An integrated human factors approach to design and evaluation of the driver workspace and interface: Driver perceptions, behaviors, and objective measures

An ergonomic driver workspace and interface design is essential to ensure a healthier and comfortable driving experience in terms of driver perceptions, postures, and interface pressures. Developing more effective methods for driver-side interior design and evaluation, hence, requires thorough investigation of: 1) which perceptual responses are more relevant to ensuring ergonomic quality of a design, 2) the interrelationships among perceptual responses and objective measures, and 3) whether current assumptions regarding driver behaviors, and tools for specifying these behaviors, are valid for the design and evaluation. Existing studies, however, have rarely addressed these topics comprehensively, and often have been conducted with unsubstantiated assumptions. In contrast, this work sought to address these topics in a way that jointly considers characteristics of driver perceptions, behaviors, and objective measures to develop an improved design and evaluation methodology for driver workspace and interface, and that can also investigate the validity of implicit assumptions regarding perceptual relevance and drivers' behaviors.

The first part of this work investigated drivers' perceptions in relation to driver workspace design and evaluation. Specifically, it examined the efficacy of several perceptual ratings, when used for evaluating automobile interface design. Results showed that comfort ratings were more effective at distinguishing among interface designs, in contrast to the current common practice of using discomfort ratings for designing and evaluating interface designs. Two distinct decision processes to relate local to global perceptions were also identified (i.e., global comfort as an average of local comforts, and global discomfort predominantly influenced by maximal local discomforts). These findings were observed consistently across age and cultural groups. In addition, this work provided empirical support for an earlier hypothetical comfort/discomfort model, which posited comfort and discomfort are complementary, yet independent entities.

In order to facilitate the integration of driver perceptions and dynamic behaviors into driver workspace design and evaluation, the second part of this work clarified the relationships between perceptual ratings and various types of driver-seat interface pressure. Interface pressure was found to be more strongly related to overall and comfort ratings than to discomfort ratings, which is also in marked contrast with existing work that has focused on identifying association between discomfort and interface pressure. Specific pressure interface requirements for comfortable driver workspace design and evaluation were also provided.

Lastly, this work specified more rigorous driving postures for digital human models (DHMs), based on actual drivers' perceptions, postural sensitivity, and static behavioral characteristics, to facilitate proactive design and evaluation that enables cost/time efficient vehicle development. Drivers' behavioral characteristics observed in this work were applied to the driver workspace design. First, postural sensitivity obtained by using a psychophysics concept has been applied to determination of core seat track ranges. Second, postural data have been used: 1) to review relevant industry standards on driver accommodation, 2) to investigate whether driving postures are bilaterally asymmetric, 3) to provide comfortable joint ranges, and lastly 4) to identify drivers' postural strategies for interacting with a vehicle.

Overall, this work identified three important behavioral characteristics, specifically a bilateral imbalance in terms of interface pressure, bilaterally asymmetric joint posture, and postural strategies identified by cluster analysis. Such characteristics can be embedded in DHMs to describe more accurately actual driver behaviors inside a driver workspace, which is deemed to be a fundamental step to improved virtual ergonomic vehicle design and evaluation. In addition, the strategy-based classification method used in this work can be extended to simulate and predict more complex human motions. Practical and fundamental findings of this work will facilitate efficient and proactive design and evaluation of driver workspace and interface, and will help provide a healthier driving experience for a broader range of individuals.