No abstract

Urban mobility of a population is usually estimated within procedures that focus on specific domains, using limited datasets, indicators, and indices related to the targeted subsets of the urban population. This paper proposes a new approach to urban mobility estimation, based on the telecommunication activities within the public mobile telecommunication networks. The urban mobility indicators in this research are generated from a database of mobile phone users call data records and are integrated into the urban mobility index of the population based on the model defined through the adaptive neuro-fuzzy inference system (ANFIS). The following has been considered in the process: an initial fuzzy inference system, model learning, model quality control, limitations, errors, and deficiencies. The model is practically applied in the programming environment, on a set of real word data. The research results prove the following hypothesis set in this paper: the urban mobility of inhabitants in a specific timeframe, can be described with an urban mobility index based on the data on the recorded telecommunication activities of the public mobile communication network users.

The transport system is sensitive to external influences generated by various economic, social and environmental changes. The society and the environment are changing extremely fast, resulting in the need for rapid adjustment of the transport system. Traffic system management, especially in urban areas, is a dynamic process, which is why transport planners are in need of a proven and validated methodology for fast and efficient transport data collection, fusion and analytics that will be used in sustainable urban mobility policy creation. The paper presents a development of a methodology in data rich reality that combines traditional and novel data science approach for transport system analysis and planning. The result is overall process consisting of 150 steps from first desktop research to final solution development. It enables urban mobility stakeholders to identify transport problems, analyze the urban mobility situation and to propose dedicated measures for sustainable urban mobility strengthening. The methodology is based on a big data research and analysis on anonymized big data sets originating from mobile telecommunication network, where the extraction of mobility data from the big dataset is the most innovative part of the proposed process. The extracted mobility data were validated through a “conventional” field research. The methodology was, for additional testing, applied in a pilot study, performed in the City of Rijeka in Croatia. It resulted in a set of alternative measures for modal shift from passenger cars to sustainable mobility modes, that were validated by the local public and urban mobility stakeholders.

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 paper presents the results of research in tourism as one of the most important factors in the public passenger transport demand. The research has been carried out for the requirements of creating a Tourism Satellite Account (TSA) for the Republic of Croatia for 2016. Traffic and tourism, as strategic economic activities of the Republic of Croatia, have the characteristics of complex and dynamic systems, mutually conditioned by the guidelines of the demand and supply chain of tourist product values. Therefore, the paper is oriented towards the analysis of the significance of tourism for public road passenger transport in the Republic of Croatia. During 2016, road intercity passenger transport carried 50.4 million passengers, out of which 98 percent in domestic and 2 percent in international transport. Passenger road transportation is marked by mild seasonal oscillations, with the summer period marked by the lowest level of demand, and the period from January to March by the largest number of passengers. The provision of public road transportation services in 2016 realised a revenue of 1.8 billion kuna for 433 business subjects registered in this activity. The trends indicate an increase in the number of travelled kilometres by buses with passengers.