Autonomous Vehicles: Open-Source Technologies, Considerations, and Development
Oussama Saoudi, Ishwar Singh, Hamidreza Mahyar

TL;DR
This paper provides an overview of open-source tools, technologies, and considerations involved in autonomous vehicle development, covering sensors, algorithms, simulators, communication, and industry players.
Contribution
It offers a comprehensive review of open-source resources and industry insights, facilitating easier entry and development in autonomous vehicle research and deployment.
Findings
Summarizes sensor performance across environments and costs.
Reviews open-source simulators for training and testing.
Discusses industry investments and partnerships.
Abstract
Autonomous vehicles are the culmination of advances in many areas such as sensor technologies, artificial intelligence (AI), networking, and more. This paper will introduce the reader to the technologies that build autonomous vehicles. It will focus on open-source tools and libraries for autonomous vehicle development, making it cheaper and easier for developers and researchers to participate in the field. The topics covered are as follows. First, we will discuss the sensors used in autonomous vehicles and summarize their performance in different environments, costs, and unique features. Then we will cover Simultaneous Localization and Mapping (SLAM) and algorithms for each modality. Third, we will review popular open-source driving simulators, a cost-effective way to train machine learning models and test vehicle software performance. We will then highlight embedded operating systems…
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Taxonomy
TopicsAutonomous Vehicle Technology and Safety · Vehicular Ad Hoc Networks (VANETs) · Traffic Prediction and Management Techniques
