Motion platforms can be used to provide vestibular cues in a driving simulator, and have been shown to reduce driving speed and acceleration. However, motion platforms are expensive devices, and alternatives for providing motion cues need to be investigated. In independent experiments, the following eight low-cost nonvestibular motion cueing systems were tested by comparing driver performance to control groups driving with the cueing system disengaged: (1) seat belt tensioning system, (2) vibrating steering wheel, (3) motion seat, (4) screeching tire sound, (5) beeping sound, (6) road noise, (7) vibrating seat, and (8) pressure seat. The results showed that these systems are beneficial in reducing speed and acceleration and that they improve lane-keeping and/or stopping accuracy. The seat belt tensioning system had a particularly large influence on driver braking performance. This system reduced driving speed, increased stopping distance, reduced maximum deceleration, and increased stopping accuracy. It is concluded that low-cost nonvestibular motion cueing may be a welcome alternative for improving in-simulator performance so that it better matches real-world driving performance.

In advanced driving maneuvers, such as a slalom maneuver, it is assumed that drivers use all the available cues to optimize their driving performance. For example, in curve driving, drivers use lateral acceleration to adjust car velocity. The same result can be found in driving simulation. However, for comparable curves, drivers drove faster in fixed-base simulators than when actually driving a car. This difference in driving behavior decreases with the use of inertial motion feedback in simulators. The literature suggests that the beneficial effect of inertial cues in driving behavior increases with the difficulty of the maneuver. Therefore, for an extreme maneuver such as a fast slalom, a change in driving behavior is expected when a fixed-base condition is compared to a condition with inertial motion. It is hypothesized that driving behavior in a simulator changes when motion cues are present in extreme maneuvers. To test the hypothesis, a comparison between No-Motion and Motion car driving simulation was done, by measuring driving behavior in a fast slalom. A within-subjects design was used, with 20 subjects driving the fast slalom in both conditions. The average speed during the Motion condition was significantly lower than the average speed during the No-Motion condition. The same was found for the peak lateral acceleration generated by the car model. A power spectral density analysis performed on the steering wheel angle signal showed different control input behavior between the two experimental conditions. In addition, the results from a paired comparison showed that subjects preferred driving with motion feedback. From the lower driving speed and different control input on the steering wheel, we concluded that motion feedback led to a significant change in driving behavior.

Car racing is a mentally and physically demanding sport. The track time available to train drivers and test car setups is limited. Race car simulators offer the possibility of safe, efficient, and standardized human-in-the-loop training and testing. We conducted a validation study of a race car simulator by correlating the fastest lap times of 13 drivers during training events in the simulator with their fastest lap times during real-world race events. The results showed that the overall correlation was .57 ( p = .044). Next, the effect of brake pedal stiffness (soft: 5.8 N/mm vs. hard: 53.0 N/mm) on racing performance was investigated in the simulator. Brake pedal stiffness may have an important effect on drivers' lap times, but it is impractical to manipulate this variable on a race car during a real-world test session. Two independent experiments were conducted using different cars and tracks. In each experiment, participants ( N = 6 in Experiment 1 and N = 9 in Experiment 2) drove alternately with the soft and hard pedal in eight 20-min sessions (Experiment 1) or six 15-min sessions (Experiment 2). Two hypotheses were tested: (1) the soft pedal yields faster cornering times for corners that include a long brake zone, and (2) the hard pedal yields more high-frequency brake forces. Experiments 1 and 2 confirmed the second hypothesis but not the first. Drivers were highly adaptable to brake pedal stiffness, and the stiff pedal elicited higher pedal forces and more high-frequent brake pedal inputs. It is concluded that the racing simulator is a valuable tool for driver assessment and for testing adoptations to the human–machine interface.

Research on new automotive systems currently relies on car driving simulators, as they are a cheaper, faster, and safer alternative to tests on real tracks. However, there is increasing concern about the motion cues provided in the simulator and their influence on the validity of these studies. Especially for curve driving, providing large sustained acceleration is difficult in the limited motion space of simulators. Recently built simulators, such as Desdemona, offer a large motion space showing great potential as automotive simulators. The goal of this research is: first, to develop a motion drive algorithm for urban curve driving in the Desdemona simulator; and second, to evaluate the solution through a simulator driving experiment. The developed algorithm, the one-to-one yaw algorithm, is compared to a classical washout algorithm (adapted to the Desdemona motion space) and a control condition where only road rumble is provided. Results show that regarding lateral motion, the absence of cues in the rumble condition is preferred over the presence of false cues in the classical algorithm. “No motion” seems to be favored over “bad motion.” In terms of longitudinal motion, the one-to-one yaw and the classical algorithm are voted better than the rumble condition, showing that the addition of motion cues is beneficial to the simulation of braking. In a general way, the one-to-one yaw algorithm is classified better than the other two algorithms.