Sustainable Urban Mobility Boost Smart Toolbox Upgrade

M. Sostaric; M. Jakovljevic; K. Vidovic; O. Lale

doi:10.4108/ew.v9i39.1193

Authors

M. Sostaric Faculty of Transport and Traffic Sciences, Zagreb, Croatia
M. Jakovljevic Faculty of Transport and Traffic Sciences, Zagreb, Croatia
K. Vidovic Ericsson Nikola Tesla d.d., Zagreb, Croatia
O. Lale Faculty of Transport and Traffic Sciences, Zagreb, Croatia

DOI:

https://doi.org/10.4108/ew.v9i39.1193

Keywords:

big data science, origin/destination matrices, modal split, telecom operator, innovative methodology, mobile network data

Abstract

SUMBooST2 research develops universally applicable data science methodology which extracts key urban mobility parameters and origin/destination matrices from the anonymized big data set gathered from telecom operator. The methodology (toolbox) provides transport planners with a method for fast, efficient, and reliable provision of data on movements within the certain area. Origin/destination matrices with modal split will provide transport planners with valid input data for the planning of urban transport systems. The algorithms which separate relevant mobility data from the overall dataset are the unique part of the toolbox. The algorithms to identify passenger car trips are developed in 2020 project SUMBooST, and they are being upgraded in 2021 to detect trips made by active mobility modes and public transport. For the methodology to be valid, it must be implemented in representative number of cities. Previous SUMBooST project included implementation and validation in the City of Rijeka, and SUMBooST2 continues with two other cities, City of Zagreb, and City of Dubrovnik. The aim of the paper is to present innovative toolbox for the boost of sustainable urban planning based on big data science.

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