Search Results

This paper proposes a novel method of verifying comprehensive driver model used for the evaluation of driving safety systems, which is achieved by coupling the traffic simulation and the driving simulator (DS). The method consists of three-step procedure. In the first step, an actual driver operates a DS vehicle in the traffic flow controlled by the traffic simulation. Then in the next step, the actual driver is replaced by a driver model and the surrounding vehicle maneuvers are replayed using the recorded data from the first step. Then, the maneuver by the driver model is compared directly with the actual driver's maneuver along the simulation time steps.

Grip feeling is an important facet in vehicle dynamics evaluation from a driver satisfaction and enjoyment standpoint. To improve grip feeling, we analyzed the subjective comments from test driver's about grip feeling and an evaluated human sensitivity to lateral motion. As a result, we found that drivers evaluate transient grip feeling according to the magnitude of lateral jerk. Next, we analyzed what vehicle parameters affect lateral jerk by using theoretical equations. As a result, we found that cornering power is an important parameter, especially the cornering power of rear tires as they can be create larger lateral jerk than can front tires.

This study aims at the development of a projection pattern that is capable of shortening the time required by a driver to perceive a pedestrian at night when a vehicle’s high beams are utilized. Our approach is based on the spatio-temporal frequency characteristics of human vision. Visual contrast sensitivity is dependent on spatiotemporal frequency, and maximum contrast sensitivity frequency varies depending on environmental luminance. Conventionally, there are several applications that utilize the spatio-temporal frequency characteristics of human vision. For example, the National Television System Committee (NTSC) television format takes into consideration low-sensitivity visual characteristics. In contrast, our approach utilizes high-sensitivity visual characteristics based on the assumption that the higher contrast sensitivity of spatio-temporal frequencies will correlate more effectively with shorter perception times.

We investigated a lighting method that supports pedestrian perception by vehicle drivers. This lighting method makes active use of visual characteristics such as the spatio-temporal frequency of contrast sensitivity. Using reasonable parameter values derived from preliminary experiments using a Campbell-Robson chart, we determined a suitable lighting pattern that improves the driver's pedestrian perception. In order to assess the influence of visual characteristics on a reaction-time-dependent task, such as pedestrian perception in nighttime, tests were performed in the target environment, the results of which validated the proposed method.

Vehicle body movements that occur during cornering have a strong influence on the evaluation of ride and handling. As a first step, we analyze subjective comments from trained drivers and find that the sense of vision played a major part in cornering feel. As a result of quantitative evaluations, we hypothesize that smaller time lag between roll angle and pitch angle made cornering feel better. We perform a human sensitivity evaluation, which confirmed this hypothesis. Given this result, we derive analytical equations for the roll center kinematics and the damping characteristics, in order to find a theoretical condition for the time lag of 0sec (giving a good cornering feel). We verify this by experiment.

This study focuses on fluctuations in the aerodynamic load acting on a hatchback car model under steady-state conditions, which can lead to degeneration of vehicle motion performance due to excitation of vehicle vibrations. Large eddy simulations were first conducted on a vehicle model based on a production hatchback car with and without additional aerodynamic devices that had received good subjective assessments by drivers. The numerical results showed that the magnitudes of the lateral load fluctuations were larger without the devices at Strouhal numbers less than approximately 0.1, where surface pressure fluctuations indicated a negative correlation between the two sides of the rear end, which could give rise to yawing and rolling vibrations. Based on the numerical results, wind-tunnel tests were performed with a 28%-scale hatchback car model.

Accurate prediction of occupant head kinematics is critical for better understanding of head/face injury mechanisms in side impacts, especially far-side occupants. In light of the fact that researchers have demonstrated that muscle activations, especially in neck muscles, can affect occupant head kinematics, a human body finite element (FE) model that considers muscle activation is useful for predicting occupant head kinematics in real-world automotive accidents. In this study, we developed a human body FE model called the THUMS (Total HUman Model for Safety) Version 5 that contains 262 one-dimensional (1D) Hill-type muscle models over the entire body. The THUMS was validated against 36 series of PMHS (Post Mortem Human Surrogate) and volunteer test data in this study, and 16 series of PMHS and volunteer test data on side impacts are presented. Validation results with force-time curves were also evaluated quantitatively using the CORA (CORrelation and Analysis) method.

Numerical analyses of head and neck response during side impact are presented in this paper. A mathematical human model for side impact simulation was developed based on previous studies of other researchers. The effects of muscular activities during severe side impact were analyzed with the use of this model. This study shows that the effect of muscular activities is significant especially if the occupant is prepared to resist the impact. This result suggests that the modeling of muscles is important for the simulation of real accident situation.