Objective: Traffic fatalities among motorcycle users are intolerably high in Thailand. They account for 73% of the total number of road fatalities. Children are also among these victims. To improve countermeasures and design of protection equipment, understanding the biomechanics of motorcycle users under impact conditions is necessary. The objective of this work is to analyze the overall kinematics and injuries sustained by riders and child pillion passengers in various accident configurations. Methods: Motorcycle accident data were analyzed. Common accident scenarios and impact parameters were identified. Two numerical approaches were employed. The multibody model was validated with a motorcycle crash test and used to generate possible accident cases for various impact conditions specified to cover all common accident scenarios. Specific impact conditions were selected for detailed finite element analysis. The finite element simulations of motorcycle-to-car collisions were conducted to provide insight into kinematics and injury mechanisms. Results: Global kinematics found when the motorcycle’s front wheel impacts a car (config-MC) highlighted the translation motion of both the rider and passenger toward the impact position. The rider’s trunk impacted the handlebar and the head either impacted the car or missed. The hood constituted the highest head impact occurrence for this configuration. The child mostly impacted the rider’s back. Different kinematics were found when car impacted the lateral side of the motorcycle (config-CM). Upper bodies of both rider and child were laterally projected toward the car front. The windshield constituted the highest proportion of head impacts. The hood and A-pillar recorded a moderate proportion. The rider in finite element simulations with config-MC experienced high rib stress, lung strain, and pressure beyond the injury limit. A high head injury criterion was observed when the head hit the car. However, the simulation with config-CM exhibited high lower extremities stress and lung pressure in both occupants. Hyperextension of the rider’s neck was observed. The cumulative strain damage measure of the child’s brain was higher than the threshold for diffuse axonal injury (DAI). Conclusions: This study revealed 2 kinematics patterns and injury mechanisms. Simulations with config-MC manifested a high risk of head and thorax injury to the rider but a low risk of severe injury to the child. Thorax injury to the rider due to handlebar impact was only found in simulations with config-MC. However, a high risk of skull, lower extremity, brain, and neck injuries were more pronounced for cases with config-CM. A high risk of DAI was also noticed for the child. In simulations with config-CM the child exhibited a higher risk of severe injury.

The goal of this work is to compute the eco-driving cycles for vehicles equipped with internal combustion engines by using a genetic algorithm (GA) with a focus on reducing energy consumption. The proposed GA-based optimization method uses an optimal control problem (OCP), which is framed considering both fuel consumption and driver comfort in the cost function formulation with the support of a tunable weight factor to enhance the overall performance of the algorithm. The results and functioning of the optimization algorithm are analyzed with several widely used standard driving cycles and a simulated real-world driving cycle. For the selected optimal weight factor, the simulation results show that an average reduction of eight percent in fuel consumption is achieved. The results of parallelization in computing the cost function indicates that the computational time required by the optimization algorithm is reduced based on the hardware used.