Disrupting agricultural vehicular automation is imperative for the solutions to global as well local challenges in agricultural production system. Historically, application of scientific and technological developments through increased mechanization and precision farming have provided several opportunities for agricultural production in general and within forage handling operations. Some promising engineering developments in the 20th century with regards to forage handling include forage harvesters, balers, and automated wrapping equipment of balers using stretch films of 25μm thick to lower risks of dust, molds, spores, mycotoxins respiratory allergenic disorders in livestock and humans. Baler machines has made it possible to trade silage (harvest and storage of moist grass using fermentation) in portable packages between farms which typically weigh 600-800 kg freshly cut per bale and are more popular on smaller farms with limited labor and financial resources to construct silos. Bales made up of hay or silage formed by balers are usually too heavy to be picked up by humans alone. Thus, they are picked up from fields using conventional utility vehicles such as tractors or loaders operated by a human. These kinds of operations are labor intensive and associated with health and accidents risks. There is also a potential to further improve the efficiency and environmental impact since most decisions are made by humans and thus limited to human labor capabilities in terms of load handling, sensing, multitasking, planning, consequence analysis etc. One significant contribution could be relieving the human operator from tedious driving task and incorporating optimize automated planning & driving functionality of field operations such as haybale collection. The focus of this thesis is to advance the existing autonomy level in agricultural vehicles for field operations. This is done by investigating current challenges and opportunities with agricultural vehicular automation and potential improvement for one of the field operations. Bales collection operation is one of the riskiest operations and taken as one case with potential for improvement with automation. Study of path planning approaches for bales collection operation in typical fields environment shows that optimized solution with concept autonomous articulated vehicle with neighborhood collection capabilities (ANV), can reduce working distance by 15-20% for this task. To further, a new approach of pure pursuit algorithm with increased reduction in tracking errors of an articulated vehicle is developed and evaluated.