Human Machine Interface and Communication

This chapter explores the specificities of Human-Machine Interaction (HMI) in the context of autonomous vehicles. It examines how HMI in autonomous vehicles differs fundamentally from traditional car dashboards. With the human driver no longer actively involved in operating the vehicle, the challenge arises: how should AI-driven systems communicate effectively with passengers, pedestrians, and other road users?

This section addresses the available communication channels and discusses how these channels must be redefined and implemented to accommodate the new paradigm. Additionally, it considers how various environmental factors—including cultural, geographical, seasonal, and spatial elements—can impact communication strategies.

A concept, the Language of Driving (LoD), will be introduced, offering a framework for structuring and standardizing communication in autonomous vehicle contexts.

Understanding how humans perceive the world is crucial for autonomous vehicles to effectively communicate and interact with them. This chapter explores how human perception, driven by sensory input and cognitive processing, can inform the development of autonomous perception systems, emphasizing the parallels between human and animal intelligence in recognizing focus, body positioning, gestures, and movement. By examining innate perceptual capabilities such as basic physics calculations and environmental modeling, AVs can better anticipate human behavior and respond appropriately in complex traffic environments.

This chapter explores how AVs might adopt human-like communication methods, such as facial expressions or humanoid interfaces, to effectively interact in complex social driving environments.

Human communities build languages for cooperative teaming. To participate in the act of cooperative transportation, AVs will have to understand this language. Depending on the level of expectation communicated by the AV, this language may extend into social interaction models.