Search Results

This paper describes a vision-based vehicle detection system for a blind spot warning function. This detection system has been designed to provide ample performance as a driving safety support system, while streamlining the image processing algorithm so that it can be processed using the computational power of an existing ECU. The procedure used by the system to detect a vehicle in a blind spot is as follows. The system consists of four functional components: obstacle detection, velocity estimation, vertical edge detection, and final classification. In obstacle detection, a predicted image is generated under the assumption that the road surface is a perfectly flat plane, and then an object is detected based on a histogram that is created by comparing the predicted image and an actually observed image. The velocity of the object is estimated by tracking the histogram over time, assuming that both the object and the host vehicle are traveling in the same direction.

The present study investigated the aerodynamic pitching stability of sedan-type vehicles under the influence of A- and C-pillar geometrical configurations. The numerical method used for the investigation is based on the Large Eddy Simulation (LES) method. Whilst, the Arbitrary Lagrangian-Eulerian (ALE) method was employed to realize the prescribed pitching oscillation of vehicles during dynamic pitching and fluid flow coupled simulations. The trailing vortices that shed from the A-pillar and C-pillar edges produced the opposite tendencies on how they affect the aerodynamic pitching stability of vehicles. In particular, the vortex shed from the A-pillar edge tended to enhance the pitching oscillation of vehicle, while the vortex shed from the C-pillar edge tended to suppress it. Hence, the vehicle with rounded A-pillar and angular C-pillar exhibited a higher aerodynamic damping than the vehicle with the opposite A- and C-pillars configurations.

A road vehicle’s cornering motion is known to be a compound motion composed mainly of forward, sideslip and yaw motions. But little is known about the aerodynamics of cornering because little study has been conducted in this field. By clarifying and understanding a vehicle’s aerodynamic characteristics during cornering, a vehicle’s maneuvering stability during high-speed driving can be aerodynamically improved. Therefore, in this study, the aerodynamic characteristics of a vehicle’s cornering motion, i.e. the compound motion of forward, sideslip and yaw motions, were investigated. We also considered proposing an aerodynamics evaluation method for vehicles in dynamic maneuvering. Firstly, we decomposed cornering motion into yaw and sideslip motions. Then, we assumed that the aerodynamic side force and yaw moment of a cornering motion could be expressed by superposing linear expressions of yaw motion parameters and those of sideslip motion parameters, respectively.

In the present study, two kinds of simplified vehicle models, which can reproduce flow structures around the two sedan-type vehicles in the previous study, are constructed for the object and the unsteady flow structures are extracted using Large-Eddy Simulation technique. The numerical results are validated in a stationary condition by comparing the results with a wind-tunnel experiment and details of steady and unsteady flow characteristics around the models, especially above the trunk deck, are investigated. In quasi- and non- stationary manner with regard to vehicle pitch motion, unsteady flow characteristics are also investigated and their relations to an aerodynamic stability are discussed.

A numerical method specially designed to predict unsteady aerodynamics of road vehicle was developed based on unstructured Large-Eddy Simulation (LES) technique. The code was intensively optimized for the Earth Simulator in Japan to deal with the excessive computational resources required for LES, and could treat numerical meshes of up to around 120 million elements. Moving boundary methods such as the Arbitrary Lagrangian-Eulerian (ALE) or the sliding method were implemented to handle dynamic motion of a vehicle body during aerodynamic assessment. The method can also model a gusty crosswind condition. The method was applied to three cases in which unsteady aerodynamics are expected to be crucial.