Testing and Development of Autonomous Vehicle
Synopsis
In the rapidly evolving field of autonomous vehicle technology, advancements in autonomous vehicle testing and safety development offers a comprehensive exploration of the latest breakthroughs and challenges shaping the industry. This edited volume brings together researchers and engineers to examine critical topics, including adaptive cruise control, emergency braking systems, lane centring, and path planning. With a strong focus on safety and passenger comfort, this book also delves into essential aspects like motion sickness reduction and real-world test scenario design. Through case studies and practical insights, readers will gain a robust understanding of advanced driver assistance systems and the regulatory frameworks essential for safe autonomous vehicle deployment. From deep learning algorithms for collision avoidance to virtual vehicle modelling, this book serves as an invaluable resource for students, researchers, and professionals in engineering and policy who are dedicated to advancing autonomous vehicle technologies. Whether you are developing new systems or evaluating existing technologies, this book provides the tools and knowledge to contribute to the future of transportation.
Chapters
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CHAPTER 1SELF-DRIVING TECHNOLOGIES
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CHAPTER 2SAFETY ASSESSMENT USING SURROGATE SAFETY ASSESSMENT MODEL - A BIBLIOMETRIC ANALYSIS AND REVIEW
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CHAPTER 3CHALLENGES AT A ROUNDABOUT
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CHAPTER 4DEEP LEARNING FOR REAR COLLISION AVOIDANCE
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CHAPTER 5ALGORITHM FOR OPTIMUM PATH PLANNING
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CHAPTER 6MOTION SICKNESS EFFECT USING LATERAL CONTROL
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CHAPTER 7SCENARIO GENERATION FOR SAFETY TESTING