Every dynamic driving simulator, no matter how advanced its motion system is, has limited space in which to recreate the accelerating motions of the simulated road vehicle. The VTI driving simulator Sim IV is no exception. The classic motion cueing algorithm used in Sim IV strives to centre the drivers cabin in the simulator motion envelope and is tuned to precisely accommodate accelerations in a worst case scenario without hitting the physical boundaries. Using knowledge about the road ahead and the vehicle model one can preposition the cabin to an off-centre point, virtually increasing the available space so that larger motions are made possible. This aims to increase the impression of realism in the driving experience. The prepositioning algorithm presented in this thesis is developed as an addition to the current motion cueing algorithm and make use of road-and vehicle data to find a suitable preposition. The motion to the preposition is made under the human perception threshold to avoid rendering of false cues. Simulations show that the amount of acceleration presented by the sled can, with prepositioning, be increased by up to 25% in longitudinal and 53% in lateral direction. During a comparative study of the simulator motion, test subjects indicated that they had a more realistic driving experience with than without prepositioning.

Commonly used tire models for vehicle-handling simulations are derived from the assumption of a flat and solid surface. Snow surfaces are nonsolid and may move under the tire. This results in inaccurate tire models and simulation results that are too far from the true phenomena. This article describes a physically motivated tire model that takes the effect of snow shearing into account. The brush tire model approach is used to describe an additional interaction between the packed snow in tire tread pattern voids with the snow road surface. Fewer parameters and low complexity make it suitable for real-time applications. The presented model is compared with test track tire measurements from a large set of different tires. Results suggest higher accuracy compared with conventional tire models. Moreover, the model is also proven to be capable of correctly predicting the self-aligning torque given the force characteristics.

Currently the development and evaluation of winter vehicle handling characteristics are almost solely based on subjective assessments (SA) done by expert drivers. This is both expensive and time consuming, and therefore in conflict with the general goal of shortening project development and testing time meanwhile fulfilling more restrictive and demanding specifications.A more effective vehicle dynamics evaluation would be to use Computer Aided Engineering (CAE) for objective testing. Although objective evaluations are well defined for high friction conditions, or summer testing, the correlations between objective metrics (OM) and SA are still under development (Chen & Crolla 1998, Harrer et al. 2006, King et al. 2002, Nybacka et al. 2014a. Furthermore, these objective methods are not directly applicable for low friction testing, or winter testing, because the added challenge of constantly changing surface conditions. This causes both low signal-to-noise ratio measurements and low robustness, or repeatability, of the results. This difficult situation is increased by the fact that there is only one short winter test season per year and hemisphere, which limits the possibilities to shorten project times, as several winter test periods are normally required. All the above are motivations to understand: − How expert drivers perform their winter SA. − How objective tests, measurements and OM shall be defined for winter tests. − How OM and SA correlate in winter conditions and compares with summer conditions. During this research, a winter test expedition was performed in order to develop the methods to evaluate vehicle dynamics handling on winter conditions, see Figure 1. The goals of the performed tests were to study how winter objective testing should be performed when using steering robots. By identifying the suitability of different objective test manoeuvres, methods and/or procedures; the effects that the surface conditions have on the results and their repeatability, and if key OM are robust enough to describe the vehicle performance during changing surface ABSTRACT: This paper presents a test procedure developed to gather good quality data from objective and subjective testing on winter conditions. As the final goal of this test is to analyse the correlation between objective metrics and subjective assessments on winter for steering and handling, this procedure has to ensure a minimum change of the surface properties, which has a major influence on vehicle performance, during the whole test campaign. Therefore, the method presented keeps the total test time very low and allows similar vehicle configurations to be tested, objectively and subjectively, very close in time. Moreover, continuous maintenance work on the ice is performed. Reference vehicles are also used to monitor the changes on vehicle performance caused by weather conditions, which are inevitable. The method showed to be very effective. Initial results on objective metrics and subjective assessments are also presented.

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