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SUMBooST2

SUMBooST2 is a follow up of SUMBooST 2020 project where the methodology of the toolbox was based on the identification of passenger car trips only.

Project summary

SUMBooST2 develops universally applicable data science methodology which extracts key urban mobility parameters and origin/destination matrix from the anonymised big data set gathered from telecom operator. 

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 the 2021 to detect trips made by active mobility modes and public transport. 

SUMBooST2 is a follow up of SUMBooST 2020 project where the methodology of the toolbox was based on the identification of passenger car trips only. The project plans to further improve the methodology and will mainly be focused on identifying sustainable transport modes and their strengthening, but personal car trips will also be analyzed as an additional validation of the first version of toolbox. 

For the methodology to be valid, it must be implemented in representative number of cities. SUMBooST included implementation and validation in the City of Rijeka, and SUMBooST2 continues with two other cities, Zagreb and Dubrovnik. 

Innovative methodology (toolbox) is based on big data science further enhanced and validated through traditional traffic research. The most creative and innovative part is the extraction of the mobility parameters from the big data set gathered from telecom operators. 

Project start:

1 January 2021

Budget:

€ 193 400

Context

The main objective is to provide the city transport planners and city decision makers with a toolbox that can give them valid input for their transport planning. The toolbox usage will provide its users with information on origin/destination city zone pairs with a significant share of trips made by active modes of transport and give them a valid input where they can make upgrades and additionally expand the usage of active mobility modes. Also, the toolbox will provide users with origin/destination pairs with low active transport and a large share of passenger car trips and give them input where to discourage those unsustainable mobility modes. The usage of the toolbox can set basis for the development of efficient transport measures and generally to develop a transport system in a green, safe, and sustainable way.

Challenge

The main challenge addressed is the inability to collect the destination destination matrix with modal split. This dta set can simplify every urban transport planning process. The origin/destination matrix with a modal split is a valid data set that is hard and expensive to obtain in a traditional way (traffic counting, surveying). The Toolbox provides a fast and efficient way to obtain an accurate data set based on which city planners can develop new solutions.

Expected outcome

The main output of the project is a development of new features (analytical possibilities) within SUMBooST toolbox for digital transformation of existing (traditional, ingrained) analytic methodologies by novel utilization of telecom big data and data science capabilities for urban mobility domain. Also, Data science methodology validated within this project will became part of curricula of lectures being held at FTTS “Laboratory for Data science in transport and logistics”)

Project partners

Silver
France

Ynstant

Silver
Spain

RMIT Europe

Silver
Spain

Parkunload

Project Lead

Marko Šoštarić

msostaric@fpz.hr