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Motion sickness in road vehicles may become an increasingly important problem as automation transforms drivers into passengers. The University of Michigan Transportation Research Institute has developed a vehicle-based platform to study motion sickness in passenger vehicles. A test-track study was conducted with 52 participants who reported susceptibility to motion sickness. The participants completed in-vehicle testing on a 20-minute scripted, continuous drive that consisted of a series of frequent 90-degree turns, braking, and lane changes at the U-M Mcity facility. In addition to quantifying their level of motion sickness on a numerical scale, participants were asked to describe in words any motion-sickness-related sensations they experienced.

The interior layout of passenger cars and light trucks is substantially aided by SAE occupant packaging tools, which include the SAE J941 eyellipse, SAE J287 reach curves, and the seating accommodation model in SAE J4004. Most of these tools were developed based on posture and position data from drivers, although an eyellipse and head contour are available for fixed-seat passenger positions. This paper reviews the current SAE occupant packaging tools and related industry practice in the context of current concepts for highly automated vehicles, considering SAE levels 4 and 5. Concepts that have driver controls for occasional use and vehicles with no driver controls are examined. Gaps in the current knowledge and tools are reviewed to establish priorities for research and development of new standards and recommended practices.

Driver upper-extremity postures and activities were manually coded in 9856 video frames from 165 drivers in 100 vehicles that were instrumented with interior cameras as part of the Connected Vehicle Safety Pilot Model Deployment study. Drivers had left, right, and both hands on the steering wheel in 64%, 46%, and 28%, respectively, of frames in which the hand placements could be determined. The driver’s left elbow was in contact with the door or armrest in 18% of frames, and the driver’s right elbow was contacting the center console armrest in 29% of frames. Men were more likely than women to use both the left and right armrests. Women had approximately the same percentage of armrest use across vehicles, but men’s usage differed widely, suggesting that armrest design may influence whether people of different statures can use the armrests comfortably.

Analyzing dynamic postures of vehicle occupants in various situations is valuable for improving occupant accommodation and safety. Accurate tracking of an occupant’s head is of particular importance because the head has a large range of motion, controls gaze, and may require special protection in dynamic events including crashes. Previous vehicle occupant posture studies have primarily used marker-based optical motion capture systems or multiple video cameras for tracking facial features or markers on the head. However, the former approach has limitations for collecting on-road data, and the latter is limited by requiring intensive manual postprocessing to obtain suitable accuracy. This paper presents an automated on-road head tracking method using a single Microsoft Kinect V2 sensor, which uses a time-of-flight measurement principle to obtain a 3D point cloud representing objects in the scene at approximately 30 Hz.