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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.

Nomadic mobile consumer electronic (CE) devices are growing in functionality and popularity. Some of these devices, such as navigation systems, are being used in vehicles as a lower cost alternative to integrated vehicle options. Other devices, such as MP-3 players, are becoming the preferred source of music on the go. Wireless nomadic devices are now capable of accessing E-mail and other Internet-based functions. Automakers are beginning to recognize the importance of integrating support for such devices to facilitate their use in vehicles. A key element of this integration is the ability of the vehicle HMI to support both the operation of nomadic devices as well as the display of content from such devices. This paper presents an example of how a nomadic device can be properly integrated with the vehicle HMI using the AMI-C HMI architecture. In particular, a commercial nomadic device was used to stream MP3 content to a vehicle radio using an 802.11 wireless connection.

Vehicle Infrastructure Integration (VII) is an initiative of the US Department of Transportation to provide communications among vehicles and between vehicles and roadside infrastructure in order to increase the safety and productivity of transportation systems. It makes use of but is not restricted to the 5.9 GHz Dedicated Short Range Communication (DSRC) spectrum. There are 3 major categories of applications for VII - Highway Safety, Vehicular Mobility, and Consumer & Commercial Services. There are currently approximately 42,000 traffic fatalities a year in the United States. Reducing deaths, injuries and property damage is of the highest priority in the development of VII applications. Electronic Brake Warning, Signal Phase and Timing, and Collision Detection are among the applications dedicated to improving highway safety. Increasing traffic volume is outpacing the addition of new roadway capacity, resulting in increasing delays, congestion and frustration.

Automotive radar application is a focus in active traffic safety research activities. And accurate lateral position estimation from the leading target vehicle through radar is of great interest. This paper presents a method based on the regression tree, which estimates the rear centroid of leading target vehicle with a long range FLR (Forward Looking Radar) of limited resolution with multiple radar detections distributed on the target vehicle. Hours of radar log data together with reference value of leading vehicle's lateral offset are utilized both as training data and test data as well. A ten-fold cross validation is applied to evaluate the performance of the generated regression trees together with fused decision forest for each percentage of the training data.

Through the use of finite-element modeling, pressure patterns on the underside of seat foam can be computed for a variety of occupants and seating positions. A design tool has been created which allows an engineer to evaluate different layouts for a pressure-sensing bladder in just minutes. This is important to meet FMVSS-208 safety regulations for vehicles sold in the US. Further, an artificial intelligence search engine has been applied to this problem to achieve near-optimal performance given the constraints of the seat design. Results are shown and compared with the traditional manual method of layout design.

Since the end of the 1990s, model-based development processes have increasingly been adopted for the development of automotive embedded control software. One of the main goals of this approach is a reduction of project development time. This reduction is achieved through the use of executable modeling and autocoding. Due to the current constraints for a majority of embedded controllers on microprocessor memory and throughput, efficient production-quality code can not be generated from an executable model with the push of a button. The autocoding process requires manual setting of the software properties for the model's blocks and components by a software professional. Once the code is generated, code verification is needed. Although in many cases autocode generation and verification stages take less time to execute as compared to handcoding techniques, they still require substantial time to perform.

The technological and process developments within the semiconductor industry during the past two decades has led to significant advancements in the complexity, functionality and performance of standard devices, such as microprocessors, digital signal processors, memories and custom Application Specific Integrated Circuits (ASICs). Field Programmable Gate Array (FPGA) suppliers have taken advantage of these developments to offer device configurations that can include millions of programmable gates integrated with megabytes of internal memory and processor cores in package profiles and temperature ranges suitable for a variety of applications. The combination of reusable intellectual property, low unit costs and relative ease of implementation has led to increased FPGA usage in the automotive industry. Engineers are turning to FPGA solutions to enable the required features and functions not currently available with standard components.

The evolution of car radio in the past seven decades is a perfect illustration of the convergence of diverse technical fields: RF electronics, mobile wireless communications, the Internet, personal computers, consumer electronics, and automotive human machine interfaces. The early part of the radio evolution was driven by the need to improve the received audio signal quality while in the past two decades the driver has been to increase the channel capacity and to enhance the degree of personalization. Besides traditional AM/FM programming, today's radios also play a variety of media such as cassette tape, CD, MP3, DVD-A etc. as well as over 100 channels of satellite digital audio programs. Going forward, we believe that the radio will continue to be the entertainment center of the vehicle, and that the consumers are expecting to have access to personalized information anywhere and anytime.

Entertainment is THE killer application of consumer electronics in vehicles. Ever since the first AM vacuum tube radio was factory installed in a luxury vehicle in the early 1930s, entertainment has led the introduction of consumer electronics (CE) in the transportation industry. For example, over the last 68 years the auto industry has adopted FM reception; transistor radios; electronic tuning; cassette and CD playbacks; and multi-speaker, multi-channel-amplifier premium audio systems. During the “technology bubble” period (1998-2001), many industry experts predicted the next CE “killer app” in vehicles to be mobile Internet. Although mobile Internet is still a dream, significant new entertainment applications such as rear seat DVD video, satellite digital audio broadcast (XM & Sirius), and MP3 radio have exploded in the automotive and commercial vehicle markets.