Road transport is indispensable for the exchange of goods and persons, but at the same time has severe negative consequences, among others related to road safety and environment. In order to meet EU targets, both the number of road crashes and vehicle emission levels need to be reduced substantially. For identifying the next generation of measures that will enable us to actually reach these targets, a far more in-depth understanding of road user behaviour is needed. The proposed UDRIVE project is building on the experiences of the PROLOGUE feasibility study and various Field Operational Tests (FOTs), and aims to contribute to developing this in-depth knowledge by:1. Conducting a large-scale European Naturalistic Driving (ND) study;2. Building one central database with the collected ND data;3. Performing targeted analyses in the areas of:o crash causation factors and associated risks,o distraction and inattention,o vulnerable road users,o eco-driving;4. Applying the findings in four specific area, notably:o the identification of new and promising countermeasures,o the potential of simple DAS for monitoring performance indicators over time,o the improvement of driver behaviour models for road transport simulation,o the possibilities for commercial applications of ND data;5. Leaving behind the collected data to be used, subject to legal and ethical constraints, for additional analyses once UDRIVE is finished.During a 21-month data collection effort, UDRIVE will collect information on 210 vehicles, each for one year: 120 passenger cars, 50 trucks, and 40 powered two-wheelers. All data, including video data showing the forward view and the view of the driver as well as GIS data, will be collected continuously to enable knowledge in the various research areas to be brought well beyond the current state of the art.The UDRIVE consortium consists of 19 partners and represents a good balance between different EU regions and various stakeholders. The consortium also represents a good balance between expertise on the various research areas and expertise on huge data acquisition and storage.