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In the development of an Adaptive Cruise Control (ACC) system, a model-based design process uses a simulation environment with models for sensor data, sensor fusion, ACC, and vehicle dynamics. Previous work has sought to control the dynamics between two vehicles both in simulation and empirical testing environments. This paper outlines a new modular simulation framework for full model- based design integration to iteratively design ACC systems. The simulation framework uses physics-based vehicle models to test ACC systems in three ways. The first two are Model-in-the-Loop (MIL) testing, using scripted scenarios or Driver-in-the-Loop (DIL) control of a target vehicle. The third testing method uses collected test data replayed as inputs to the simulation to additionally test sensor fusion algorithms. The simulation framework uses 3D visualization of the vehicles and implements mathematical driver comfortability models to better understand the perspectives of the driver or passenger.

This study's objective was to characterize thermal-shock errors on a specific Kistler pressure transducer and to determine if a thermal-shock correction algorithm using transducer surface temperature could be developed. Atmospheric measurements were made using a thermal-shock rig which intermittently exposed the transducer to a known heat flux while maintaining atmospheric pressure on the transducer diaphragm. Any change in output is attributable to thermal shock. Surface temperature was measured using a separate eroding-type surface thermocouple. The data showed a strong correlation between heat-flux induced temperature change and thermal shock and were used in a least-squares error estimation algorithm to create a model of the thermal shock as a function of transducer surface temperature. The model was calibrated using baseline measurements and tested against measurements made at different heat flux intensities and exposure duration and frequency.