Electric and connected public transport: the case of Zaragoza City Council and the Digizity project

The main results and impacts of the project are as follows:

• More than 50 products, systems and subsystems, all created and aimed at making public transportation cleaner, more efficient and more comfortable.
• Design of the first living lab in a real relevant environment, integrated in a real public transport operation. First electric, 5G-connected and autonomous line in the world.
• Reduction of the energy consumption of the public transport system, through energy efficiency measures in vehicles and through automation and digitalization of operations.
• Reduction of CO2 and particulate emissions into the atmosphere: improving public transport services and user experience increases the number of public transport passengers and reduces the use of private vehicles.
• Circular economy: the digitalization of transport services reduces the use of resources by improving processes and efficiency in the use and treatment of materials (up to 5% reduction of paper in Zaragoza's urban transport service).
• Development of a system that allows driver monitoring in order to determine whether the driver is in optimal driving conditions by assessing physiological (breathing and heart rate) and cognitive (distraction/somnolence based on the analysis of breathing and heart rate) parameters.
• Development of an Artificial Intelligence system to perform the task of guiding the vehicle as a support to the driver".
• Development of an intelligent management system aimed at optimizing the power and efficiency of every vehicle, focused on extending the life of the high-voltage battery and the fuel cell.
• Increased vehicle energy efficiency by integrating the thermal management systems of the engine (and auxiliary equipment), the air conditioning system and the battery thermal management system.
• Increased safety in urban and interurban transport by means of an early warning detection system for incidents on the road (by other vehicles, such as infrastructure elements, traffic lights,...) and vulnerable road users (e.g. pedestrians), by means of novel communication technologies.
• New models of information management and storage in the medium and long term that represent a significant advance compared to current big data technologies, computing capacity, etc.
• Development of AI applied to predictive vehicle maintenance to anticipate problems in critical elements of the vehicle.
• Design of an intelligent system to support operational decision-making: fleet planning and management of recharging points, real-time information on line occupancy, passenger drop-off points, etc.
• Design of an intelligent user information system in real time (waiting times at stops, transit times, etc.), with special attention to users with special needs.
• Development of a system for forecasting passenger demand (origin, destination) in the short and medium term (hours, days).