Institute of Sensors, Signals and Systems, Heriot-Watt University
Dr. Cheng Wang is an assistant professor at Heriot-Watt University, leading the RoboSafe Lab where the research focus is verification & validation, and AI safety for safe and trustworthy autonomous driving. Before this, he was a research associate at the University of Edinburgh, doing explainable AI for autonomous driving. He completed his PhD at the Technical University of Darmstadt, Germany, and was a subgroup leader in the VVM project. He is the Marie Curie Postdoctoral Fellow and the DAAD AINet Fellow.
Dr. Cheng Wang, Heriot-Watt University, cheng.wang@hw.ac.uk
Dr. Jiawei Zheng, DigitLab, jw.zheng@ed.ac.uk
Background:
Autonomous vehicles (AVs) must operate safely in the real world without endangering passengers or others on the road. However, challenges arise from external factors like adverse weather conditions and internal issues such as sensor failures, making their reliable deployment difficult. The problem is further exacerbated by the introduction of AI to AVs, wherein uncertainty and opacity characteristics are brought. Despite these additional risks that AI will bring, its superior performance compared to traditional modular pipelines (perception-planning-control) is appealing. Therefore, how to fully leverage the potential of AI while assuring its safety and trustworthiness is a question faced by researchers. Since safety standards such as ISO 26262 and ISO 21448 do not take AI into account, new safety assurance paradigms are critical to mitigate the risks posed by AI.
Goal/Rationale:
The symposium aims to bring researchers together to discuss novel solutions to address this challenge and identify future research questions, with the ultimate goal of bridging the gap between the utility and safety of AI-driven AVs.
Scope and Information for Participants:
This symposium will discuss relevant technologies to address AI safety in AD. Specifically, topics such as robust training, safety verification and validation, simulation and testing, scenario generation, uncertainty quantification, AI monitoring and risk quantification fall into the scope of the symposium. As a result, engineers or scholars from the background of robotics, automotive, intelligent transportation and AI are welcome to join the symposium.
The main topics of this symposium are listed below.
Meanwhile, submissions aligned with the overall conference theme are also welcome.
Prospective authors are kindly invited to submit full papers that include title, abstract, introduction, tables, figures, conclusion and references. It is unnecessary to submit an abstract in advance. Please submit your papers in English.
Each paper should be no less than 4 pages. One regular registration can cover a paper of 6 pages, and additional pages will be charged. Please format your paper well according to the conference template before submission. Paper Template Download
Please prepare your paper in both .doc/.docx and .pdf format and submit your full paper by email with both formats attached directly to sympo_edinburgh@confmss.org
Process | Date & Time |
---|---|
Submission Deadline | June 9, 2025 |
Symposium Date | June 16, 2025 |
Notification of Acceptance | 7-20 workdays |
Fees (VAT Included) | Amount |
---|---|
Registration and Publishing Fee (6 pages included) | $450 |
Additional Page (per extra page) | $40 |
Accepted papers of the symposium will be published in Conference Proceedings, and will be submitted to EI Compendex, Conference Proceedings Citation Index (CPCI), Crossref, CNKI, Portico, Engineering Village (Inspec), Google Scholar, and other databases for indexing. The situation may be affected by factors among databases like processing time, workflow, policy, etc.
Please note that the publication policy may vary between different publishers. For details regarding the publication process, kindly refer to the policies of the respective publisher.
This symposium is organized by CONF-MSS 2025 and it will independently proceed the submission and publication process.
Heriot-Watt University Edinburgh Campus, Heriot-Watt University, EH14 4AS
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