The objective of this study was to investigate the aerodynamics of a road vehicle during cornering. We focused on steady-state cornering and divided the vehicle motion into two components, a yaw rotation and a sideslip motion. The fluid-dynamic characteristics of the vehicle in steady-state cornering and the effects of the two motion components were investigated both by a towing tank experiment and by numerical simulation. The results indicate that both of the motion components generated fluid-dynamic centripetal force and fluid-dynamic yaw moments in opposite directions. The distributions of pressure change on the vehicle body, generated by the motion components, were numerically visualized. The physical mechanisms that generated these aerodynamic characteristics are discussed.

Path planning in dynamic environments is still a challenging issue with autonomous mobile robots. Current methods lack adaptability to various passing scenarios, a variety of passing trajectories including an acceleration path, or immediacy in planning time, which require human-aware navigation. In this study, we propose Dynamic Waypoint Navigation (DWN), which is a model-based adaptive real-time trajectory planning method. DWN first predicts human-robot path interference and the time and position of the interference on the basis of the measured velocity of humans. It then dynamically designates several waypoints considering the time delay of both calculation time and robot travel time. Then, DWN generates several trajectories by combining different speeds (default, acceleration, and deceleration) and paths (default, right, and left) and selects the best trajectory in terms of an interference-avoidance energy cost based on the degree of velocity-vector change. DWN can also output a trajectory within 0.5 s to immediately adapt to changes in human behavior and adopt a simple mathematical model and algorithm to enable easy expansion. Simulation and experimental results reveal that the DWN can adequately select a time-efficient trajectory in real-time and adaptively change a trajectory depending on human movement.

In this study, an aerodynamics simulation of a road vehicle in a steady-state cornering motion is conducted, and the aerodynamic effects of its postural change in the roll direction are discussed. The numerical results indicated an aerodynamic centrifugal force induced by the roll-on. This aerodynamic effect was decomposed into two causes: a revolution of force direction with a rotation of the vehicle's body, and a change in aerodynamic force distribution on the vehicle's body according to changes in flow structures around the vehicle. From a quantitative evaluation, neither factor is negligible in the aerodynamics of the vehicle during steady-state cornering. The side force distribution in the vehicle's longitudinal direction, the pressure changes on the vehicle's body, and the total pressure distributions around the vehicle were visualized, and aerodynamic phenomena were discussed. The changes in flow caused by roll variations were observed mainly around the front wheels. Nomenclature  = Slip angle of a vehicle C S = Aerodynamic side force coefficient CS,flow = Aerodynamic side force coefficient induced by a change in flow phenomena CS,lift = Aerodynamic side force coefficient apparently changed by a rotation of lift and side forces C L = Aerodynamic lift force coefficient C pt = Total pressure coefficient CYM = Aerodynamic yaw moment coefficient CS,flow = Aerodynamic yaw moment coefficient induced by a change in flow phenomena C YM,pitch = Aerodynamic yaw moment coefficient apparently changed by a rotation of pitch and yaw moments C = Variation of aerodynamic coefficient C caused by a cornering motion G = Roll stiffness of a road vehicle 2  = Roll angle of vehicle M = Sprung mass of vehicle r = Yaw rate (yaw angular velocity) r' = Nondimensional yaw rate; r' = r / (U/L) U = Running velocity of vehicle u = Forward speed (longitudinal velocity of vehicle); u = U cos v = Slip speed (lateral velocity of vehicle); v = U sin wr,wor = Valuable in cases with and without roll angle

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Human symbiotic mobile robots are required to smoothly reach destinations while avoiding humans. Human-intent information, e.g., a moving direction, must be carefully estimated since its lack leads to the hesitation and repetitious avoidance. Conventional studies address human intent estimation and conveyance but do not consider cases of failing communication as a systematic framework, even though the intent is essentially difficult for humans to estimate due to its interiority. In response to this problem, we propose a framework of error-tolerant navigation (ETN) with a process to actively estimate the human intent by iterative interaction from the robot. As a preliminary study, we focus on ‘the intent conveyance from robot to human’ and ‘its achievement’ as core information. The ETN estimates interference possibility to determine the need for inducement, human awareness (HA) to select an inducement method, and inducement achievement (IA) to judge the need for action again. If the ETN estimates the interference, the robot provides inducements according to HA, e.g., route indication when HA is high or voice/physical interaction when HA is low. Each inducement corresponds to an expected behavior change in the human. IA is calculated from the difference between the expected and actual changes. If the robot observes no change within a specified time after the inducement, it executes inducements with a stronger intent conveyance. When IA is none after the strongest action, it selects another route. This error-collection loop in the ETN could prevent a fatal mistake by recognizing a small mistake and recovering it. The static and dynamic experimental results indicated that the ETN could achieve smoother human movement and reduce psychological burden by correcting the robot behaviors, compared with a conventional navigation system, which can contribute to constructing a practical ETN framework.