Drone-to-Vehicle Integration of Data: Design Concept and Application to Vehicle Automation System

Modern vehicles are characterized by a high degree of environmental perception and automation. This is made possible by the development of new motion control and driver assistance systems as well as new methods for sensor-based detection of driving parameters. However, the functionality of commonly used visual and wave-based sensor systems, such as cameras, radars, etc., can be limited when installed in a vehicle as some obstacles fall into the blind zone due to the road profile or other road users. It is also difficult to detect road-specific parameters such as gradient, slope, or surface conditions with onboard vehicle sensors. A method to improve the vehicle’s detection capabilities can be proposed by extending the information channels with additional sensors by mounting them on an assistant drone. This article presents a framework for drone-to-vehicle collaboration that enables the integration of data from drone sensors into the vehicle motion control. The article gives an overview of the system, the technology created for the implementation, and the challenges to be overcome by integrating the different components. The hardware implementation of the drone and the integration of the data into the vehicle control unit (VCU) are presented. The proposed approach allows the vehicle to view the road from different angles and detect changes in road conditions from a distance. It extends the capabilities of the vehicle motion control. The effectiveness of the developed framework is experimentally validated with an electric vehicle’s velocity control and traction control on low-friction surfaces.