Evaluation of static driving posture predictions for trucks

Abstract: The project aims to validate and assess different methods for predicting driving posture in trucks using a physical truck cabin as well as a digital version of the truck cabin in the form of CAD geometries. Two prediction methods, statistical and IPS IMMA simulation, were employed. By doing a User Test, measurements in the physical truck cabin were obtained for at least one of the four key analysis points, the position of the Steering Wheel. In both prediction methods, the statistical and IPS IMMA simulation, the location of the Steering Wheel, H-Point, Hip Center and Eye Point were obtained.  Some similarities exist between the results of the two prediction methods and the User Test. Some of the most relevant conclusions drawn from the results obtained were that regarding the Steering Wheel position the statistical prediction better predicted the distances above accelerator heel point and IPS IMMA simulation better predicted the distance aft to accelerator heel point, in both predictions, it can be seen that there wasa direct relationship between the anthropometric measurements of the subjects and the position of the steering wheel, but in the User Test this did not occur. To conclude, the results from this project work indicates that the statistical prediction gives better results, since they were more in line to reality. However, both prediction methods have improvement potential that could be studied in future projects.