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Pedal misapplication (PM) is an error in which a driver unintentionally presses the wrong pedal. When drivers mistake the accelerator pedal for the brake pedal, the vehicle experiences a sudden unintended acceleration, and the consequences can be severe. A brief history of PM is covered, and several novel studies of PM are described. The goals of these studies were as follows: 1. Identify and analyze multiple samples of PM crashes from a variety of data sources using both established and novel methods to gain new insight into the characteristics and frequency of PM crashes. 2. Use the confirmed, real-world PM crash data to develop a custom vehicle dynamics simulation and evaluate the overall potential safety benefit of a theoretical PM advanced driver assistance system. Using an established keyword search identification method and two unique crash datasets, a PM crash frequency of approximately 0.2% of all crashes was found. These PM crashes were typically rear-end or road departure crashes in moderate- to low-speed commercial or residential areas. Female drivers and elderly drivers were more often involved in these PM crashes, which generally featured slightly lower injury severities and often involved inattention or fatigue. Anecdotally, PM crash narratives contained repeated evidence of unexpected events, driver inexperience, distraction, shoe-malfunction, extreme stress, and medical conditions/emergencies. A novel PM crash identification algorithm was developed to detect PMs from time-series pre-crash data. This algorithm was applied to a sample of crashes with event data recorder data available, and a frequency of 4.3% of eligible crashes were found to have exhibited PM behavior, suggesting that PM crashes may be more prevalent than previously thought. While the data from these crashes suggested that a PM occurred, this dataset lacked sufficient data regarding driver intention, which is necessary to confirm each crash as PMs. The characteristics of these PM-like crashes were analyzed and found to be largely similar to those of previous samples, with notable exceptions for higher proportions of male drivers, higher travel speeds, and higher maximum injury severities. More robust data from a naturalistic driving study (NDS) was acquired, and the novel algorithm was applied to all of the sample’s eligible crashes. Because the NDS data contained more data elements such as driver-facing video, crashes that exhibited PM behavior were individually inspected to confirm PM. This produced a PM crash frequency of 1.1%. The characteristics of these confirmed PM crashes were investigated, but a small sample size limits the generalizability of the results. Lastly, crash data from confirmed, real-world PM crashes was used to inform a custom vehicle dynamics model into which a theoretical PM advanced driver assistance system was simulated. The effect of the accelerator suppression system on crash avoidance and mitigation was evaluated to assess its potential safety benefit, which was found to be highly dependent on system threshold values and largely underwhelming in the absence of supplemental braking. The results indicated that a system that detected PM, suppressed acceleration, and applied braking could provide a substantially higher safety benefit.

Hot stamped boron steels, such as Usibor® 1500, have been increasingly used in automotive structural components for light-weighting and impact resistance. Classified as an ultra-high strength steel, these alloys have superior strength with tensile strengths exceeding 1500 MPa. The rapid heating and cooling thermal cycle during resistance spot welding can significantly alter the martensitic base metal microstructure, resulting in formation of coarse-grained and subcritical heat-affected zones (CGHAZ and SCHAZ) with inferior mechanical properties. The martensitic CGHAZ is adjacent to the weld nugget and experiences the most time above the AC3, which allows for austenite grain growth. The SCHAZ is next to the unaffected base metal and does not reach the AC1¬ during welding, thus the base metal microstructure is over-tempered into cementite and ferrite. The present research aims at developing the fundamental knowledge of plastic deformation and fracture behaviors of ultra-high strength steel resistance spot welds. As a resistance spot weld comprises highly inhomogeneous microstructure, the overall research approach is based on studying the local (or microstructure-dependent) mechanical properties for individual regions in the weld as well as their interactions with weld geometry on the deformation behavior. Specifically, optimal welding parameters are determined to produce welds of appropriate nugget diameter for 2T Usibor 1500 with a gauge thickness of 1.5 mm. Micro-hardness mapping and metallographic analysis allow for characterization of the weld metal, CGHAZ, SCHAZ, and base metal of the spot weld. Quasi-static tensile testing with digital image correlation (DIC) is used to determine the local stress-strain behaviors of each region using bulk microstructural samples created in a Gleeble® thermal-mechanical simulator. Conventional and innovative resistance spot weld mechanical testing methods are used to generate more knowledge on the deformation of joints under various loading conditions. Sectioned tensile shear testing and single-sided wedge testing procedures have been established to use 2-D DIC for in situ observations of local deformation on the exposed weld cross-section during testing. A mechanical model, developed using Abaqus finite element analysis (FEA) code by incorporating the local constitutive behaviors of RSW joints, is used to better understand the effect of weld nugget profiles on the stress state present during loading. The FEA model is validated by comparing the simulated strain fields to the experimentally measured strain fields. The knowledge generated in this study can help improve the accuracy of predicting spot weld fracture of ultra-high strength steels in the automotive industry. Particularly, the fine-resolution, coupon-scale model developed in this research will be useful for implementation into coarse-resolution, full-scale models for crash simulation and optimization of vehicle components.

Design and analysis of seat and restraint systems for crash simulation