Triboelectric nanogenerator sensors for intelligent steering wheel aiming at automated driving

This paper reports a novel intelligent steering wheel developed based on the concept of triboelectricity aiming at automated driving to reduce traffic accidents. A sandwich-type sensor is designed to be integrated into the steering wheel with the aim of identifying driver's steering intention. The steering wheel of a vehicle is furnished with a triboelectric nanogenerator (TENG)-based sensor for detecting driver intention. The superiority of the TENG-based sensor is demonstrated by comparing it to other available sensors within a vehicle. By employing different machine learning techniques, we develop classification models based on driving data from multiple drivers. We show that the faster reaction time of the TENG-based sensor can aid in emergency obstacle avoidance when compared to the regular steering wheel sensor through the use of model-predictive control. The fusion of data generated by the proposed TENG-based sensor and advanced control model represents a crucial step towards the development of an intelligent steering wheel for automated systems. This will improve the human-machine interaction for vehicle control, ultimately resulting in more efficient and effective control of the vehicle.