2025-1.2.1-HU-RIZONT
Acronym and title of the project
| AITONOMY: Artificial Intelligence-driven Traffic Optimization and intelligent battery maNagement for interaction-aware autOnomous Mobility sYstems |
Project overview
The project aims to develop an integrated framework for autonomous, cooperative and electric vehicles (ACEVs) addresses two critical and interdependent challenges: ensuring safe and socially aware navigation in complex urban environments and managing battery health and energy efficiency.
Enabling easy data exchange is achieved through a unified layer, promoting cooperation between vehicles.
Partners
| Partner name | Country | Role |
|---|---|---|
| Széchenyi István University | Hungary  | Lead partner |
| Karlsruhe Institute of Technology | Germany  | Cooperating partner |
| Delft University of Technology | Netherlands  | Cooperating partner |
| Embry-Riddle Aeronautical University | USA  | Associated partner |
References
- aitnm.github.io
- jkk-web.sze.hu/en/projektek/aitonomy
- go.sze.hu/aitonomy
- nkfih.gov.hu/english/international-cooperation/hurizon-programme
What is our research topic?
AITONOMY focuses on an integrated framework for autonomous, cooperative and electric vehicles (ACEVs), addressing two tightly coupled challenges: safe, socially aware navigation in complex urban environments and battery health/energy efficiency over the vehicle’s operational lifetime.
Why is it important?
Urban deployment of ACEVs depends on predictable, trustworthy interaction with all road users, especially vulnerable road users (VRUs), while also meeting sustainability requirements through energy-efficient operation and long-term battery preservation. AITONOMY explicitly merges cooperative safety concepts with predictive energy management to support both goals in real urban traffic scenarios.
What do we want to achieve?
- Cooperative trajectory planning that optimizes safety, passenger comfort, and interaction with VRUs.
- Battery-aware decision-making: balancing short-term safety maneuvers with long-term battery state-of-health and reduced degradation, through a multi-objective planning approach.
- A validated, deployable framework that improves urban mobility safety and sustainability, supported by rigorous verification and validation.
What is new in the project?
AITONOMY introduces AI-driven, scenario-in-the-loop testing, where the test environment evolves dynamically based on the vehicle’s real-time behavior, enabling systematic exposure of rare, safety-critical edge cases. Validation leverages the ZalaZONE proving ground’s modular mixed-traffic zones, combined with digital-twin capabilities for realistic and repeatable assessment.
Why our team?
The consortium brings complementary excellence across cooperative autonomy, battery modeling and predictive optimization, real-world validation infrastructure, and regulatory alignment:
- Széchenyi István University (lead) contributes scenario generation, embedded integration, and validation infrastructure linked to ZalaZONE’s mixed-traffic environment.
- Delft University of Technology leads battery degradation models and state-of-health estimators integrated into an optimization framework for long-term battery preservation.
- Karlsruhe Institute of Technology contributes cooperative autonomous systems and safe decision-making for predictable interaction with VRUs.
- Embry-Riddle Aeronautical University (associated partner) supports validation benchmarks and regulatory/compliance alignment relevant to ACEV deployment.
Acknowledgement
Grant No. / project ID: 2025-1.2.1-HU-RIZONT-2025-00129
Funding: Supported by the National Research, Development and Innovation Fund of Hungary (NRDI Fund) under the HU-RIZONT International Research Excellence Cooperation Programme (Grant No. 2025-1.2.1-HU-RIZONT-2025-00129).
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