An Open Approach to Autonomous Vehicles

Author:

Prajwal Gowda H G 1,Pradeep Nayak 1,Prajna 1,Pragathi 1,Prashanth Kumar B C 1

Affiliation:

1. Alva’s Institute of Engineering and Technology, Mijar, Karnataka, India

Abstract

The evolution of autonomous vehicle (AV) technology is rapidly transforming the automotive industry, driving innovations in safety, efficiency, and user experience. This research paper explores the impact of open approaches on the development and deployment of autonomous vehicles. By leveraging open-source software and hardware platforms, such as OpenPilot and Apollo, the study highlights how collaborative, transparent methodologies foster innovation and accelerate technological advancements. The paper examines the technical, regulatory, and ethical challenges associated with open-source AV development, including data management, sensor integration, and compliance with safety standards. Through a comprehensive analysis of successful open-source projects and emerging trends, the research identifies the benefits of open approaches in promoting cross-disciplinary collaboration and addressing complex challenges. The findings underscore the potential of open-source solutions to drive the future of autonomous vehicle technology, offering insights into their role in shaping industry standards and regulatory frameworks

Publisher

Naksh Solutions

Reference8 articles.

1. Zhao, Y., & Zhao, S. (2023). "Recent Advancements in End-to-End Autonomous Driving." IEEE Transactions on Intelligent Vehicles, 9(1), 103-118. Available at IEEE Xplore.

2. Li, Y., & Xu, K. (2022). "Research Advances and Challenges of Autonomous and Connected Vehicles." IEEE Access, 10, 1025-1039. Available at IEEE Xplore.

3. Chen, Y., & Zhang, H. (2021). "Autonomous Driving Cars in Smart Cities: Recent Advances." IEEE Communications Magazine, 59(6), 112-118. Available at IEEE Xplore.

4. Smith, J., & Wang, T. (2023). "Autonomous Cars: Research Results, Issues, and Future Challenges." IEEE Transactions on Intelligent Transportation Systems, 24(4), 1645-1658. Available at IEEE Xplore.

5. Jones, R., & Lee, P. (2022). "Autonomous Car Driving Using Deep Learning." Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2022, 512-519. Available at IEEE Xplore.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3