Prediction of Involuntary Knee Engagement on Dashboard Controls to Prevent Potential Accidents for Drivers in a Passenger Car

Abstract

<div class="section abstract"><div class="htmlview paragraph">Ergonomics plays an important role in safety, comfort, and convenience of occupants in passenger cars. Customers come in different sizes; have different preferences and exhibit different seating behaviors while driving a car. With sophisticated interior styling themes aimed at satisfying the increasing customer demands, dashboard packaging and its integration in the vehicle has become a challenging task. This has a deteriorating effect on the driver knee clearance since dashboard has penetrated more into cockpit area to house the complex integration. With drivers having significant workload, their postures are within a presumable range of prediction. However, there still exists ‘out-of-customary’ behaviors while driving a vehicle. Drivers tend to sit in a slouched posture, and this leads to an involuntary knee engagement resulting in activation of critical controls like EPB (Electronic Parking Brake). EPB is an Active Safety feature and on activating it, the vehicle stops immediately. If this is not an intended action, it will potentially result in an accident, especially when the vehicle is traveling at a high speed. Although there are several recommended measurement standards by SAE to measure the design intent of vehicle, these do not directly address the situation explained above. The aim of this research is to prevent the involuntary action of knee engagement with dashboard controls by analyzing driver knee clearance in correlation with the ‘out-of-customary’ behaviors and making necessary corrections in the early design phase of the vehicle. In this study, we represent ‘out-of-customary’ driver behavior in the form of a slouched posture for subsequent assessments. This ‘out-of-customary’ characteristic of driver become more pronounced in autonomous vehicles where driver workload is significantly reduced and there are lot more unconventional driver behaviors that are possible. We aim to arrive at a mathematical model that predicts involuntary knee engagement based on architecture parameters for a given vehicle and a given anthropometry. This model can be deployed in early design phase of a vehicle to develop dashboard metrics. This model will act as a guiding principle to specify the threshold knee clearance of driver necessary to avoid potential accidents arising due to ‘out-of-customary’ behaviors.</div></div>