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Today’s automobiles include more electronics features and functions than at any time in history. From engine controller to crash sensing and passenger protection, all the way to automated driving, a complex network of electronic sensors and controls is being integrated into most of the vehicles. While many of these are necessary for increased comfort, convenience and safety, they must also be designed for the stringent quality requirements compared to standard consumer electronics. The business driven need for miniaturization with increased functionality but at reduced cost necessitates use of high density interconnection with advanced electronics components like Ball Grid Array (BGA) instead of many chip scale packages, which are potentially susceptible to failure while handling and shipping of the components. With the reduced mass of the component, accidental drop from the hand level would experience higher impact loading on the component to create significant damage.

Development pace of new embedded projects often requires usage of model-based design process (MBD). More individuals start using MBD without previous experience with tools and new processes. Matlab/Simulink/Stateflow is a common tool that is used in control applications in automotive and airspace industries. Because of its complexity, the tool has a steep learning curve. Therefore, it is vitally important to set the MBD environment that allows persons to develop real-life projects even without a deep knowledge of the tool. The quality of the product should not be compromised and the development time should not be extended due to the initial lack of knowledge of the tool by the developers. The shifting to MBD leads to changes of roles and responsibilities of algorithm designers and software implementers. This shift is due to ability of creating of efficient production code by code generators.

In this paper we present a fast symmetry search and filtering algorithm for monocular vision based pedestrian candidate detection application. First the ROI of symmetry search is focused on the pedestrian leg region, where the background is relatively simple ground plane. Afterward, the search region is divided into 2 × 4 sub blocks and symmetry density and distribution of each sub block is calculated. Finally, by comparing the symmetry density and distribution of the sub blocks, the correct symmetry axis of the pedestrian candidate is search and also some no-pedestrian candidates are filtered out. The results shown in this method are fast, cost effective and well suited for real-time vision applications.

Driver error is a major cause of vehicle accidents and fatalities. Many of these accidents are related to impaired driver cognition because of fatigue, drowsiness, stress, or mental workload. Physiological parameters such as heart rate and respiration rate are useful for monitoring the cognitive state of a vehicle driver. The Delphi Passive Occupant Detection System (PODS) is passive, non-invasive and non-intrusive. We studied the PODS AC output to explore its utility for measuring occupant physiological parameters in a static environment. We demonstrated that with suitable filtering, amplifying, and signal processing, PODS AC signals can give respiration rate, heart rate and heart rate variability.