RADAS 2021: Reliability of Advanced Driving Assistant Systems Wuhan, China, October 25-28, 2021 |
Conference website | https://radas2021.github.io/radas2021/ |
Submission link | https://easychair.org/conferences/?conf=radas2021 |
Abstract registration deadline | July 25, 2021 |
Submission deadline | August 17, 2021 |
Workshop summary
International Workshop on Reliability of Advanced Driving Assistant Systems (RADAS 2021) seeks to bring together researchers and practitioners to exchange and discuss the reliability issues of the emerging advanced driving assistant systems. As the AV (Autonomous Vehicle) industry is growing exponentially, and according to a report by Market Research Future, the market is expected to hit over $65 billion by 2027. With the recent popularity and attention received by AV industry, advanced driving assistant systems (including many autopilot systems) has become a key driving force of the next-generation AV technology. However, the reliability and safety issues of advanced driving assistant systems have caused wide public concern and touched a nerve of public anxiety, especially when fatal traffic accident happened due to failures of advanced driving assistant systems. This year’s RADAS centers around two key scopes to bring researchers with diverse background (e.g., reliability, autopilot, AI) to come up with in-depth discussion and solutions for both reliability issues and autopilot techniques: (1) How to better take the advantage of recent reliability techniques and tools to further improve quality of advanceddriving assistant systems, and (2) How to advance and develop reliability theory and methods for AI-Intensive Systems (e.g., autopilot system). As we see that reliability techniques have already significantly contributed to automotive industry, with some initial work to research on AV and autopilot technology. On the other hand, reliability for autopilot is still at a very early stage.
RADAS 2021 will, therefore, be a workshop, which seeks to develop a cross-domain community that systematically looks into both areas from the new perspective. The workshop will explore the emerging techniques and tools for assessing, predicting, and improving the safety, security, quality, and reliability of advanced driving assistant systems that in turn help the development of reliability modeling methods and techniques. We hope RADAS could facilitate to improve autopilot systems with high quality, as well as accelerate the process of system engineering and quality assurance.
Theme, Goals and Relevance
Theme: The theme of the workshop is to leverage traditional reliability techniques to better understand advanced driving assistant system and draw strong connections between the two. We aim to apply reliability methods to accomplish the tasks such as failure prediction for advanceddriving assistant system, as well as advance and complement the existing reliability theory and practice for AI-Intensive System.
Goals: Our main goal is to shed light on the direction of applying the principles of reliability theory and methods to advanced driving assistant system and therefore evaluate the robustness of autopilot techniques especially AI-based techniques. The workshop also aims to leverage reliability techniques to advance the efficiency, accuracy, effectiveness, and usefulness of current autopilot techniques.
Relevance: The audience of ISSRE focuses on general reliability issues of hardware/software systems, which is highly related and would be benefited by leveraging the reliability techniques for advanced driving assistant system. In addition, it would be helpful for the ISSRE community to know at what aspect the reliability theory and methodology should be improved for the AI-Intensive System (e.g., autopilot systems) and make a broader impact to the community.
Submission instructions
This workshop accepts regular research papers within 6 pages, and short papers (new idea and position) within 4 pages.
Submitted papers must conform to the two-column IEEE conference publication format. Templates for LaTeX and Microsoft Word are available from http://www.ieee.org/conferences_events/conferences/publishing/templates.html: please use the letter format template and conference option.
Papers should be submitted in the PDF format: they must not exceed page limit. Submissions will be handled via EasyChair. Papers must neither have been previously accepted for publication nor be under submission in another conference or journal. For your paper to be published in the proceedings, at least one of the authors of the paper must register for the conference and confirm that she/he will present the paper in person.
Describe the review and evaluation process to decide which submissions to accept: All papers will be evaluated in terms of the following criteria:
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Originality or potential for impact: The submission presents a particularly novel collation of historical work, insight or approach towards new/future work, and/or is potentially disruptive of current practice or common knowledge.
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Soundness: The submission makes a coherent argument, substantiated by historical analysis, cogent analytical argument, or appropriately-scoped initial empirical results.
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Relevance: The submission appropriately considers and puts itself in context with respect to the relevant literature.
Specific topics of interest include, but are not limited to the following subject categories:
- Testing and verification of Advanced Driving Assistant Systems
- Robustness, adversarial attack, defense in Advanced Driving Assistant Systems
- Defects, errors, failures, defects, bugs of Advanced Driving Assistant Systems
- Availability and safety of Advanced Driving Assistant Systems
- System and software security of Advanced Driving Assistant Systems
- Hardware reliability of Advanced Driving Assistant Systems
- Systems (software and hardware) engineering of Advanced Driving Assistant Systems
- AI and Advanced Driving Assistant Systems
- Quality Assurance of Advanced Driving Assistant Systems
- Traffic Engineering for reliability of Advanced Driving Assistant Systems
- Human computer interaction issues in Advanced Driving Assistant Systems
- Empirical studies on Advanced Driving Assistant Systems
- Industry best practices
Expected Participation
We expect to attract researchers and practitioners from either reliability or advanced driving assistant system communities to attend the RADAS. The ballpark estimate of the number of participants is 20-30 attendees. We also expect to take in around 12 submissions and eventually 3-4 accepted papers would warrant publication. As the RADAS is the first start-up workshop connecting reliability and autopilot techniques, we hope that the fairly competitive acceptance rate would facilitate high-quality submissions, to eventually build up the workshop to be the home of crossover areas of reliability and advanced driving assistant system.
Organizing Committee
Yinxing Xue (University of Science and Technology of China, China) Email: yxxue@ustc.edu.cn
Yan-Fu Li (Tsinghua University, China) Email: liyanfu@tsinghua.edu.cn
Lei Ma (University of Alberta, Canada) Email: ma.lei@acm.org
Shengjian Guo (Baidu Research Silicon Valley) Email: sjguo@baidu.com
Guozhu Meng (University of Chinese Academy of Sciences) Email: mengguozhu@iie.ac.cn