The vision of i4Driving is to lay the foundation for a new industry-standard methodology to establish a credible and realistic human road safety baseline for virtual assessment of CCAM systems.
Cooperative, connected and automated mobility (CCAM) will transform drivers from isolated entities to users of a shared fleet of vehicles in a fully integrated multi-modal transport system. Ensuring the safety and efficiency of such a system will require extensive simulation of virtually limitless scenarios and consideration of a wealth of human factors including age, disease, driving experience and more.
The EU-funded i4Driving project will develop a simulation library and methodology to account for the incredible uncertainty in both human behaviour and use case scenarios. It will lead to an industry-standard methodology for establishing a realistic human road safety baseline for the virtual assessment of CCAM systems via augmented reality.
i4Driving covers the full performance spectrum of human drivers in critical driving simulations, to compare the safety performances of AVs and human-driven vehicles.
Two central ideas proposed are:
- a multi-level, modular and extendable simulation library that combines existing and new models for human driving behavior; in combination with
- an innovative cross-disciplinary methodology to account for the huge uncertainty in both human behaviors and use case circumstances.