Autonomous Vehicle

share their practical experiences designing autonomous vehicle systems. These systems are complex, consisting of three major subsystems: (1) algorithms for localization, perception, and planning and control; (2) client systems, such as the robotics operating system and hardware platform; and (3) the cloud platform, which includes data storage, simulation, high-definition (HD) mapping, and deep learning model training. The algorithm subsystem extracts meaningful information from sensor raw data to understand its environment and make decisions as to its future actions. The client subsystem integrates these algorithms to meet real-time and reliability requirements. The cloud platform provides offline computing and storage capabilities for autonomous vehicles. Using the cloud platform, new algorithms can be tested so as to update the HD map—in addition to training better recognition, tracking, and decision models.

by Shaoshan Liu (Author)

In this book, valuable research on the modeling, systems, transportation, technological necessity, and logistics of autonomous vehicles is presented. The content of the book will help researchers to create ideas for their future studies and to open up the discussion of autonomous vehicles.

Autonomous Vehicle International features nothing but the latest and next-generation thinking and technologies for driverless vehicles. From cars to trucks, Autonomous Vehicle International is produced twice a year.

Autonomous Vehicle International features nothing but the latest and next-generation thinking and technologies for driverless vehicles. From cars to trucks, Autonomous Vehicle International is produced twice a year.

This book is a collection of experiences shared by scientists from different parts of the world doing researches and daily exploiting autonomous systems. The book will be a treasure trove of knowledge and inspiration for further research in the field of autonomous vehicles.