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Mandatory policies have played an important role for the automakers develop better projects in terms of safety and fuel efficiency; while customers of commercial vehicles are mainly interested in lowering the Total Cost Ownership (TCO). A common factor among these requirements is the driving performance, which is influenced by external sources. A lot of Original Equipment Manufacturers (OEMs) and tech companies are launching driving feedback systems that look over all of the data from the vehicle, driver and road in order to generate outputs to improve driver behavior. Understanding human machine interface (HMI) and applying Behaviorism concepts to the analysis of these systems, this paper is aimed to discuss how different driver coaching systems work. Overall, the main result is the changes in decision making outcomes about driving styles through enhancing awareness.

The logistics process in Brazil and the world represents a significant portion of the cost of manufactured products, either for export or import. The availability of technologies that make the logistic process more efficient directly affects the product’s transportation productivity and makes them more competitive. This paper presents a telemetry model of commercial vehicles integrated with harvest machines in agriculture operations, allowing accurate scheduling of loading and unloading processes at the field. In this study, we introduce a conceptual model of a technological matrix, where the shared topologies of vehicle information processing help predict failures, identification of wear of vehicle and machine’s components. The opportunity is demonstrated to collect data from agricultural machines and combine them with data extracted from trucks. The sharing of information on farm machinery and trucks in real-time establishes an essential change in crop management in the field.

The study is carried out through numerical and experimental methods. The finite element method is used to simulate the support mechanical behavior via modal analysis, and for the evaluation of stress concentration regions through pressure and thermoelastic static analyses, and dynamic analysis. The fatigue life is calculated for the presented stresses. Stress, acceleration and temperature data were obtained through dynamic test. For material evaluation, chemical analysis, hardness and metallographic analysis were carried out. For thoroughness, a failed support fractography will be presented. The objective of this study is to correlate the data obtained by numerical method with experimental data, and as a result, the support failure mechanism was identified. A modified support is presented to avoid the failure for the determined loads. The support within the proposed modifications reduces the current maximum stress in 41% and improved the fatigue life in 4.99e5 cycles.