers (and third party companies), research activities in this field are still needed in order to increase the reliability of these alert systems. Also, in the context of automated driving, the driver mental state assessment will be an important part of cars in future. This paper presents state-of-the-art review of different approaches for driver fatigue and stress detection and evaluation. We describe in details various signals (biological, car and video) and derived features used for these tasks and we discuss their relevance and advantages. In order to make this review complete, we also describe different datasets, acquisition systems and experiment scenarios.

Considering the human contribution to car crashes, it seems necessary to make a distinction between different forms of aberrant driver behaviour and its different psychological origins. The aim of the present study was to determine the factors that affect driving behaviour, to prepare a factor model, to identify the role of age, gender, kilometres driven per year, and social status, and to examine the relationship between self-reported driver behaviour in DBQ and self-reported accident involvement and offences among Czech drivers. For this purpose the original 50-item version of DBQ was translated and adjusted to the Czech driver population. A total of 2,684 Czech drivers participated in the study, 1,791 men and 893 women. Responses to the 50 items were submitted to a principal components analysis with a varimax rotation. Our research confirmed a three-factor approach as the most appropriate for the interpretation of data. In our case, the three-factor solution can provide an explanation for 31.75 % of the total variance. While Factor 1, “Dangerous Violations”, and Factor 2, “Dangerous Errors”, are consistent with the findings of other authors, Factor 3, interpreted as “Not Paying Attention to Driving, Straying, and Loss of Orientation”, has been identified as a new one. In addition, predictors of (driver behaviour) factors defining the driver groups prone to engaging in specific types of driving behaviour are further discussed. Practical implications for the education, training, and assessment of drivers, preventive measures, and on-board assistance systems are addressed.

Electric scooters (e-scooters) have become a popular phenomenon internationally; however, their use has raised concerns about pedestrian safety. This study describes the possible effects of the emergence of e-scooters on pedestrians. We focus on the interaction, conflicts, crashes, and attitudes between pedestrians and e-scooter riders and pedestrians' perceived safety in the presence of e-scooters. Data were collected from e-scooter riders and non-riders (n = 3385) through an online survey in Australia, Belgium, the Czech Republic, Norway, and Sweden. Around 20–30% of e-scooter riders rode on sidewalks, whether it is allowed or not. Non-riders of e-scooters tended to report that riding an e-scooter is rather dangerous. Pedestrians, except Australian ones, perceived e-scooter riders (and e-scooter operation) as annoying. Half of the e-scooter riders had experienced a near miss at some point in the past and more than 50% of these near misses included another road user. Up to 10% of the e-scooter riders from all five countries reported having experienced a crash. On the basis of these findings, we believe that the most relevant suggestions for the implications in sustainable (urban) mobility involve separating e-scooter riders and pedestrians.

The empirical research on the COVID-19 epidemic’s consequences suggests a major drop in human mobility and a significant shift in travel patterns across all forms of transportation. We can observe a shift from public transport and an increase in car use, and in some cases also increase of cycling and (less often) walking. Furthermore, it seems that micromobility and, more generally, environmentally friendly and comanaged mobility (including shared services), are gaining ground. In previous research, much attention was paid to the mode choice preferences during lockdown, or early stages of the SARS-CoV-2 situation. The blind spot, and aim of this work, is how long observed changes in mode choice last and when or if we can expect the mode choice to shift back to the situation before the SARS-CoV-2 episodes. The research sample consisted of 636 cases; in total, 10 countries contributed to the sample examined in this study. The data were collected in two phases: the first in the spring of 2020 and the second in the fall of the same year. Results showed that respondents reduced mobility by car, local public transport and walking, but not bicycling during the lockdown, compared to the time before the pandemic started. When the easing came, respondents assessed their own use of the car and walking as almost back to normal. They also reported an increase in the use of public transport, but not reaching the level prior the pandemic by far. It seems that cycling was affected least by the pandemic; use of a bicycle hardly changed at all. As for the implication of our study, it is evident that special attention and actions will be needed to bring citizens back to public transport, as it seems that the impact of the pandemic on public transport use will last much longer than the pandemic itself.