With a goal to help develop pressure sensor calibration and deployment algorithms using computer simulations, an Arbitrary Lagrangian Eulerian (ALE) approach was adopted in this research to predict the responses of side crash pressure sensors for unitized vehicles. For occupant protection, acceleration-based crash sensors have been used in the automotive industry to deploy restraint devices when vehicle crashes occur. With improvements in the crash sensor technology, pressure sensors that detect pressure changes in door cavities have been developed recently for vehicle crash safety applications. Instead of using acceleration (or deceleration) in the acceleration-based crash sensors, the pressure sensors utilize pressure change in a door structure to determine the deployment of restraint devices. The crash pulses recorded by the acceleration-based crash sensors usually exhibit high frequency and noisy responses. Different from those of the acceleration-based crash sensors, the data obtained from the pressure sensors exhibit lower frequency and less noisy responses. Due to its ability to discriminate crash severities and allow the restraint devices to deploy earlier, the pressure sensor technology has gained its popularity for side crash applications. The lower frequency and less noisy characteristics are also more suitable for non-linear finite element codes to predict.Fifteen different benchmark problems were designed and tested in the first stage of this research to investigate the responses of pressure sensors in different impact conditions and the capabilities of the ALE method in the predictions of different pressure sensor responses. The fifteen benchmark problems were divided into three groups to examine the capabilities of the ALE method in detail. Different structures, gases, hole locations, sensor locations, hole sizes, impact speeds, and impactors, were chosen in the fifteen benchmark problems so that the sensitivity of the pressure responses to different factors could be obtained and understood. Computer simulations conducted by employing the ALE method for all fifteen benchmark problems were compared to their corresponding theoretical solutions or test data. The correlations between the tests and the computer simulations were found to be reasonable as reported in a paper published previously.The research was advanced into its final stage, full vehicle tests, after the positive results obtained from the benchmark study. The full vehicle study included two major vehicle architectures, body-on-frame and unitized, that are commonly used to design vehicles in the automotive industry. This paper focuses on the unitized vehicles. A total of thirteen tests, including different body styles, powertrains, drivetrains, test modes, and impact speeds, were investigated.A simulation methodology was developed in this study to correlate the structural responses and to predict the pressure sensor responses for unitized vehicles. The results obtained from the developed methodology using the ALE simulations are compared to those obtained from the corresponding tests. In the full vehicle study, low speed impact conditions were found to be more challenging to predict compared to those of the high speed impact conditions. This is because the pressure responses for the low speed impacts are usually much weaker than those of the high speed impacts. The numerical errors obtained from the simulations become more significant when the magnitudes of the pressure responses are low. The numerical errors induced by the coupling of Lagrangian and Eulerian calculation need to be distinguished and ignored (or filtered) when processing the pressure information. The slopes, peak values, and overall shapes of the predicted pressure responses correlate reasonably with most of the full vehicle tests selected. The correlations of the pre-peak responses are better than those of the post-peak responses which involve air leakage. The oblique pole, IIHS MDB, and FMVSS 214 MDB test modes create distinct door deformations and pressure responses which can be predicted by the computer simulations reasonably. Sensor engineers analyzed the results obtained from a FMVSS 214 simulation and confirmed that replacing the test data with the predicted results would result in the same deployment algorithm.