# Autonomous Vehicles: Open-Source Technologies, Considerations, and Development

**Authors:** Oussama Saoudi, Ishwar Singh, Hamidreza Mahyar  
**arXiv:** [2202.03148](https://arxiv.org/abs/2202.03148)  
**Date:** 2022-01-25  
**Summary page:** https://www.summarizepaper.com/en/paper/2202.03148v2/

## Key points

- Advancements in sensor technologies, artificial intelligence (AI), networking, and other areas have led to the development of autonomous vehicles
- Focus on open-source tools and libraries that make autonomous vehicle development more affordable and accessible for developers and researchers
- Discussion on sensors used in autonomous vehicles, including performance, costs, and unique features
- Exploration of Simultaneous Localization and Mapping (SLAM) techniques and algorithms for each modality
- Highlighting of popular open-source driving simulators for training machine learning models and testing software performance
- Emphasis on embedded operating systems selection and security considerations for autonomous vehicle development
- Review of Vehicle-to-Vehicle (V2V) and Internet-of-Vehicle (IoV) communication technologies to extend functionality
- Overview of the five levels of vehicle automation, including commercial and open-source Advanced Driving Assistance Systems (ADAS)
- Insights into major manufacturing and software companies involved in the field of autonomous vehicles, their investments, and partnerships
- Comprehensive coverage to equip readers with an understanding of the industry landscape, technologies, ongoing research efforts, and available tools for building autonomous vehicles.

## Summary

This paper titled "Autonomous Vehicles: Open-Source Technologies, Considerations, and Development" explores the advancements in sensor technologies, artificial intelligence (AI), networking, and other areas that have led to the development of autonomous vehicles. The authors aim to introduce readers to the technologies involved in building autonomous vehicles, with a focus on open-source tools and libraries that make it more affordable and accessible for developers and researchers. The paper covers various topics related to autonomous vehicle development. It starts by discussing the sensors used in autonomous vehicles, providing insights into their performance in different environments, costs, and unique features. The authors then delve into Simultaneous Localization and Mapping (SLAM) techniques and algorithms for each modality. Next, the paper explores popular open-source driving simulators as a cost-effective means of training machine learning models and testing vehicle software performance. It also highlights embedded operating systems and emphasizes security considerations when selecting one for autonomous vehicle development. The authors further discuss Vehicle-to-Vehicle (V2V) and Internet-of-Vehicle (IoV) communication which combine networking technologies with autonomous vehicles to extend their functionality. They review the five levels of vehicle automation including commercial and open-source Advanced Driving Assistance Systems (ADAS), along with their features. Finally, the paper touches on major manufacturing and software companies involved in the field of autonomous vehicles; providing insights into their investments and partnerships. By covering these topics comprehensively, the authors aim to equip readers with an understanding of the industry landscape; its technologies; ongoing research efforts; as well as available tools for developers interested in building autonomous vehicles. Overall this paper serves as a valuable resource for individuals looking to explore open-source technologies related to autonomous vehicle development while providing an overview of key considerations within this rapidly evolving field.