The goal is fuel savings during the operation of trains, from diesel and electric to battery-powered. Safe passage through the tracks according to the timetable can be achieved in various ways, which are more or less economical. Using available data and with the help of AI algorithms, an energy-efficient route can be calculated and recommended.
Assistant train driver for energy saving and consumption management on the train
Client NameDE, FR, CH železniční dopravci a FR výrobce vlaků (DE, FR, and CH railway operators and an FR train manufacturer)
Client CountryEU
- Client typeEnterprise
- IndustryTransportation, Mobility & Logistics
- Application areasOperations & Process Automation, Strategy, Planning & Decision-Making, Supply Chain & Logistics
- AI technologiesAdvanced Analytics / Data Science, Forecasting & Time Series Analysis, Graph AI, Optimization & Planning, Simulation / Digital Twins
- Business impactsOperational Efficiency & Cost Savings, Sustainability & Social Responsibility
- Data typesGeospatial Data, Graph / Network Data, Sensor / IoT Data, Structured Tabular Data, Time Series
- Delivery modelsConsulting, Custom Development, Product / Licensed Software
- DeploymentsHybrid
- Key capabilitiesDecision Support & Augmented Analytics, Planning, Scheduling & Optimization
- Project stagesInitial Production Deployment
- Solution formsAnalysis, Recommendation, or Report, Automated Backend Process, Integrated Edge / On-device Solution, Standalone Application, Web Portal / Dashboard
Solution Description
Problem description
Solution
Our assistant can calculate the energetically optimal passage for the entire route, ensuring the train travels safely and according to the timetable. We consider all available information, from timetables, map data, the physical model of the train, up to track management. The system provides recommendations to the engine driver and transmits recommendations to the train’s energy unit.
Main Users of the Solution
Train drivers; dispatchers / operations supervisors; energy and operations analysts; train driver instructors/trainers.
Project timeframe (months)
36
Technologies used
Mobile platform, planning algorithms and scheduling algorithms, integration into the train system.
Additional services
- Audit / feasibility study
- Identification and prioritization of suitable use-cases
- Data collection and pre-processing
- Annotation / synthetic data / dataset extension
- Selection and adaptation of the AI model
- Ongoing maintenance and rmodel retraining
Use of Personal / Regulated Data
Yes
Implementation
Project Owner on the Client's Side
Head of Innovation / Digital Transformation
Participation on the Client's Side
- Domain / process experts
- Data & ML specialists
- Software & data engineering / IT Ops
- Project and change management
- Quality, security compliance
- End users
Form of Supplier Involvement
Joint implementation with the client
Operation and Maintenance
Operational Model
Joint management
Needed Competencies on the Client's Side
System configuration
Impact and Results
Qualitative Benefits
- Lower energy consumption and emissions; smoother ride and less wear and tear
- Unified driving style across drivers thanks to the Assistant
- Informed energy management for battery trains (how much to charge batteries, whether it is possible to reach the next station, when to heat, etc.)
Quantitative Results
Energy consumption with the use of the system is 5-8% lower
Lessons Learned and Recommendations
Key Success Factors
- Strong sponsor on the operations side and involvement of train drivers from the first prototype
- High-quality and unified data (track profile, gradients, speed limits, timetable).
- Iterative tuning via simulation/digital twin and real tests on the test track.
- Managed adoption: training, coaching, change management and crew feedback.
Recommendation for Others
Iterative development starting from the first prototype and a simple sub-optimal algorithm, leading up to a fine-tuned system with very precise calculation. Possibility of simulations, data collection during real-world operation, and testing on the track.
- CompanyEntentee
- ContactSeen Aquin Avila
- Emailseen.aquin@ententee.com
- Websitehttps://ententee.com
- AddressZa Poříčskou bránou 365/21, 186 00 Praha