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.
Highlights
The sustainable mobility of the urban population is an important and integrated part of social and economic life, directly affecting the economy and life quality, especially in large agglomerations
The defined goal of research was to establish a process of the passenger urban mobility estimate as a quantitative measure of the process of urban migrations caused by socioeconomic activities, one which is in the function of determining a new urban mobility estimation index
The result is a system that permits the usage of well-known neural network learning algorithms, ones that cannot be used in fuzzy logic systems, while at the same preserving the possibility of using fuzzy logic
Summary
The sustainable mobility of the urban population is an important and integrated part of social and economic life, directly affecting the economy and life quality, especially in large agglomerations. Understanding of key urban mobility features has an extremely important role from the perspective of sustainable urban transport organization and development, in line with the objectives of reducing traffic congestions, mitigating negative environmental and health impacts, and achieving transport-related time and cost savings. This research paper proposes a new approach to urban mobility estimation based on the data in the recorded telecommunication activities of the public mobile communication network users. The research objective is to define a model for estimating the urban mobility of the population as a quantitative parameter derived from the data on the recorded telecommunication activities of the public mobile communication network users (represented by the call data records, CDR), and to define a new index for the urban mobility estimation
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