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A transformation of agriculture reached commercial reality at the beginning of this century as automated steering of agricultural machine systems increased the productivity and convenience in crop production systems. Following guidance, additional technologies have resulted in increasing optimized machine productivity. Today, integrated worksite solutions through machine and information management continues to transform agriculture. This is the precursor to autonomous worksite solutions that lead to the optimization of the worksite ecosystem. This paper will review the progress from the perspective of the customer value provided by increasing automated systems and the industry execution of autonomous driving technologies and will enable the pathways to autonomous worksites.

Typical approaches to regulating sound performance of vehicles and products rely upon A-weighted sound pressure level or sound power level. It is well known that these parameters do not provide a complete picture of the customer’s perception of the product and may mislead engineering efforts for product improvement. A leading manufacturer of agricultural equipment set out to implement a process to include sound quality targets in its product engineering cycle. First, meaningful vehicle level targets were set for a tractor by conducting extensive jury evaluation testing and by using objective metrics that represent the customer’s subjective preference for sound. Sensitivity studies (“what-if” games) were then conducted, using the predicted sound quality (SQ) index as validation metric, to define the impact on the SQ performance of different noise components (frequency ranges, tones, transients).