Accurate prediction of occupant head kinematics is critical for better understanding of head/face injury mechanisms in side impacts, especially far-side occupants. In light of the fact that researchers have demonstrated that muscle activations, especially in neck muscles, can affect occupant head kinematics, a human body finite element (FE) model that considers muscle activation is useful for predicting occupant head kinematics in real-world automotive accidents. In this study, we developed a human body FE model called the THUMS (Total HUman Model for Safety) Version 5 that contains 262 one-dimensional (1D) Hill-type muscle models over the entire body. The THUMS was validated against 36 series of PMHS (Post Mortem Human Surrogate) and volunteer test data in this study, and 16 series of PMHS and volunteer test data on side impacts are presented. Validation results with force-time curves were also evaluated quantitatively using the CORA (CORrelation and Analysis) method. The validation results suggest that the THUMS has good biofidelity in the responses of the regional or full body for side impacts, but relatively poor biofidelity in its local level of responses such as brain displacements. Occupant kinematics predicted by the THUMS with a muscle controller using 22 PID (Proportional-IntegralDerivative) controllers were compared with those of volunteer test data on low-speed lateral impacts. The THUMS with muscle controller reproduced the head kinematics of the volunteer data more accurately than that without muscle activation, although further studies on validation of torso kinematics are needed for more accurate predictions of occupant head kinematics.