Geoinformation inventories are often employed as a tool for providing a comprehensive view onto the required state of traffic control infrastructure. They are especially important in road safety inspection where, in combination with georeferenced video, they enable repeatable off-line and off-site assessments as an attractive aternative to classic onsite inspection. Nevertheless, manual assessments are tedious and time-consuming even when performed off-line, and this seriously impairs the potential of the geoinformation inventory concept. This paper therefore researches a hypothesis that suitable georeferenced video processing techniques would allow reliable automation of the following operations: i) creation of the traffic inventory from the given video, and ii) assessing the video against the state in the inventory. Prominent computer vision approaches have been rigorously and systematically evaluated and the obtained results are presented. The results seem to support the hypothesis, although further work is required for a more definite answer.

The urban mobility is affected by global trends resulting in a growing passenger and freight transport demand. In order to improve the understanding of urban mobility in general, to evaluate mobility services and to quantify the overall transport system performance, it is necessary to assess urban mobility. Urban mobility assessment requires the application of methodology integrating different metrics and explicitly applying a multi-dimensional approach. Since scientific community does not define urban mobility in an unambiguous way, part of this paper is devoted to the analysis of the definition of urban mobility. This step enables better understanding of urban mobility in general, as well as understanding of the urban mobility assessment process. Usually, a three-layered approach that includes urban mobility data, indicators and indices is used for the assessment. Therefore, the aim of this paper was to perform extensive research in order to synthesize, define and organize the elements of those layers. The existing urban mobility indicators and indices have been developed for specific urban areas, taking into account local specifications, and they are not applicable in other cities. Also, the choice of urban mobility indicators is mainly related to the existence of data sources, which limits the objective and comparable assessment of the mobility of cities where such data do not exist.

The limiting conditions of traffic in cities, together with the complex and dynamic traffic flows, require an efficient and systematic management and information provision for the traffic participants, with the goal to achieve better utilisation of traffic resources and preserve sustainable mobility. In that context, it is important to identify the traffic flow location features, which requires data and information. This paper presents the application of mobile vehicles for the collection of real time traffic flow data. Such data have become an important source of traffic data, since they can be collected in a simple and cost-efficient way, enabling higher coverage than the conventional approaches, despite the reliability issues. The term referring to that type of data collection, commonly used in scientific and professional literature is FCD (Floating Car Data) and “Probe vehicle”. The efficiency presentation of applying this extensive data source for retrieving necessary parameters and information related to the achievement of sustainable mobility is the final objective of this paper. A description of modern technologies that serve as a basis for probe vehicle data collection has been provided: a geographical information system (GIS), global navigation satellite system (GNSS) and related wireless communication. Within the key technologies review, the development possibilities of data collection by mobile sensors have also been presented.

There is a small number of empirical modelling study cases available that are related to the calculation of variant solutions efficiency from the aspect of sustainable mobility in the urban areas. In practice, it is often necessary - especially when it comes to the urban transport network - to evaluate the solutions for traffic flow organisation and routing, in order to implement the one(s) with the maximum potential to reduce the possibility of congestion during peak travelling periods i.e. during transport network peak load. The paper presents an approach to the aforementioned problem by the application of the transport system efficiency analysis. The aspect of traffic flow organisation and routing efficiency in variant solutions is clarified through the analysis model development, built on the premises of Data Envelopment Analysis (DEA) method and the principles of unnecessary traffic flow intersections (TFI) theory. The proposed model defines the efficiency limit for data attributed to variant solutions, based on the calculation of the optimal TFI model and the possibilities of DEA method that include comparison and definition of relative routing efficiency for every optional traffic flow against the efficiency limit (optimal model) in order to calculate relative efficiency in relation to other solutions.

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