Titlebook: Vehicle Computing; From Traditional Tra Sidi Lu,Weisong Shi Book 2024 The Editor(s) (if applicable) and The Author(s), under exclusive lice

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Testing for Vehicle Computing,indoor environments and delving into the nuances of single-vehicle and multi-vehicle testing, illustrated by the ICAT case study. Finally, the chapter engages in a thoughtful discussion on the challenges posed by experimental platforms and physical worlds coupling, providing a comprehensive overview

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Mobile Computation in Connected Vehicles,rtation functions. With the advent of diverse computing hardware such as Graphic Processor Units (GPUs), Digital Signal Processors (DSPs), Field Programmable Gate Arrays (FPGAs), and Application-Specific Integrated Circuits (ASICs), vehicles are now equipped to execute intricate computational tasks.

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Vehicular Communication and Networking Technologies,hapter provides a comprehensive exploration of mainstream vehicular communication mechanisms, their reliability, bandwidth, scalability, and envisioned advancements. Through detailed discussions on communication architectures, including centralized, decentralized, and publish/subscribe frameworks, t

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Sensing and Data Acquisition Techniques,. Relying on a sophisticated array of sensors—including cameras, LiDARs, radars, IMUs, and GPS—these vehicles perceive and interact with their surroundings with remarkable accuracy. This chapter delves into the multifaceted sensing and data acquisition techniques pivotal to the operation of CVs, exa

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Energy Management, Efficiency, and Delivery,hicles (EVs). It discusses the criticality of real-time monitoring and predictive analysis for key parameters like voltage, temperature, and state of charge (SOC) that ensure the health and efficacy of EV batteries. This chapter also discusses advanced modeling techniques for fuel consumption in hea

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Programming Interfaces for Vehicle Computing,ng. It scrutinizes the eclectic array of Automotive Software Platforms, from the structured approaches of AUTOSAR and SOAFEE to the cutting-edge developments by Baidu Apollo, Autoware, NVIDIA DRIVE, BlackBerry IVY, and the robotics-focused ROS. We present a stratified analysis of VPIs, delineating t