IEEE Std 3307-2024 PDF
Name in English:
St IEEE Std 3307-2024
Name in Russian:
Ст IEEE Std 3307-2024
Original standard IEEE Std 3307-2024 in PDF full version. Additional info + preview on request
Full title and description
IEEE Standard — Adoption of Moving Picture, Audio and Data Coding by Artificial Intelligence (MPAI) Technical Specification Connected Autonomous Vehicle‑Architecture (MPAI‑CAV) V1. This document adopts the MPAI Technical Specification that defines a reference architecture for connected autonomous vehicles (CAVs), breaking a CAV into subsystems and specifying functions, inputs/outputs and component topology.
Abstract
This standard (IEEE/MPAI 3307‑2024) provides a reference architecture for connected autonomous vehicles intended to guide system designers, integrators and standards developers. It describes subsystem decomposition, component topologies, data inputs and outputs, and functional interfaces required to enable interoperable CAV implementations that leverage MPAI AI‑based coding and processing techniques.
General information
- Status: Active standard.
- Publication date: July 12, 2024.
- Publisher: IEEE Standards Association (IEEE/MPAI adoption).
- ICS / categories: 35.240 (Applications of information technology / AI applications); 43.040 (Road vehicle systems).
- Edition / version: 2024 (first IEEE adoption of MPAI‑CAV, Version 1).
- Number of pages: 49 (approx.).
Scope
The standard adopts the MPAI Technical Specification Connected Autonomous Vehicle‑Architecture (MPAI‑CAV) V1 and specifies a reference model for CAV architecture. It defines subsystem boundaries, the functions assigned to each subsystem, the expected input and output data types, and the recommended topology of components and interfaces to support AI‑based coding and data exchange in connected autonomous vehicle environments. The scope intentionally targets architecture and interoperability rather than vehicle safety certification or detailed physical implementation requirements.
Key topics and requirements
- Reference architecture for Connected Autonomous Vehicle (CAV) systems, including subsystem decomposition (sensors, perception, planning, control, connectivity, etc.).
- Specification of functional roles, input/output data formats and expected data flows between components and subsystems.
- Topology and component mapping recommendations to support distributed processing and AI‑based media/data coding per the MPAI framework.
- Interoperability considerations and interface definitions to enable multi‑vendor integration and data exchange.
- Guidance on using MPAI AI coding techniques for moving picture, audio and data within vehicle and edge/cloud contexts.
- Non‑normative guidance on potential deployments and architecture variants (informative examples).
Typical use and users
Primary users are automotive system architects, OEMs, Tier‑1 suppliers, autonomous vehicle platform integrators, AI solution providers, and researchers working on connected/autonomous vehicle architectures. The standard is also useful for standards developers and regulators seeking a reference architectural model for CAV interoperability and AI‑based data coding.
Related standards
Related IEEE and MPAI adoption documents include other IEEE MPAI adoption standards addressing AI‑based media and data coding and related AI topics (examples from the IEEE Autonomous & Intelligent Systems initiative). Implementers may also reference vehicle‑centric standards such as SAE J3016 (automated driving taxonomy), ISO/IEC and IEC standards for ITS and vehicle systems when aligning safety, interfaces and testing strategies.
Keywords
MPAI, MPAI‑CAV, connected autonomous vehicle, CAV architecture, AI coding, moving picture/audio/data coding, interoperability, vehicle subsystems, reference architecture, IEEE 3307
FAQ
Q: What is this standard?
A: IEEE/MPAI 3307‑2024 is an IEEE adoption of the MPAI Technical Specification “Connected Autonomous Vehicle‑Architecture (MPAI‑CAV) V1”. It defines a reference architecture and related data/interface expectations to support connected autonomous vehicle systems.
Q: What does it cover?
A: It covers architecture-level descriptions: subsystem decomposition, functional definitions, input/output data types, component topologies and recommendations for interfaces to enable interoperable CAV implementations that leverage AI‑based coding approaches from MPAI. It does not itself replace safety certification or vehicle regulatory standards.
Q: Who typically uses it?
A: Automotive architects, OEMs, Tier‑1 suppliers, system integrators, AI developers for in‑vehicle and edge/cloud processing, academic researchers, and standards developers concerned with CAV interoperability and data coding.
Q: Is it current or superseded?
A: It is an active IEEE standard published on July 12, 2024 (first IEEE adoption). Users should check IEEE SA or subsequent IEEE publications for any amendments or revisions after that date.
Q: Is it part of a series?
A: Yes — it is part of a set of IEEE adoptions of MPAI technical specifications and sits within IEEE work on Autonomous & Intelligent Systems; implementers should review other related IEEE/MPAI standards for complementary topics (compression, watermarking, data coding, etc.).
Q: What are the key keywords?
A: CAV, MPAI‑CAV, connected autonomous vehicle, AI coding, moving picture/audio/data coding, architecture, interoperability, IEEE 3307, reference model.