Keeping the basic principles of sustainable development, it must be highlighted that decisions about transport safety projects must be made following expert preparation, using reliable, professional methods. A prerequisite for the cost–benefit analysis of investments is to constantly monitor the efficiency of accident forecasting models and to update these continuously. This paper presents an accident forecasting model for urban areas, which handles both the properties of the public road infrastructure and spatial dependency relations. As the aim was to model the urban environment, we focused on the road public transportation modes (bus and trolley) and the vulnerable road users (bicyclist) using shared infrastructure elements. The road accident data from 2016 to 2018 on the whole road network of Budapest, Hungary, is analyzed, focusing on road links (i.e., road segments between junctions) by applying spatial econometric statistical models. As a result of this article, we have developed a model that can be used by decision-makers as well, which is suitable for estimating the expected value of accidents, and thus for the development of the optimal sequence of appropriate road safety interventions.

On one hand, better and better databases occur through the world, however for cities a lot of important data is unavailable. On the other hand, the cities are one of the most important units, where transportation interactions ought to be analyzed. In this recent paper the order of the cities (based upon the NUTS – Nomenclature des unités territoriales statistiques classification) will be introduced, and an answer will be found for the question whether this parameter could be used as a substitution of an economic parameter.

Nowadays the spatial econometrics is became widely used in transportation sciences. In order to know which method can be used or how they should be used, the review articles give answers. In this recent paper the goal is to collect all of the methods in one article which can be used in further researches. The improvement in this article is that beside the spatial econometric methods, other necessary techniques are also introduced. With this fact a whole analysis can be applied.

This study presents a method to analyze the most critical elements of the public road system concerning outer effects which hinder the normal operation of the whole system. The surveyed public road network in Budapest, Hungary is studied as a graph: Dijkstra’s algorithm is applied to find the shortest path, and the Boykov-Kolmogorov method is used to calculate the maximum flow of the network. Those elements are identified whose damage can critically influence the operation of the network, and where the infrastructure available for rescue teams has a bottleneck. Finally, the Wilcoxon post hoc test was applied with Bonferroni correction. The tests have proven that the new method can successfully identify the critical vulnerabilities of the network to determine its weak points by considering reduced road capacities and the increased needs for transportation arising due to a disaster. This pilot study confirmed that after the elimination of the problems in statistical methods, the new framework can robustly identify those road network elements whose development is of key importance from a disaster management perspective.

The analysis on the border crossings, as the objects to decrease the separation effect, is really important for our country, to evaluate the connection of the neighbouring and other nearby countries and international economic centres with Hungary. In our country’s life the cross-border partnerships have an important role because of historical and cultural causes. In recent article, our task is to analyse changes of the cross-border traffic, with the help of the spatial econometrics. The goal is, to show the effect of five outstanding areas on the crossing traffic, and to analyse the spatial connection between them.

The level of greenhouse gas emissions is one of the most important issues today, both professionally and politically, because a lower level of greenhouse gas emission is mandatory for a sustainable economy. Besides industry and households, the transport sector is also responsible for these emissions. For this reason, it may be essential to set up a model with which the amount of CO2 emissions could be estimated or predicted. This article presents a model that examines the extent of economic development and CO2 emissions in European countries. The result is establishing a pattern requiring a longer time series. If the pattern is proven, a clear reassessment of the current relationship between economic development and environmental protection should be made.