| Summary: | The diffusion of electronics and sensors in agricultural vehicles is enabling a revolution in the field, leading—among the rest—to the introduction of advanced driving-assistance systems (ADAS). From this perspective, the three key performance indicators (KPI) in a tractor are indeed the driving safety, fuel consumption, and operator comfort. Such indexes describe the way the driver interacts with the vehicle, the environment, and other vehicles, respectively. Therefore, such information would be particularly valuable if promptly provided to the driver, e.g., on a dashboard visualizer, so as to adapt the driving style accordingly. Within this context, we propose an algorithmic solution for the on-line estimation of such KPIs. More specifically, by using an off-the-shelf smart-sensor equipped with an Electronic Control Unit (ECU), the chassis accelerations are first processed to extract physics-inspired features and then used to assess the safety and comfort levels; similarly, the speed profile is used to evaluate the economicity of the driving style. The developed method is based upon a cheap setup, and thus it is industrially amenable for its simplicity and robustness. A sensitivity analysis to establish the best sensor placement is finally carried out, together with an extensive experimental campaign considering offroad, urban, and circuit paths.
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