Robust Truck Cabin Layout Optimization Using Advanced Driver Variance Models

Abstract

One important source of variance in the performance and success of products designed for use by people is the people themselves. In many cases, the acceptability of the design is affected more by the variance in the human users than by the variance attributable to the hardware from which the product is constructed. Consequently, optimization of products used by people may benefit from consideration of human variance through robust design methodologies.We propose that design under uncertainty methodologies can be utilized to generate designs that are robust to variance among users, including differences in age, physical size, strength, and cognitive capability. Including human variance as an inherent part of the product optimization process will improve the overall performance of the product (be it comfort, maintainability, cognitive performance, or other metrics of interest) and could lead to products that are more accessible to broader populations, less expensive, and safer. A case study involving the layout of the interior of a heavy truck cab is presented, focusing on simultaneous placement of the seat and steering wheel adjustment ranges. Tradeoffs between adjustability/cost, driver accommodation, and safety are explored under this paradigm.

Simulated effect of driver and vehicle interaction on vehicle interior layout

“…Since eye location is important for the field of view, and the location of the center of the hips is closely related to the seat location and the lower body posture, these variables are selected for the comparison. The results from the physics-based method with 0 N m pedal reaction moment and the CPM show good agreement for the center of hip and eye locations with an average of maximum difference of 0.039 m in Eyey reHip followed by 0.033 m in ðHipx reBOFÞ and 0.024 m in Eyez reHip (Parkinson and Reed, 2005;Reed et al, 2002). In other words, the proposed method gives accurate results not only for accommodation, but also for the vision.…”

“…Validation of the posture prediction is assessed with the comparison of center of hip locations relative to the BOF in x direction ðHipx reBOFÞ, eye locations relative to the center of hips in x direction ðEyex reHipÞ, and eye locations relative to the center of hips in z direction ðEyez reHipÞ, with those obtained from the CPM (Parkinson and Reed, 2005;Reed et al, 2002). Since eye location is important for the field of view, and the location of the center of the hips is closely related to the seat location and the lower body posture, these variables are selected for the comparison.…”

“…It was shown that the clearance between the waist and steering wheel decreases as waist size increases; thus, obese individuals prefer to move further from the steering wheel than non-obese subjects. The cascade prediction model (CPM) for posture predictions was reported (Parkinson and Reed, 2005;Reed et al, 2002). The CPM method was extended to SAE Class-A vehicles (passenger cars and trucks with design seat heights less than 405 mm) for optimizing a vehicle cabin layout (Parkinson and Reed, 2006;Gordon et al, 1988Gordon et al, , 1989.…”

Experiential Conjoint Analysis: An Experience-Based Method for Eliciting, Capturing, and Modeling Consumer Preference

“…However, in many professional settings, the effect of a product's usability transcends satisfaction, affecting factors such as safety or efficiency [52,53]. Layouts of controls/interfaces have previously been optimized and evaluated with respect to anthropometrics and eye-gaze data [55], but it is crucial to consider user feedback, especially in situations where a product's usability affects efficiency or safety [56][57][58]. VR technologies eliminate the need for physical prototypes and allow users to gain an understanding of and evaluate the layout of controls/interfaces with respect to usability.…”

Including Preference in Anthropometry-Driven Models for Design

“…Realistic posturing is required for any use of manikins in design [19,4]. Sometimes, this posturing is performed manually by the designer, but to improve accuracy and repeatability it is increasingly done algorithmically.…”