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AVS 2024: IEEE International Symposium on Autonomous Vehicle Software

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AVS
Día de Entrega:
2024-04-05
Fecha de Notificación:
2024-05-06
Fecha de conferencia:
2024-07-01
Ubicación:
Cambridge, UK
Vistas: 9009   Seguidores: 0   Asistentes: 0

Solicitud de Artículos

AVS 2024 (IEEE International Symposium on Autonomous Vehicle Software) is an academic conference held in Cambridge, UK on 2024-07-01. The paper submission deadline is 2024-04-05. Acceptance notifications are sent on 2024-05-06.

The IEEE International Symposium on Autonomous Vehicle Software (AVS 2024) creates a unique venue for the researchers, engineers, industry players and policy makers to present the latest advancements and innovations in the theoretical research, open source projects, software applications and regulation work in the autonomous vehicle software. AVS 2024 features keynote ad- dresses by eminent scientists from both academia and industry. All research papers will be peer reviewed on the basis of a full length manuscript and acceptance will be based on quality, originality and relevance. IEEE Conference Publishing Services (CPS) will publish the proceedings. Accepted papers will also be submitted for inclusion in the IEEE Xplore and to other abstracting and indexing partners such as the Ei Compendex. Selected papers of top quality will be published in a special section of IEEE Transactions on Reliability instead of the conference proceedings. This will speed up the journal publication of these papers. Topics The topics of interests in this special issue include, but are not limited to: · Autonomous vehicle software vulnerability assessment, risk analysis, attack and threat models · Autonomous vehicle software reliability · Safe design and implementation of autonomous vehicle software and applications for autonomous vehicles · Autonomous vehicle operating system security · Autonomous vehicle embodied intelligence · Availability, resiliency and fault tolerance in autonomous vehicle software · Autonomous vehicle software testing, verification and validation · Autonomous vehicle software quality evaluation methodologies and metrics · Autonomous vehicle software forensics, events monitoring and auditing · Autonomous vehicle software standardization, certification, and interoperability · Secure intra-vehicle, vehicle-to-vehicle, and other vehicular network communications · Testing of machine learning components for autonomous vehicles · Practical experiences, empirical studies, and testbeds for autonomous vehicle software · Industrial experiences and best practices for autonomous vehicle software development · Program synthesis for autonomous vehicle software · Intelligent interaction in self-driving · Self-driving environment perception, machine vision
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