A special element of road safety research is accidents at the interface of the road and rail system. Due to their low share in the total number of incidents, they are not a popular subject of analyses but rather an element of collective studies, whereas the specificity of the road–rail accidents requires a separate characteristic, allowing, on the one hand, to categorize these types of incidents, and on the other, to specify the factors that affect them, along with an assessment of the strength of this impact. It is important to include in such analyses all potential predictors, both qualitative and quantitative. Moreover, the literature considers most often a number of accidents while, according to the authors, it does not fully reflect the scale of the danger. A better evaluation would be the victim’s degree of injury. Therefore, the purpose of this article is to assess the likelihood of occurrence of various effects of road–rail accidents in the aspect of selected factors. Due to the ordinal form of the dependent variable, the classification trees method was used. The results obtained not only allow the characterization and assessment of the danger but also constitute guidelines for taking preventive actions.

Cycling safety management is particularly important due to the increasing use of this mode of transport and increasing car traffic flows. Cyclists—travelling on roadways or sharing the space with pedestrians—are exposed to considerable risks for their safety, as well as for the safety of other road users. Comprehensive and effective management of bicycle traffic safety is therefore essential for the protection of this group of road users. The article presents procedures, the implementation of which is aimed at increasing the safety of cyclists and effective implementation of measures to achieve that. The analyses aimed at the selection of appropriate measures and solutions to improve safety of cyclists in the road traffic have been presented. The procedures include: Selection of devices and measures, risk assessment and estimation of the potential to reduce the risk of collisions/accidents involving cyclists, selection of investment measures and devices reducing the risk of cyclists and other road users, implementation methods and monitoring of selected measures reducing the risk of collisions/accidents involving cyclists. The proposals contained in the article fill in the gap existing in this area of knowledge. The analyses conducted and the presented results show that the construction of infrastructure for cyclists is not the only way to improve the safety of this group of road users. Due to the high costs and deficit of the road surface in the road-street cross-section—other forms of measures in this area should also be analyzed.

The problem of poor quality of traffic accident data assembled in national databases has been addressed in European project InDeV. Vulnerable road users (pedestrians, cyclists, motorcyclists and moped riders) are especially affected by underreporting of accidents and misreporting of injury severity. Analyses of data from the European CARE database shows differences between countries in accident number trends as well as in fatality and injury rates which are difficult to explain. A survey of InDeV project partners from 7 EU countries helped to identify differences in their countries in accident and injury definitions as well as in reporting and data checking procedures. Measures to improve the quality of accident data are proposed such as including pedestrian falls in accident statistics, precisely defining minimum injury and combining police accident records with hospital data.

Maria Dąbrowska Loranc, Przemysław Skoczyński, Anna Zielińska Badania Obserwatorium Polityki Miejskiej https://doi.org/10.51733/opm.2023.02 Raport w punktach • W maju i czerwcu 2021 r. oraz w styczniu 2022 r. wprowadzono istotne zmiany w Prawie o ruchu drogowym (PoRD) i w Kodeksie wykroczeń. Dodano nowe kategorie pojazdów, które dotychczas nie były opisane w regulacjach prawnych: […]

This research examines the risk factors that influence injury severity in individual motorcycle accidents, utilising a dataset of 5253 incidents. Five machine learning algorithms—multinomial logistic regression, classification trees, random forests, XGBoost, and neural networks—were used to classify the results into three groups: Death (13.48%), Injury (80.14%), and No injury (6.38%). In all models, passenger presence was the most important predictor of injury. Motorcycle accidents involving passengers do not always have more serious consequences for several overlapping reasons. On the one hand, a motorcycle with a passenger has a significantly higher mass, which increases the braking distance and kinetic energy at the moment of collision, hindering quick defensive manoeuvres, cornering, and reactions to sudden hazards. Often, the rider also refrains from sudden movements to prevent the passenger from losing their balance. In the case of single-rider motorcycle accidents on roadways, approximately 5% of those involved with a passenger were fatalities, while approximately 48% were uninjured; in the case of those without a passenger, no one was uninjured. It follows from the above that the presence of a passenger increases the rider’s sense of responsibility. Other factors that significantly increased risk were single-lane carriageways, vehicle overturning, contaminated road surfaces, and collisions with complex objects, e.g., like trees. The multinomial logistic regression model had an overall accuracy of 69.2% on the test set. The Recurrent Neural Network achieved the best overall accuracy of 79.56%. Balanced accuracy, as the average between sensitivity and specificity of the RNN model for the “death” class was 68.15%, for the “injury” class—72.6%, and for the “no injury” class—96.61%. The Area Under the ROC Curve of the Recurrent Neural Networks model for “no injury” was 0.97, indicating it was very good at distinguishing between this class and the other classes. Even though it was easy to tell which cases did not involve injuries, it was still hard to tell the difference between fatal and non-fatal injuries in all models. The results support interventions tailored to specific situations, such as improved road lighting and speed control in rural areas, as well as helmet enforcement and safety measures at intersections in cities.

In Poland, the risk of road safety is still one of the highest in the EU and, despite a 36% decrease in the number of fatalities, requires further intensive work to reduce the risk associated with travelling on the roads. In 2021, the National Road Safety Program for 2022-2030 was announced, which should be followed by regional programs. The article presents a set of information needed to diagnose traffic safety at the province level. Using the example of the Masovian Province, basic statistical data, road safety trends, basic risk indicators, the structure of accidents and fatalities from various perspectives were presented. In addition, the costs of accidents and collisions that occurred in the Masovian Province were shown. Based on the analyses conducted, the characteristic features and main road safety problems in the province were identified. The analyses and their results presented show that the annual costs of all road accidents in the Masovian Province, although decreasing, still significantly exceed the expenses planned in the province budget for a given year. Therefore, reducing the number of road incidents, especially accidents, and their consequences may bring significant savings to the province budget.