AI-supported decision-making support

Project description

This project deals with the development of an intelligent traffic management system to overcome operational challenges in public transportation. The system uses artificial intelligence, in particular Large Language Models (LLMs), to provide real-time decision support and optimize resource allocation in Hannover's transport network.

The system supports employees in critical situations such as

• Accidents on the tracks
• Severe weather events
• Spontaneous absences due to illness
• Passenger bottlenecks
• Train delays

Project goals

• Implementation of an AI-based decision support system for short-term operational challenges
• Development of a real-time dashboard to monitor and visualize key traffic metrics
• Integration of multiple data streams, including timetables, staff availability and passenger numbers
• Development of an interactive chatbot interface for quick decision support
• Development of predictive analytics functions to forecast staff shortages
• Optimization of resource allocation in the event of disruptions and at peak times

Project team

Students

• Pascal Nemecek
• Sithara Senarath
• Maximilian Feldhaus
• Ahmed Shahin
• Nail Khazeev

Supervisor

• Mara Burger
• Jan vom Brocke