Motion feedback in advanced driving manoeuvres

During advanced driving manoeuvres, drivers can be hypothesized to use all the available cues to optimize their performance. Fixed-base simulators are commonly used for training of these advanced driving manoeuvres, despite the fact that motion cues are not present. In this
experiment we hypothesize that motion feedback improves driver performance and affects the driving control strategy during advanced driving manoeuvres when compared to a situation without motion feedback. A comparison between no-motion car-driving simulation and motion-feedback car-driving simulation is done, by measuring driver performance and control behaviour in a fast slalom. In the fast slalom designed for this experiment, a car drives at 70 Km/h around pylons spaced quite closely at approximately 30 meters apart. The advanced Desdemona motion platform was used in this study. Desdemona’s unique motion system allowed us to create a motion simulation that was almost one-to-one regarding the specific forces and angular rates in the actual car. A new motion cueing algorithm was developed to handle advanced driving manoeuvres like this fast slalom. Twenty subjects successfully drove the fast slalom in both conditions. The results from a paired comparison show that subjects prefer driving with motion feedback. Motion feedback also helped subjects conducting the driving task. The number of accidents was significantly lower in the motion condition, as compared to the no-motion condition. Significant differences in the maximum lateral specific force and in the average speed between the two motion conditions were found also. From the experimental results we conclude that there is a difference in driving advanced manoeuvres in a fixed based simulator as compared to a motion simulator. This difference influences driving behaviour with respect to keeping control over the car and also it is clear that the driver changes his control strategy.