Public road transport jobs forecast by Autocorb

Duration of the project:

January, 2020 –
June, 2022


Project Manager

inLab FIB Team:

Areas of expertise involved in the project


Public road transport jobs forecast by Autocorb


The inLab FIB of the UPC collaborates with Intelibus in the project of characterisation and modelling of passenger demand in buses.

The main objective is the development of algorithms for predicting the use of passengers on a bus using data-driven methodologies from heterogeneous data sources (ticketing, calendar, bus cameras, etc.). In particular, classical methods for the treatment of time series will be studied, such as the ARIMA method, and neural network algorithms that will allow other important variables such as the school calendar to be incorporated into the time series of employment.

Intelibus is a real-time information system in the passenger transport sector, which uses the GPS positions of buses and the ticketing or counting system to provide useful information in real time to both public transport users and the company operating the service.

The results of the search will allow the user to consult, through an APP, the estimated bus occupancy throughout the day. In this way, the aim is to ensure that users opt for those journeys that run more empty, thus balancing the supply and demand of the service and avoiding crowds on public transport.

The new tool will be implemented in the collaborating company Autocorb, which operates urban and interurban lines in the metropolitan area of Barcelona.


Poster summarising the project: