Presentation of the project: BusCA – Analysis of Disruptions in the Metropolitan Bus Service

BusCA – Analysis of Disruptions in the Metropolitan Bus Service is a project promoted by AMB Informació and developed by Eurecat within the CIDAI framework to analyse planned disruptions affecting the metropolitan bus service and assess the potential of artificial intelligence to improve their management.

Based on historical incident data recorded on AMB Informació’s corporate platform, as well as external data sources related to municipal activities and events, the project has analysed the behaviour of service disruptions and developed a proof of concept based on predictive models.
During the session, the main findings of the analysis will be presented, along with the challenges involved in developing models capable of anticipating disruptions and recommendations for moving forward with the potential deployment of an AI-based alert system to support operational management.

What will attendees learn?

How are disruptions in the metropolitan bus service distributed geographically and by type?
What value can external data sources provide to improve incident analysis?
The results achieved with the predictive models developed.
The feasibility of an AI-based alert system to support service managers.
The key recommendations and next steps identified throughout the project.

Programme

09:45 h | Registration

10:00 h | Welcome

- - Mireya Saludes, Business and Ecosystem Manager at CIDAI
  - Ramon Pruneda, CTO of AMB Informació
  - Sergi Masip, Coordinator of the Catalonia AI 2030 Strategy at the Secretariat for Digital Policies, Government of Catalonia

10:10 h | The Challenge of Managing Disruptions in the Metropolitan Bus Service
Ramon Campoy, Transport Information Management Specialist at AMB Informació

He will present the main challenges AMB Informació faces in managing planned disruptions to the metropolitan bus service, as well as their impact on operations and service quality. He will discuss the need for more structured and homogeneous data, the value of combining internal information with external data sources to better understand disruption patterns, and the opportunities offered by advanced analytics and artificial intelligence to move towards a more proactive, data-driven approach. He will also share key lessons learned throughout the project and the organization’s vision for future developments in this area.

10:25 | BusCA Project Development: Data Analysis and Predictive Modelling
Francisca Rosell, Researcher at the Applied Artificial Intelligence Technological Unit of Eurecat

To provide a technical introduction to the project, she will present the methodology followed throughout the project, from the analysis of available data sources to the development of predictive models. She will explain the main challenges related to data quality, structure and integration, the value of external data sources in enriching the analysis, and the modelling approach used to explore the potential of artificial intelligence to anticipate service disruptions. She will also share the technical results achieved and the lessons learned from the proof of concept.

11:00 | Results, Recommendations and Feasibility of an Alert System
Javier Fernández, Data Specialist at AMB Informació

This session will present the main results obtained, with special emphasis on the insights gained from both the data analysis and the proof-of-concept development. It will also show how the project highlighted the need for more homogeneous, structured and AI-ready datasets. Beyond the predictive model outcomes, the speakers will discuss the current limitations of the available data, the improvements required in data generation and management processes, and the recommendations for progressing towards future AI-based decision-support systems with greater chances of success.

11:10 | Q&A Session

11:30 | Coffee & Networking

11:30 | Closing

Programme

Venue