On Automated Vehicles
Edward Au, Vice Chair, IEEE TAB Committee on Standards

An automated vehicle is a vehicle capable of sensing its environment and moving safely with minimum or no input from human beings. Recent literature, industry projects, and prototypes have revealed its potential to improve transportation efficiency due to better synchronization of vehicle movements, and also to improve safety by reducing the number of accidents, injuries, and fatalities on the road while enabling new emerging applications.

Even though there are rigorous and well-defined levels of automation, there are different interpretations and understandings on the state-of-the-art technologies of automated vehicles, which may send a mixed, and potentially confusing, message to end users.

To address these concerns, the Standards Board of the IEEE Standards Association (IEEE SA) has recently approved the formation of the following four new projects proposed by the Automated Vehicles Working Group of the IEEE Consumer Technology Society Standards Committee:

IEEE P2040: Standard for General Requirements for Fully Automated Vehicles Driving on Public Roads

This project will result in a comprehensive list of all of use cases, scenarios, and worst conditions that a fully automated vehicle certified by the public body shall address on public roads to protect the safety of the public, including passengers, pedestrians, and other traffic participants.

IEEE P2040.1: Taxonomy and Definitions for Connected and Automated Vehicles

The purpose of this project is to clarify the necessary functionalities of connected and automated vehicles, with the desired outcome of helping end users make choices while staying safe. Environmental sensing is the core of automated vehicles, which must use the information collected via sensors (e.g., camera sensors, radar sensors, light detection, and ranging sensors) to make driving decisions. The information used for decision-making is not limited to the environment around the vehicles but also includes inputs from other surrounding vehicles, and infrastructure.

IEEE P2040.2: Recommended Practice for Multi-Input Based Decision Making of Automated Vehicles Driving on Public Roads

IEEE P2040.2 will develop methods to determine the next action based on multiple sensing inputs, with the desired outcome of maximizing safe driving while avoiding negative impact on traffic flow. It also will itemize scenarios where different inputs suggest different actions, and will recommend solutions in these cases.

IEEE P2040.3: Recommended Practice for Permitting Automated Vehicles to Drive on Public Roads

IEEE P2040.3 addresses the problem that state-of-the-art vehicle functionalities cannot yet address all circumstances on roads. To ensure safe driving, this project will provide regulators with recommendations for permitting automated vehicles to drive on public roads, i.e. when specific conditions are met. This document will itemize combinations of vehicle capabilities and different situations on public roads, with the aim of facilitating the adoption of automated vehicle technologies while ensuring safety and efficiency in traffic flows.

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