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Fuel efficiency improvement in automobiles has been a topic of great interest over the past few years, especially with the introduction of the new CAFE 2025 standards. Although there are multiple ways of improving the fuel efficiency of an automobile, lightweighting is one of the most common approaches taken by many automotive manufacturers. Lightweighting is even more significant in electric vehicles as it directly affects the range of the vehicle. Amidst this context of lightweighting, the use of composite materials as alternatives to metals has been proven in the past to help achieve substantial weight reduction. The focus of using composites for weight reduction has however been typically limited to major structural components, such as BiW and closures, due to high material costs. Secondary structural components which contribute approximately 30% of the vehicle weight are usually neglected by these weight reduction studies.

In modern passenger vehicles, A-pillar plays an important role in its passive safety by minimizing the deformation of passenger compartment during the crash. To meet various crash requirements, as well as sometimes due to demand of vehicle styling, A-pillar cross section of modern vehicles is generally wider. This wider cross section acts as an increased obstruction to the field of vision of the driver. It is considered detrimental for the safety of road users. The current work proposes an innovative design solution to reduce the obstruction angle due to an A-pillar. It also addresses the weight reduction objective. This is done by utilizing the noble properties of Carbon Fiber Reinforced Polymers (CFRP). Carbon Fiber Reinforced Polymers (CFRP) offer flexibility for complex design. Due to high specific strength and stiffness, CFRP's are suitable candidate for design considerations presented in this study.

This paper presents an approach for performing software in the loop testing of autonomous vehicle software developed in the Autoware framework. Autoware is an open source software for autonomous driving that includes modules such as localization, detection, prediction, planning and control [8]. Multitudes of autonomous driving frameworks exist today, each having its own pros and cons. Often, MATLAB-Simulink is used for rapid prototyping, system modeling and testing, specifically for the lower-level vehicle dynamics and powertrain control features. For the autonomous software, the Robotic Operating System (ROS) is more commonly used for integrating distributed software components so that they can easily share information through a publish and subscribe paradigm. Thorough testing and evaluation of such complex, distributed software, implemented on a physical vehicle poses significant challenges in terms of safety, time, and cost, especially when considering rare edge cases.