Cermonews #18 | What Is AI-Assisted Public Transport Planning?
- Parabol
- 16 hours ago
- 5 min read
🚌 Hello from the 18th edition of Cermonews! 👋🏻
We’re back with a new edition, and this time we’re exploring a topic that is becoming increasingly relevant in public transport planning: AI-Assisted Public Transport Planning.
Every day, public transport systems generate large amounts of data across routes, stops, timetables, vehicles, drivers, passenger demand, and daily operations. And these data points are not independent from one another. A decision made in one part of the system can directly affect the rest of the plan.
Throughout this edition, we’ll explore:
🤖 What AI-assisted public transport planning is,
📊 How AI can be used in public transport planning,
🔍 How AI can support the evaluation of existing plans and help identify potential problems,
💻 How we use AI in Cermoni,
👩💻 And the role of AI in supporting planners’ decision-making processes.
We’ll also ask you a question to hear different perspectives and experiences on the topic.
Enjoy reading! ✨
🤖 What Is AI-Assisted Public Transport Planning?
Public transport planning requires many interconnected components to be considered together, including passenger demand, routes, stops, timetables, vehicles, drivers, and daily operations. A change made in one part of the plan can directly affect another.
AI-assisted public transport planning is an approach that supports planning processes by enabling this large and interconnected data structure to be analyzed and interpreted more quickly.
The goal is not for AI to make decisions instead of the planner. Rather, AI helps highlight important information within large amounts of data, identify potential problems faster, and make it easier to evaluate different alternatives.
📊 What do you think is the most important contribution AI can make to public transport planning?
Identifying problems faster
Analyzing large amounts of data more easily
Evaluating different planning alternatives
Accelerating planning processes
🤖 How Is AI Used in Public Transport Planning?
AI can be used across many areas of public transport planning. Historical journey data can be analyzed to identify changes in passenger demand and determine which routes, stops, or time periods experience higher demand, helping planners anticipate where service needs may change.
AI can also be used to predict delays, identify vehicle maintenance needs, or detect potential disruptions earlier by analyzing historical operational data.
Machine learning-based methods can support the detection of unusual patterns or potentially inaccurate results within large datasets. This makes it possible to go beyond simply reporting public transport data and instead identify patterns and areas that may require closer attention.
🔍 How Can AI-Assisted Planning Support the Evaluation of Existing Plans?
As public transport plans become more complex, identifying certain problems manually can become increasingly difficult. Long vehicle idle times, unbalanced driver duties, insufficient break times, capacity issues, or conflicting assignments can easily be overlooked across hundreds of rows of planning data
.
AI can evaluate the plan as a whole and help identify areas that require attention more quickly. Importantly, the source of a problem may not always be where it first appears. For example, an inefficiency observed in vehicle and driver assignments may actually originate from an irregularity in the timetable.
AI can also help evaluate the impact of different alternatives. The effects of changing a departure time, adding an extra trip to a high-demand route, or assigning a vehicle to a different duty can be compared across the rest of the plan.
In this way, AI can support planners not only in answering “Is there a problem in the plan?” but also “What is causing the problem, and what can we change?”
💻 How Do We Use AI in Cermoni? | AI-Assisted Public Transport Decision Support System
At Cermoni, we use AI at different stages of the planning process. One of these is Cermoni AI, our AI assistant integrated directly into the platform.
Cermoni AI evaluates project data and planning outputs together, allowing planners to ask questions across different areas, from GTFS data and occupancy analysis to timetables and vehicle and driver assignments.
For example, in a vehicle and driver assignment project, a planner can ask, “Are there any inefficient areas in this plan?” Cermoni AI can evaluate the existing outputs and identify that the underlying issue may not be the vehicle or driver assignment itself, but an irregularity in the timetable, and suggest revising it.
Similarly, when an unexpected result appears, AI can help investigate potential errors or anomalies instead of requiring planners to manually review hundreds of rows.
But our use of AI is not limited to Cermoni AI. We also use machine learning-based methods to identify unusual or potentially inaccurate results in occupancy detection. When developing new algorithms, we use AI to create different scenarios, test results, and evaluate edge cases that may occur less frequently in normal operations.
With this approach, AI becomes more than a tool that simply answers questions. It acts as an assistant that helps interpret data, identify problems, and support planners throughout different stages of the planning process.
👩💻 Is AI Replacing the Public Transport Planner?
The purpose of AI-assisted public transport planning is not to make decisions instead of planners, but to support their decision-making process. AI can analyze large amounts of data in a short time, highlight problems that might otherwise be overlooked, evaluate different options, and provide recommendations.
However, the quality of AI-generated results is directly related to the accuracy and timeliness of the data being used. Incomplete or inaccurate data can affect the resulting analyses and recommendations. At the same time, factors such as a city’s needs, service priorities, operating conditions, and real-world experience cannot always be fully understood from data alone, yet they play an important role in planning decisions.
For this reason, AI-generated insights need to be evaluated together with the planner’s experience and operational knowledge. AI helps interpret the data and reveal problems and alternatives, while the planner evaluates this information within the city’s actual conditions and makes the final decision.
Ultimately, the real value of AI in public transport planning lies not in replacing planners, but in helping them make faster, more comprehensive, and data-driven decisions.
News From Us 📰
🌍 Discussing Data and AI in Public Transport with the RTA Team in Dubai
Our Marketing & Business Development Director, Tuğçe Işık, and Chief Technology Officer, Haldun Yıldız, contributed to the “Data and Business Intelligence in Public Transport” training organized by UITP for Dubai’s RTA team.
🚌 The training covered the collection and measurement of mobility data, the role of AI and open data in public transport, and data-driven decision-making processes through examples from different cities.
We would like to thank the RTA team, UITP, and UITP MENA teams for their contributions. 🤝
📊 A New Era for Onboard Occupancy Insights with Cermoni: No Additional Hardware Required
Cermoni can generate onboard occupancy information with 90%+ accuracy using existing smart card data, without requiring additional hardware or manual passenger counts.
🚌 These route- and trip-level insights can support a wide range of decision-making processes, including demand-based timetable planning, fleet and capacity management, crowding detection, and performance analysis.
🎙️ Voice of Customer: Operational Planning with Cermoni in Konya
Konya Metropolitan Municipality uses Cermoni in its public transport operational planning processes, enabling timetable and vehicle planning to be managed in a more integrated, traceable, and manageable structure.
🎙️ Mahmut Sami Demirel from Konya Metropolitan Municipality’s Bus and Terminal Branch Directorate shares how Cermoni contributes to faster planning results, reduced risk of errors, and improved operational efficiency.
🚍 How Would AI-Assisted Public Transport Planning Impact Your Operations?
📩 If you would like to share your experiences or perspectives on the use of AI in public transport planning, we would be happy to hear from you.
We continue working to make public transport planning processes more efficient, faster, and data-driven through AI-assisted approaches. 🤖🚌
You can also read this edition online and share it with anyone who might find it interesting.
See you in the next edition! 👋
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