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. [Display omitted] •Design of TENG-based sensor for steering wheel aiming at automated vehicle’s safety.•Verification of faster reaction of TENG-based sensor than steering angle sensor.•Identification of driver’s steering intention based on machine learning algorithms.•A shared haptic driving method based on model predictive control for driving safety.