TrenLab

Safety and Safety Culture are high on the agenda of our Strategic Plan 2019-2023-2028, being fundamental pillars for Renfe and key elements for business development. Safety is an unquestionable value for Renfe, and therefore, in order to move forward, it is essential to carry out actions that allow us to transform and strengthen it.

We are looking for digitalization solutions in operational safety with the aim of providing Renfe with technological improvements and innovation in its systems through the strategy of implementing active and proactive safety in all its processes.

Below are examples of potential solutions for this challenge; however, candidates may propose any solution not included as long as it aligns with the challenge:

Development of a system for capturing and analyzing data in the cabin in real time using sensors and cameras to assist driving, for example, in detecting driver fatigue or drowsiness.
Development of geospatial communication systems that improve current speed support and monitoring systems during driving and approaching critical points (switches, signals, station stops, bumpers). For example, a predictive overtaking system before approaching a stop signal.
Interactive solutions that improve real-time information for travelers, allowing communication of, for example, high occupancy on trains and stations, warnings in case of emergencies or incidents, etc.
Digitization and automation of the real-time data dump of the onboard systems in the cabin, such as, for example, the data of the legal recorders with which Renfe’s traction vehicles are equipped, with the aim of developing real-time security and maintenance surveillance services.
Image monitoring and analysis systems for the identification of dangerous situations in railway environments such as level crossings, platform crossings, passenger boarding and alighting from trains and access to tracks integrated into control and alarm systems.
Development of data analysis systems based on neural networks that allow, through the analysis of internal data (operational and security level) and external data (economic, weather, social, etc.) to obtain predictions in the field of security with the aim of being able to anticipate possible negative events.
Solutions aimed at improving human resource management in the field of operational safety.
Video image analytics using neural networks for the analysis of risk situations in railway environments.