Car-motorcycle accidents have been reported higher in recent years in Hungary due to increasing number of motorbikes on road. Car-motorcycle collisions mostly lead to fatal and seriously injured accidents mainly due to the vulnerability of motorcyclists and other related factors. The crash investigation studies aim to analyze the main contributing factors that cause fatal road accidents and injury outcomes. The main goal of this study is to evaluate and compare the contributing factors to car-motorcycle accidents in Budapest city by using a microsimulation tool. The procedure utilized the statistical analysis and data sampling to categorize car-motorcycle accidents by dominant accident types based on collision configurations. The police report is used as a data source for designated accidents and simulation models are plotted according to scale (M 1:200). The simulation crash study results observed the main contributing factors to car-motorcycle accidents such as driver behavior, rider behavior and view obstruction. The comprehensive in-depth investigation also found that most of the car drivers and riders could not perform collision avoidance manoeuvres before the collision. This study can help the traffic safety authorities to solve road safety issues by considering the main contributing factors to car-motorcycle collisions. The study also proposes safety measures to avoid car-motorcycle accidents in future.
The results of route planning researches are monitored by logistic and automotive industries. The economic aspects of the cost saving are in the focus of the attention. An optimal route could cause time or fuel savings. An effective driving or an optimal route is a good basis to achieve an economical aim. Moreover the spread of new automotive solutions especially in case of electric cars the optimisation has particular significance regarding the limited battery storage. Additionally the autonomous car development could not be neglected. As a result the society could expect safer roads, better space usage and effective resource management. Nevertheless the requirements of users are extremely diverse, which is not negligible. Supporting these aims, in this paper the connection between the multimodal route planning and the user requirements are investigated. The examination is focused to a sensitivity analysis and a survey to evaluate the data and support the settings of a user habit effect to the final route.
In recent years, the increased frequency of inland excess water in the Carpathian Basin gets more and more attention. The authors developed a web based pilot application for disaster management, with special emphasis on inland excess water hazard management. Free and open source software was used to generate a model, and our work was based on Web GIS standards (OGC), which makes further development possible. The developed Web GIS application provides functions to support the data collection regarding channels and ditches, and on-line hydrological analysis based on OGC Web Processing Services (WPS). Hydrological analysis aims to visualize the areas potentially at risk, depending on different precipitation quantities and various values of influencing factors. In order to run the prototype a sample data set was gathered including reference maps, technical parameters and current condition of canals and ditches. The methodology of crowdsourcing can produce valuable Volunteered Geographic Information (VGI) that can fulfill the data requirements of disaster management applications. The prototype supports Crowdsourcing in the following aspects: free user access to the system’s analysis functionality, stakeholders may digitize the position of ditches, modify the status of the existing ditch system according to current conditions and add or modify parameters relevant for the analysis. The application demonstrated the usability of stakeholder generated geographic information and web processing for disaster management. The idea of integrating user-generated data into the various tasks of a disaster management agency is promising. However, maintaining data quality and standards compliance remain important issues.