The aim of this work is to describe pedestrian-driver encounters, communication, and decision strategies at marked but unsignalised crossings in urban areas in the Czech Republic and the ways in which the parties involved experience and handle these encounters. A mixed-methods design was used, consisting of focus groups with pedestrians and drivers regarding their subjective views of the situations, on-site observations, camera recordings, speed measurements, the measurement of car and pedestrian densities, and brief on-site interviews with pedestrians. In close correspondence with the literature, our study revealed that the most relevant predictors of pedestrians' and drivers' behaviour at crossings were the densities of car traffic and pedestrian flows and car speed. The factors which influenced pedestrians' wait/go behaviour were: car speed, the distance of the car from the crossing, traffic density, whether there were cars approaching from both directions, various signs given by the driver (eye contact, waving a hand, flashing their lights), and the presence of other pedestrians. The factors influencing drivers' yield/go behaviour were: speed, traffic density, the number of pedestrians waiting to cross, and pedestrians being distracted. A great proportion of drivers (36%) failed to yield to pedestrians at marked crossings. The probability of conflict situations increased with cars travelling at a higher speed, higher traffic density, and pedestrians being distracted by a different activity while crossing. The findings of this study can add to the existing literature by helping to provide an understanding of the perception of encounter situations by the parties involved and the motives lying behind certain aspects of behaviour associated with these encounters. This seems necessary in order to develop suggestions for improvements. For instance, the infrastructure near pedestrian crossings should be designed in such a way as to take proper account of pedestrians' needs to feel safe and comfortable, as well as ensuring their objective safety. Thus, improvements should include measures aimed at reducing the speed of approaching vehicles (e.g. humps, speed cushions, elevated crossings, early yield bars, and narrow lanes), as this would enhance yielding by motor vehicles. Other measures that specifically rely on the subjective perception of different situations by the parties involved include the education and training of drivers, the aim of which is to promote their understanding and appreciation of pedestrians' needs and motives.

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Purpose 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. Methods 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. Results 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. Conclusions 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.

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.

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