People
doc. Ing. Pavel Hrubeš, Ph.D.

2024, Transportation Research Procedia, Amsterdam, Elsevier B.V.), p. 619-626), ISSN 2352-1465

This paper presents a method for assessing the quality of floating car data and estimating emissions of the road network. The authors use a fundamental diagram from real probe vehicles to determine the categorization of the road network. These data are complemented by the widely used emission factors of the COPERT model to investigate the quality of the floating vehicle data to use them for the determination of emissions on individual road classes with a detailed spatiotemporal resolution. From the same data, an estimate of the emission rate of the categories is determined and it is assessed whether similar differences are exhibited. The hypothesis is that the quality of data is quite sufficient on highways and high-class roads, but unusable and insufficient on low-class roads. The results show that differences in emission estimates can be observed for the road categories of the highway network and low-class road network. For some pollutants, the urban network can also be identified. The offered categorization could lead to further possibilities of using floating vehicle data, such as the assumption of the possibility to detect atypical traffic phenomena (traffic jams, accidents, or impassable roads due to bad weather conditions).

2024, Neural Network World, 34 (4), p. 203-218), ISSN 1210-0552

The primary objective of the presented research is to enhance an existing data quality control application by integrating advanced anomaly detection mechanisms based on generalized additive models. This approach targets time- series traffic data, where traditional methods may fall short in identifying complex, non-linear patterns of anomalies. In collaboration with Simplity s.r.o., we are extending their current data quality assessment tool to incorporate generalized additive models, providing a more robust and dynamic solution for monitoring and ensuring the reliability of traffic datasets. The integration of these models aims to improve the accuracy of anomaly detection, leading to more effective data management in transport systems and contributing to higher standards of data quality in the field of traffic informatics.

2024, PROMET - Traffic&Transportation, 36 (6), p. 988-1005), ISSN 1848-4069

This paper attempts to determine the role of street lighting in the spatial clustering of night-time crashes involving pedestrians in the Republic of Croatia. Five-year (2018–2022) night-time pedestrian crash data were used in conditions with and without street lighting. First, distance-based statistical methods were used to assess the spatial clustering and deviations from complete spatial randomness (CRS) of the crash patterns. Second, the global Moran’s I analysis was conducted to investigate a degree of spatial autocorrelation of the annual crash counts aggregated in 21 counties of Croatia. Finally, the local indicators of spatial association (LISA) were used to identify the locations of the crash count hotspots. The results of the ANND analysis confirm a significant clustering of crashes for both street lighting conditions. However, different global Moran’s I values for both conditions were obtained with a high and statistically significant positive value for the crash counts without street lighting. Local Moran's I analysis reveals that the High-High (H-H) county clusters are located in coastal regions of Croatia, while the Low-Low (L-L) county clusters appear in the East continental part, next to Slavonia. The results suggest that inadequate lighting conditions have an impact on the clustering of pedestrian crashes at night.

2024

Zpráva o činnosti ČVUT FD v roce 2023 při řešení projektu Nástroje kvality dat pro zabezpečení systémové spolehlivosti dopravně informačních center.

2024, 2024 Smart City Symposium Prague - IEEE PROCEEDINGS, New York, IEEE Press), ISBN 979-8-3503-6096-7, ISSN 2831-5618

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.

2023, Neural Network World, 33 (5), p. 375-396), ISSN 1210-0552

Night-time light (NTL) radiance has a great potential in analyses of dynamic changes in patterns of human activities, and socio-economic and demographic factors. However, most of those analyses are focused on factors at global scales such as the population size, gross domestic product, electric power consumption, fossil fuel carbon dioxide emission etc. In this study we investigate the relationships between three urban lighting indicators and monthly averaged NTL radiance obtained from NASA’s Black Marble monthly NTL composites for 4 study areas in the Czech Republic at local scale. The Pearson correlation analysis was used to identify a strength of the correlations between the indicators and radiance at near-nadir for two different snow conditions. The results from the correlation show that radiance has a strong positive correlation with the number of streetlighting points and their total nominal power, while for the average mast height there were observed moderate correlation coefficients. However, the areas with larger scales have higher correlation coefficients. Moreover, we found that the correlation coefficients are higher for snow-covered condition radiances. Generalized linear (GL) regression analysis was used to examine an association between the radiance and selected indicators. Owing to the excess zeros and overdispersion in the data, the zero-inflated regression performs better than the GL regression. Results from the regression analysis evince a statistically significant relationship between the radiance and selected indicators.

2023, European Transport (93), ISSN 1825-3997

Data from floating vehicles is a modern technology and can be another source of data. There is a free data source available in the Czech Republic, which is relatively new. The addressed source of data from floating vehicles covers the whole Czech Republic, which is a promising source for future use e.g. in transport planning in logistics, estimation of travel times and other related issues. For this reason, it is appropriate to examine the qualitative parameters of the data to see if they characterize the traffic stream. The present paper deals with the size of the processed data. Furthermore, the paper compares the data quality and coverage. January data for four subsequent years was used. The period of the COVID19 pandemic, when traffic declined, was included. Finally, data from selected highways are compared and the period covered is evaluated.

2023, 2023 Smart City Symposium Prague, New York, IEEE Press), ISBN 979-8-3503-2162-3, ISSN 2691-3666

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.

