Within the activities of planning, organizing, or regulating traffic, a considerable amount of various traffic data is actively used. For responsible data-based decision-making, the quality of the utilized data is crucial. However, defining the specifics of this quality and establishing procedures for its control is often ambiguous. The primary objective of the research was to review methods for ensuring or managing data quality within the transportation environment. Building on the collected information, a practical data governance approach was delineated to be applied to specific transportation data. Simultaneously, data from detectors and floating vehicles on the highway network in the Czech Republic were analyzed for the same reason. The results show that the chosen data governance approaches are applicable to transportation data, even in the task of evaluating data quality in the detail of individual dimensions. In the context of semantic data quality control, it is necessary to explore additional suitable tools, such as the use of statistical models, to reliably distinguish real errors or otherwise reduced data quality from genuinely truthful values, such as traffic conditions.

Floating car data (FCD) is a beneficial consequence of the modern telematics technologies in the logistics and automotive industry, and can thus be an additional source of transportation data about current traffic flows on the road network. There is a state-provided free source of this data available in the Czech Republic, which is relatively new and gradually being introduced for use by the public and private sectors. This data source appears to be very promising for nationwide coverage; however, due to its novelty, it is necessary and advisable to investigate its qualitative parameters and assess whether it actually adequately characterizes vehicle traffic flows. The present paper deals with the characteristics and quality of processed FCD outputs before and during the covid-19 pandemic, for the possibility of capturing and comparing significant changes in the behaviour of road users. The paper describes the impact of the associated pandemic measures on traffic in the country in general, which can be detected during FCD processing, as well as the impact on the quality of FCDs as such. It also tests the hypothesis that although the quality of the data has been reduced as a result of the pandemic, the data still have sufficient predictive value. The paper describes the specifics of the data in the spatial and temporal domain analyzed and makes recommendations for future work for use in models and predictions.

The aim of the article is to present a comprehensive procedure for processing and evaluating directional data from vehicle license plates, focusing on the specific challenges of areas that are sparsely or not at all equipped with permanently located standard license plate recognition systems. This remains a current issue, especially in smaller towns; it leads to the implementation of short-term directional traffic surveys, often using inexpensive measurement devices, in order to obtain directional traffic data. In this research, a procedure for evaluating license plate recognition data is proposed with a primary focus on its simple adaptability and automation for any subsequent use. The data sources considered are primarily the above-mentioned traffic surveys; however, the proposed evaluation procedure is theoretically transferable to any off-line data obtained from license plate recognition systems. Identifying potential inaccuracies in the data is also an integral part of the evaluation process. The design of the proposed procedure follows the Checkland soft systems methodology and the functionality of the resulting procedure was validated through a case study of a directional survey in Prague. The proposed procedure contributes to greater accuracy of the conclusions drawn from evaluated traffic engineering parameters under non-ideal, but common conditions of smaller cities, not only in the Czech Republic.

This paper provides an overview of the current challenges that occur within the design of the urban mobility concept and urban development concept. These challenges are discussed in view of the unique ELABORATOR project, which brings together different approaches and measures in a total of 12 European cities to improve micro mobility and sustainability and prove a concept toward climate-neutral cities. The main goal of the paper is to clearly describe the current state of mobility in the city of Liberec in the Rochlice housing estate area with the main objective focused on parking availability and identification of undesirable phenomena (incorrect parking, exhausted parking capacity, difficult passage for rescue services etc.). Therefore, the definition of ongoing problems is described from default to design and propose strategic interventions towards efficient parking supporting local mobility needs. Parallelly, the evaluation methodology is defined according to the requirements of strategically defined goals in sustainable urban mobility plans and the goals of the project. The proposed methodology reflects in situ measurement, identification of large-scale impacts based on quantitative analysis, and qualitative feedback collection from public events and applied interviews with city residents, and last but not least, the use of shared experiences of cities within the ELABORATOR project. This complex solution is defined to improve parking availability and to measure the real impact of proposed interventions on traffic on dedicated housing estates.

In the context of nature protection, there is an effort to regulate individual car traffic in protected areas. In the framework of the research, a pilot testing of a vehicle detection and identification system in the Krkonoše National Park was carried out using two selected technologies (license plate recognition and Bluetooth token detection). The research was carried out under conditions of poorer availability of mobile signal for transmission of measured data, lack of electrical power supply, and in challenging climatic conditions in the mountains. The main objective was to verify the applicability and limits of the mentioned technologies under these difficult conditions. For this purpose, two test sites were built: a fixed and a mobile point. Testing at both points was carried out using two basic methods, namely online through continuous data collection from the detectors and on-site through a local survey during the summer of 2022. The parameters evaluated were the reliability of the vehicle identification itself and the reliability of the operation of the individual detection subsystems and the tested system as a whole. The results show that the license plate recognition system using two cameras for the checkpoint shows a high recognition reliability, but it is reduced for some types of vehicles (especially motorcycles and four-wheelers). At the same time, this technology is demanding on energy resources. Detection using a Bluetooth scanner has proven to be highly reliable up to 50 km/h. A reliable power supply is necessary to achieve high reliability, which was a problem at the mobile point. Evaluation of images from cameras with motion detection showed the limits of this technology, which increased with increasing vehicle speed. The system can be used to detect traffic in protected areas, taking into account the limits specified in this article.