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

Ergonomics plays an important role in safety, comfort and convenience of occupants in passenger cars. Customers come in different anthropometry; have different preferences and exhibit different seating behaviors while driving a car. Integration of dashboard and in the vehicle has become a challenging task with sophisticated interior styling themes aimed at satisfying the increasing customer demands. The dashboard design is becoming more futuristic, leading to complex integration of parts in the cockpit area. This has a deteriorating effect on the driver knee clearance. In general, the postures of drivers are within a presumable range of prediction. However, there 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 on the dashboard, which has many switches and controls. This could lead to activation of any switches on dashboard including 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-ofcustomary' behaviors and making necessary corrections in the early design phase of the vehicle. In this study, we represent 'outof-customary' driver behavior in the form of a slouched posture for subsequent assessments. This characteristic of driver becomes more pronounced in autonomous vehicles where driver activity 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. Simulation and data analysis are carried out on a varied set of carlines covering a wide range from a roadster to a SUV. The resulting 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