Communication between Autonomous Vehicle and Human Traffic Partners

As automated vehicles (AVs) becoming a part of the foreseeable future, our traffic environment will be populated with a mixture of AVs and human traffic partners (HTPs) such as pedestrians, cyclists and conventional human drivers. Thus, the opportunity of interactions between various AVs and HTPs is increasing. However, a bottleneck is that HTPs may not feel safe when they do not percept, understand and project the intentions of AVs. It may result in potential issues such as distrust, unsafety, inefficiency and bad pro-sociality. This potential issue could hinder the public acceptance and broad deployment of AVs. The current research focuses are on, e.g., identifying highly relevant real-world use cases of AVs-HTPs communication and safety factors between HTPs and AVs in mixed traffic environments, and the decision-making process in AVs-HTPs interactions. Besides, multiple studies discuss the relevant factors, e.g., positions, timing as well as types for human-machine Interfaces (HMI). Until now, there were some workshops which relate to behavioral research and transportation system modeling methods of the AV-human interaction in both IV and ITSC workshops. However, there has been no workshop topic focus on AVs-HTPs communication and even more discussed potential solutions to compensate the gap of this from a design perspective held jointly by IEEE IV and IEEE ITSC.

• • Why does AV need to communicate with HTPs?

  • In what kind of scenes does AV need to communicate with HTPs?

  • How does AV communicate with HTPs?

  • How does AV know that HTPs understands its conveyed intentions?

  • What contents between AV and HTPs are communicated?

  • How to promote HTPs’ safe behaviours through AVs-HTPs communication?

  • Is HMI a potential solution to compensate the gap of AVs-HTPs communication?

  • How to design and evaluate the external human-machine interface (eHMI) and internal human-machine interface (iHMI)?

  • Human-computer interaction theories, concepts and models

  • Typical ambiguous traffic scenarios

  • Implicit and explicit communication

  • Traffic partner behaviour research

  • Intention perception, understanding and prediction

  • Human factors (Situation awareness, trust)