Adapted particle swarm optimization algorithm–based layout design optimization of passenger car cockpit for enhancing ergonomic reliability

Abstract

The mechanical reliability problem of passenger car cockpit facilities layout is increasingly complex and has potential and uncertain risks for human safety while the number of private cars is increasing. A new system of layout design optimization is proposed to solve this problem. First, the optimization sequences of facilities are determined using a hybrid method of multiple-attribute decision-making and entropy. Second, the degree of feeling crowded in the cockpit layout can be adjusted based on customers’ preference. Third, an adapted particle swarm optimization algorithm is proposed to solve the problem of three-dimensional layout optimization in car cockpit human–machine interface according to the ergonomic principles, and the adapted algorithm called smoothing iteration particle swarm optimization is contrasted with those of other common algorithms to demonstrate its advantages. Finally, the optimized layout is analyzed by virtual simulations and compared with the original layout to show the feasibility and effectiveness of the proposed design system. Analysis results indicate that the optimized layout by the new particle swarm optimization can make the operation easier and safer than the original one to enhance ergonomic reliability.