The aim of this article is to improve road safety. Specifically, it deals with the development of a mathematical model that will more accurately define the severity of a defect in a road restraint system. Currently, that evaluation is based only on the subjective perception of individual safety auditors. The mathematical model was developed based on the principle of Bayesian statistics. The determination of the specific risk was made by comparing the results of the model for two datasets. In the first case, the model was based on accident data correlated with recorded defects in road restraint systems. In the second case, the dataset represented accident events with crash barriers where no defect was identified. Based on the comparison, a total of 64 risk combinations were identified. The mathematical model confirmed 26 combinations (41% of all selected combinations of the defect levels of the crash barriers). Although not even half of the identified combinations were confirmed, more than 90% of all correlated records are found in these exposures of confirmed combinations. The verification was able to clearly define the risk of safety defects and thus brings potential accuracy to subsequent decision-making related to the repair of road restraint systems.

This study examines the possibilities of using hybrid data collection methods based on photogrammetric and LiDAR imaging for documenting traffic accident sites. The evaluation was performed with an iPhone 15 Pro and a viDoc GNSS receiver. Comparative measurements were made against instruments with higher accuracy. The test scenarios included measuring errors along a 25 m line and scanning a larger traffic area. Measurements were conducted under limiting conditions on a homogeneous surface without terrain irregularities or objects. The results show that although hybrid scanning cannot fully replace traditional surveying instruments, it provides accurate results for documenting traffic accident sites. The analysis additionally revealed an almost linear spread of errors on homogeneous asphalt surfaces. Moreover, it was confirmed that the use of a GNSS receiver and control points has a significant impact on the quality of the data. Such a comprehensive assessment of surface homogeneity has not been tested yet. To achieve accuracy, it is recommended to use a scanning mode based on at least 90% image overlap with RTK GNSS. The relative error rate on a linear section ranged from 0.5 to 1.0%, which corresponds to an error of up to 5 cm over a 5 m section. When evaluating a larger area using hybrid data collection, 93.38% of the points had an error below 10 cm, with a mean deviation of 6.2 cm. These findings expand current knowledge and define practical device settings and operational limits for the use of hybrid mobile scanning.

The primary objective of this article is to determine and subsequently verify the severity of a traffic accident caused by a collision with a fixed obstacle located in rural area sections along international roads in the Czech Republic. The aim is to create a unified assessment tool of fixed obstacles along roads. In this way, it is possible to determine in advance the level of risk of fixed obstacles along roads before traffic accidents could occur at these locations. The work is based on the assumption that the severity level of fixed obstacles in road traffic is determined by the product of the probability of hitting the object and the severity of the consequences. On the basis of these parameters, 54 specific combinations of fixed obstacles and surrounding terrain are determined, to which the specific severity of the combination is assigned in relation to the potential impact on the health of the vehicle occupants. Subsequently, a hypothesis is established that confirms or refutes, in a clear and unified manner, the initial, subjective views on the possible consequences of a traffic accident related to a fixed-obstacle impact. The verification of the hypothesis is carried out using a statistical apparatus based on the principles of conditional probability on 280 traffic accidents related to hitting a fixed obstacle. The proposed procedure verified 36 out of 54 (almost 67%) individual combinations of fixed obstacles and surrounding terrain. It was determined that there were 13 combinations with a high risk, where there is a significant probability of serious injury to occupants; 6 combinations with a moderate severity of injury to occupants; 3 cases with a low severity; and 14 cases where it was shown that the impact with a fixed obstacle was most probably not going to result in personal injury but only in material damage to the vehicle. The results of this research, which applies a unified approach to the risk analysis of fixed obstacles, will systematically improve the level of traffic safety. This primarily means preventing accidents with fixed obstacles, saving lives and reducing economic losses.