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Simulation is often used to gain an understanding of vehicle directional response. Furthermore, it is widely agreed that, given an adequate set of parameters that model the vehicle and the surface it drives on, it is reasonable to simulate a particular vehicle with a view toward understanding and perhaps improving its performance. This is not the case with the vehicle/driver system. Rather, in terms of a particular vehicle and driver, simulations provide interesting but not particularly reliable results because of the routine variability of the human part of the system. Genetic algorithms and their derivatives are algorithms with their form drawn from the biological theory of evolution. This paper suggests that genetic algorithms may be useful to evaluate certain important facets of vehicle/driver performance.

Recent advances in computing power, computer graphics, and virtual reality systems are leading to important new opportunities for the development and use of driving simulators. These advances in technology are pointing towards a future where human-in-the-loop simulation is increasingly valuable for training, human-factors research, and virtual prototyping. This paper presents a general literature review of driving simulation, and discusses important components of modern driving simulators. The paper concludes with speculation on the future of driving simulation.

The high expense of vehicle testing leads to the desire to use analysis as much as possible to get an understanding of rollover resistance. There is no shortage of computer programs which claim to be capable of simulating rollover events. The challenge is in providing reasonable parameters for the simulation and in understanding the range of validity of the computed results. This paper presents various mathematical models which bear on rollover, starting with a very simple quasi-static model which requires knowledge of only a few measured vehicle parameters. It then deals with simulations of increasing complexity and increasing need for measurements to provide accurate and detailed input data. The paper closes with remarks on the relationship between simulation and vehicle testing for rollover resistance.

The use of both closed- and open-loop test procedures for evaluating the performance of motor vehicles in lane-change maneuvers is reviewed. It is found that (a) variations in driver skill, (b) differences in the amount of information imparted to the driver by the layout of the test course, (c) the asymmetry in response between right and left lane-changes, and (d) the lack of understanding of the connection between open- and closed-loop performance present difficulties in evaluating lane-change performance. Further study is recommended using a particular form of evasive performance test to seek identifiable ergonomic and vehicle dynamics bounds on driver-vehicle system performance.