Three computational fluid and gas dynamic methods, UP (Uniform Pressure), ALE (Arbitrary Lagrangian and Eulerian), and CPM (Corpuscular Particle Method), were investigated in this research in an attempt to predict the responses of side crash pressure sensors. Acceleration-based crash sensors have been used extensively in the automotive industry to determine the restraint system firing time in the event of a vehicle crash. The prediction of acceleration-based crash pulses by using computer simulations has been very challenging due to the high frequency and noisy responses obtained from the sensors, especially those installed in crush zones. As a result, the sensor algorithm developments for acceleration-based sensors are largely based on prototype testing. With the latest advancement in the crash sensor technology, side crash pressure sensors have emerged recently and are gradually replacing acceleration-based sensor for side crash applications. Unlike the acceleration-based crash sensors, the data recorded by the side crash pressure sensors exhibits lower frequency and less noisy responses. The lower frequency and less noisy response characteristics are more suitable for CAE prediction. Fifteen benchmark tests, in three groups, were designed and conducted to better understand the pressure responses under different impact conditions and to provide data for the evaluation of the three computational fluid and gas dynamic methods. The first group of benchmark tests included a piston compression test with two different gases being compressed in a container. The second group of benchmark tests consisted of a rigid impactor or a deformable barrier hitting a rectangular steel box with and without a hole as well as at different impact speeds. The third group of benchmark tests involved a rigid impactor or a deformable barrier hitting a vehicle side door with different openings and at different impact speeds. To ensure the robustness of CAE predictions for different test conditions, variables such as, structural design, hole size, hole location, sensor location, impactor type, and impact speed, were considered when designing the benchmark tests. To choose appropriate approaches for side crash pressure sensor predictions, three computational fluid and gas dynamic methods available for SFI (Structure-Fluid Interaction) applications were evaluated in this research. The three methods, UP, ALE, and CPM, were employed to simulate the fifteen benchmark tests and to understand their corresponding numerical performances. The predictions of the benchmark tests including the structure deformation mode and the pressure response are compared to those of the tests. The advantages and limitations of each method for the different variables are discussed in detail based on the results obtained from the numerical simulations. In addition, computation efficiency and user-friendliness for the three methods are also compared. The main objective of this research is to identify the most appropriate methods to predict pressure sensor responses and to enable computer simulations for the development of restraint deployment algorithms associated with the side crash pressure sensors. It is also hoped that the three methods can be enhanced and/or developed further through this research to expand their applications in other SFI problems in the future.