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This study presents a methodology for comparative analysis of seat and suspension parameters on a system level to achieve minimum occupant head displacement and acceleration, thereby improving occupant ride comfort. A lumped-parameter full-vehicle ride model with seat structures, seat cushions and five occupants has been used. Two different vehicle masses are considered. A low amplitude pulse signal is provided as the road disturbance input. The peak vertical displacement and acceleration of the occupant’s head due to the road disturbance are determined and used as measures of ride comfort. Using a design of experiments approach, the most critical seat cushion, seat structure and suspension parameters and their interactions affecting the occupant head displacement and acceleration are determined. An optimum combination of parameters to achieve minimum peak vertical displacement and acceleration of the occupant’s head is identified using a response surface methodology.

This study was conducted to assess the occupant restraint use and injury risks by seating position. The results were used to discuss the merit of selected warning systems. The 1989-2015 NASS-CDS and 2017-2021 CISS data were analyzed for light vehicles in all, frontal and rear tow-away crashes. The differences in serious injury risk (MAIS 3+F) were determined for front and rear seating positions, including the right, middle and left second-row seats. Occupancy and restraint use were determined by model year groups. Occupancy relative to the driver was 27% in the right-front (RF) and 17% in the second row in all crashes. About 39% of second-row passengers were in the left seat, 15% in the center seat and 47% in the right seat. Restraint use was lower in the second row compared to front seats. It was 43% in the right-front and 32% in the second-row seats in all crashes involving serious injury. Restraint use increased with model year groups.

This paper presents results of two surveys, namely, a photographic measurements survey and a rider survey, conducted to determine how the type and origin of a motorcycle related to motorcycle dimensions, rider characteristics, seating posture, and motorcycle controls and displays. In the photographic survey, 12 most popular motorcycles covering three types (cruiser, sport, and touring) and three origins (Europe, Asia and North America) were measured from photographs taken in a standardized procedure with and without a rider. The data showed that the Asian and North American cruisers were very similar in all dimensions. These include seat height, seat to handlebar location, seat to foot rest location, foot rest size, and handgrip stance. This resulted in similar rider posture. North American sport motorcycles were more like cruisers than the Asian and European sport motorcycles.

This paper presents results of a three-phase research project aimed at understanding how future automotive interior materials should be selected or designed to satisfy the needs of the customers. The first project phase involved development of 22 five-point semantic differential scales to measure visual, visual-tactile, and evaluative characteristics of the materials. Some examples of the adjective pairs used to create the semantic differential scales to measure the perceptual characteristics of the material are: a) Visual: Light vs. Dark, Flat vs. Shiny, etc., b) Visual-Tactile: Smooth vs. Rough, Slippery vs. Sticky, Compressive vs. Non-Compressive, Textured vs. Non-Textured, etc., c) Evaluative (overall perception): Dislike vs. Like, Fake vs. Genuine, Cheap vs. Expensive, etc. In the second phase, 12 younger and 12 older drivers were asked to evaluate a number of different automotive interior materials by using the 22 semantic differential scales.

This study was conducted to develop and validate a multidimensional measure of shift quality as perceived by drivers during kick-down shift events for automatic transmission vehicles. As part of the first study, a survey was conducted among common drivers to identify primary factors used to describe subjective gear-shifting qualities. A factor analysis on the survey data revealed four semantic subdimensions. These subdimensions include responsiveness, smoothness, unperceivable, and strength. Based on the four descriptive terms, a measure with semantic scales on each subdimension was developed and used in an experiment as the second study. Twelve participants drove and evaluated five vehicles with different gear shifting patterns. Participants were asked to make kick-down events with two different driving intentions (mild vs. sporty) across three different speeds on actual roadway (local streets and highway).

Seat comfort is a highly subjective attribute and depends on a wide range of factors, but the successful prediction of seat comfort from a group of relevant variables can hold the promise of eliminating the need for time-consuming subjective evaluations during the early stages of seat cushion selection and development. This research presents the subjective seat comfort data of a group of 30 participants using a controlled range of seat foam samples, and attempts to correlate this attribute with a) the anthropometric and demographic characteristics of the participants, b) the objective pressure distribution at the body-seat interface and c) properties of the various foam samples that were used for the test.

Nowadays, the automotive industry is experiencing the advent of unprecedented applications with connected devices, such as identifying safe users for insurance companies or assessing vehicle health. To enable such applications, driving behavior data are collected from vehicles and provided to third parties (e.g., insurance firms, car sharing businesses, healthcare providers). In the new wave of IoT (Internet of Things), driving statistics and users’ data generated from wearable devices can be exploited to better assess driving behaviors and construct driver models. We propose a framework for securely collecting data from multiple sources (e.g., vehicles and brought-in devices) and integrating them in the cloud to enable next-generation services with guaranteed user privacy protection.

This paper presents results of a five phase study conducted to evaluate touch feel and appearance of door armrest materials. Seven different production door armrests with different material characteristics such as softness, smoothness, compressibility, texture, etc. were evaluated. In the first phase, the subjects seated in a vehicle buck in their preferred seating position with the armrests adjusted at their preferred heights, provided ratings on a number of touch feel and appearance of the door armrest materials using 5-point semantic differential scales. In the second phase, the armrests were presented to each subject in all possible pairs and they were asked to select preferred armrest material in each pair.

The automotive interior suppliers are challenged to develop materials, that not only perform functionally, but also provide the right combination sensory experience (e.g. visual appeal, tactile feeling) and brand differentiation at very competitive costs. Therefore, the objective of this research presented in this paper is to develop a methodology that can be used to measure customer perception of interior materials and to come up with a unique system for assessing value of different interior materials. The overall methodology involves the application of a number of psychophysical measurement methods (e.g. Semantic Differential Scaling) and statistical methods to assess: 1) overall customer perceived quality of materials, 2) elements (or attributes) of perception, and 3) value of materials from OEM's viewpoint in terms of the measurement of perception of quality divided by a measure of cost.