Driving experiences provided by the introduction of new vehicle technologies are directly impacting the criteria for road network design. New criteria should be taken into consideration by designers, researchers and car owners in order to assure traffic safety in changed conditions that will appear with, for example, introduction of Autonomous Vehicles (AVs) in everyday traffic. In this paper, roundabout safety level is analysed on the originally developed microsimulation model in circumstances where different numbers of AVs vehicles are mixed with Conventional Vehicles (CVs). Field data about speed and traffic volumes from existing roundabouts in Croatia were used for development of the model. The simulations done with the Surrogate Safety Assessment Model (SSAM) give some relevant highlights on how the introduction of AVs could change both operational and safety parameters at roundabouts. To further explore the effects on safety of roundabouts with the introduction of different shares of AVs, hypothetical safety treatments could be tested to explore whether their effects may change, leading to the estimation of a new set of Crash Modification Factors.

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Children pedestrians make up 30% of the total number of children injured in road traffic in the EU. Research shows that children are injured more often in the urban areas, in residential areas near schools and parks, often at intersections and pedestrian crossings. In this study, children’s traffic behavior was analyzed by observation of signalized pedestrian crosswalks. According to the same methodology, the research was conducted in three cities in two countries (Enna, Italy, Osijek and Rijeka, Croatia) with different urban and traffic characteristics. A total of 900 measurements were analyzed, 300 in each of the cities at 18 pedestrian crosswalks located in an urban setting in the vicinity of primary schools. A detailed statistical analysis of the influence parameters shows that, as general influence parameters, pedestrian crosswalk length, movement in a group and the age of children can be distinguished. Factors that have proven to have a significant influence on the movement of children in two of the three cities observed are gender, supervision by adults, running and cellphone use. The result can serve as a valuable input for interventions in traffic education as well as a basis for the improvement of traffic conditions at intersections where children are regularly present.

Modeling the behavior of pedestrians is an important tool in the analysis of their behavior and consequently ensuring the safety of pedestrian traffic. Children pedestrians show specific traffic behavior which is related to cognitive development, and the parameters that affect their traffic behavior are very different. The aim of this paper is to develop a model of the children-pedestrian’s speed at a signalized pedestrian crosswalk. For the same set of data collected in the city of Osijek—Croatia, two models were developed based on neural network and multiple linear regression. In both cases the models are based on 300 data of measured children speed at signalized pedestrian crosswalks on primary city roads located near a primary school. As parameters, both models include the selected traffic infrastructure features and children’s characteristics and their movements. The models are validated on data collected on the same type of pedestrian crosswalks, using the same methodology in two other urban environments—the city of Rijeka, Croatia and Enna in Italy. It was shown that the neural network model, developed for Osijek, can be applied with sufficient reliability to the other two cities, while the multiple linear regression model is applicable with relatively satisfactory reliability only in Rijeka. A comparative analysis of the statistical indicators of reliability of these two models showed that better results are achieved by the neural network model.

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