AI-Powered Innovation: Shaping the Future of Public Transit
Artificial intelligence is playing a key role in driving the next generation of public transit solutions. Across various projects, AI is helping us enhance our products and services, making mobility smarter, more efficient, and more passenger-friendly.
Significantly Improve Departure Predictions
In a pilot project between INIT and the Golden Gate Bridge, Highway & Transportation District in San Francisco, INIT significantly enhanced bus departure predictions using AI-based software. Using a machine-learning core, historical and real-time data were analyzed, leveraging advanced pattern recognition algorithms to process vast amounts of information. Integrated within INIT's statistics software, the system continuously evaluated operating data, automatically retraining models when prediction accuracy declined, ensuring real-time adaptability to traffic changes. This dynamic approach improved prediction accuracy from 49 to 87.47 percent in extreme cases, far surpassing traditional methods. INIT's MOBILE-ITCS nextGen now includes ML forecasting as a standard feature, enabling transit agencies to provide highly accurate departure times while enhancing passenger satisfaction through live predictions.
Seamless On-Demand Transport with MOBILE-FLEX Efficient, customer-friendly, on-demand transport is a cornerstone of the mobility transition — especially when it comes to the first and last mile of a journey. Our MOBILE-FLEX solution uses AI-based algorithms to optimize ride pooling and dispatching in real time. Whether passengers request rides to virtual stops, fixed addresses, or specific coordinates, the AI efficiently links travel requests, reduces empty trips, and shortens waiting times — all while ensuring seamless integration with public transit networks. This makes on-demand transport more flexible, accessible, and sustainable, especially in rural areas or during off-peak hours.
Smarter Decisions in the Control Center An exciting project INIT is working on is KARL (Artificial Intelligence for Work and Learning in the Karlsruhe Region). This initiative explores how AI can transform workplaces and organizations by developing human-centered, transparent assistance systems. As part of KARL, INIT is researching AI-based tools to support control center personnel. The goal is to train AI to analyze historical data, consider numerous influencing factors, and recommend dispatching measures tailored to the current situation — making decision-making faster, more accurate, and more efficient.
Passenger Satisfaction Public transport is evolving rapidly — and with it, the expectations of passengers. AI and machine learning are powerful tools that allow transit agencies to create smarter, more personalized services. By leveraging AI in everything from departure predictions to dispatching, INIT helps public transport providers meet the needs of today’s passengers while paving the way for the mobility of tomorrow.
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