Thiag Subbian

Optimization of a vehicle restraint system using a genetic algorithm

In an attempt to make vehicle restraint systems more effective in protecting occupants, many advanced safety technologies have been introduced. These advanced technologies are mostly adaptive technologies. The ability of a restraint system to adapt itself to crash parameters like crash speed and type, occupant size, and belt-usage status, offers possible enhancements in occupant protection. Designing a restraint system boils down to the determination of the design variables of either the restraint technologies or vehicle interiors. A restraint system of adaptive technologies involves much more design variables than a restraint system containing only load-limited belts and dual stage inflators, possibly posing a challenge to safety engineers. In this paper, a genetic algorithm (GA) tailored for restraint system optimization will be presented. Two restraint systems, one for the driver side and one for the passenger side, containing a variety of advanced safety technologies will be used as examples to demonstrate the feasibility of this new tool in optimizing advanced restraint systems. The efficiency of this optimization tool and its application to evaluating the net benefit of adaptive technologies will be discussed at the end.