2021, 2021 Smart City Symposium Prague, Piscataway, IEEE Signal Processing Society), p. 1-6), ISBN 9780738131580

Modern telematics systems are based on data collected from real operation. The article works with a new source of traffic data, which is freely available to the public. Linking traffic data with spatio-temporal significance also allows us to examine data from the perspective of user behavior. From the principle of data collection, the data already have their specific assumed behaviors, which are described in the article. It is desirable to further investigate these behaviors, to what extent they are affected and whether they can be considered as parameters of the entire traffic flow

2021, 27th ITS World Congress, Brussels, ERTICO - ITS Europe), p. 1702-1713)

In the Czech Republic, there is a new, freely available source of data on the speeds of traffic flows on the road network, based on the movement of floating vehicles. This opens up new possibilities for community and commercial use, as well as research, especially in assessing the qualitative characteristics of this resource and the possibilities and areas of application of its use. It is a unique source of traffic data covering the entire country and it is necessary to examine its reliability in time and space resolution. In the future, this source could be used directly to influence and manage the optimization of the transport network operation, so it is necessary to subject it to a detailed qualitative examination. In addition to these qualitative analyzes, the paper also deals with similar research and the presentation of the user interface. Finally, possible uses and other directions of research are discussed.

2021, 2021 The 9th International Conference on Information Technology: IoT and Smart City (ICIT 2021), New York, ACM), ISBN 978-1-4503-8497-1

Today, traffic management is based on traffic data, which must be high quality and reliable. The article deals with a new data source that is available in the Czech Republic. Thanks to this dataset, it is possible to get an overview of a wide road network throughout the whole area of the country. The authors use a broader view of the road network to study the behavior of drivers of floating vehicles in an accident on the main road. The high data coverage promises the ability to monitor traffic spills in the event of an emergency. These data can be used in the future to improve the overview of the current state of traffic and road management.

2021, Prostorové služby pro Smart City a Smart Region, Ostrava, VYSOKÁ ŠKOLA BÁŇSKÁ-TECHNICKÁ UNIVERZITA OSTRAVA), ISBN 978-80-248-4508-1, ISSN 1213-239X

The modern trend in the "Smart" areas is the collection of data to influence, control, optimize or predict general processes, including transport. In the Czech Republic, model data on the speed of road traffic flow based on the movement of floating vehicles, as it is called, have been available since last year. It is a new source of data on the traffic situation with nationwide coverage. These data are therefore published not only on traditional main roads but also on roads that have not been and are not equipped with any detection technology. Thanks to this model, it is possible to monitor and analyze the speed of the traffic flow and its development over time for a large part of the transport network throughout the Czech Republic. The article deals with the use of this data, their spatial significance, and processing in GIS.

2020, GARI INTERNATIONAL JOURNAL OF MULTIDISCIPLINARY RESEARCH, Colombo, GARI Publisher), p. 86-93), ISBN 978-955-7153-00-1, ISSN 2659-2193

Progress in the option of transport data collection allows users to collect data using floating vehicles. This data provides real-time information about the road network. In the Czech Republic, these data were published in a pilot project last year. The article uses this new data source. Data can be spatially displayed using GIS software. Analysis options can be used and drivers' choice when the main road is closed can be detected.

2020

2020

2020, Young Transportation Engineers Conference 2020, Praha, Fakulta dopravní), p. 119-125), ISBN 978-80-01-06793-2

Digitization of the transport environment and the use of new data sources is a much-discussed topic today. FCD (Floating Car Data) systems, so-called floating vehicles, make it possible to obtain data of traffic parameters directly from the road network without the need to install stationary sensors. The article deals with the use of this new data source in the Czech Republic, financed from public sources, and made available by the Directorate of Roads and Motorways. This data can be displayed in the road network model using geographic information programs and further analyzed.

2019, 2019 Smart City Symposium Prague, New York, IEEE Press), p. 1-5), ISBN 978-1-7281-0497-3

This paper presents a new approach to pavement rehabilitation using a 3D measuring. The proposed methodology of the pavement rehabilitation overcomes the limitation of the traditional methods of the pavement rehabilitation which cannot achieved the required accuracy. The 3D measuring technology eliminates human faults and improves the total quality of the pavement rehabilitation. The pavement rehabilitation is performed in the concept of Industry 4.0 which is part of Smart City owing to the 3D measuring.

2018, Proceedings of 36th International Communications Satellite Systems Conference (ICSSC), FGM Events), ISSN 2573-6124

The basic concept of Industry 4.0 is virtualization of reality - creating a digital image of real world and optimizing and planning processes in this virtual environment. The aim is to find the best solutions in a broad relationship with other processes and their realization in the real world. In the construction industry, Industry 4.0 is only at the beginning phases of utilization, especially the area of a highwayroad reconstruction, which provides an extremely high potential for process optimization. This was confirmed, for example, in the ASFALT project: Advance Galileo Navigation System for ASPHALT's fleet machines (ID: 247976, Funded under: FP7-TRANSPORT). This paper introduces the methodology of complex robotic and automation process of the pavement repair according to the industry 4.0 principles, which uses Exact Street DNA navigation, patented hybrid GNSS based technology for precise millimetre navigation of road milling machines. The DNA navigation achieves millimetre height accuracy using an inexpensive GNSS receivers. The pavement repair process often takes place in urban canyons areas, which is why the 3D data is enhanced by GNSS Galileo and EGNOS.