Collaborative Autonomous Driving-A Survey of Solution Approaches and Future Challenges

Area of Science:

• Intelligent Transportation Systems
• Autonomous Vehicle Technology
• Cooperative Driving Systems

Background:

• Roads will soon feature many connected and autonomous vehicles (CAVs).
• These vehicles must cooperate using Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication for efficient mobility.
• Cooperative driving encompasses functionalities like cooperative sensing and maneuvering.

Purpose of the Study:

• To provide a comprehensive overview of cooperative driving in autonomous vehicles.
• To detail current solution approaches for various cooperative driving applications.
• To identify research gaps and challenges for future CAV development.

Main Methods:

• A detailed taxonomy of cooperation in cooperative driving is presented.
• Existing solutions for applications like smart parking, lane changes, intersection management, and platooning are reviewed.
• A focused analysis of platooning use-cases, including leader election, is provided.

Main Results:

• Current cooperative driving solutions are categorized based on application.
• Platooning is highlighted as a critical use-case with specific challenges, such as leader election.
• Key research gaps and open challenges are identified.

Conclusions:

• Understanding vehicular cooperation is crucial for advancing autonomous driving.
• Further research is needed to address identified challenges before widespread adoption of CAVs.
• This survey serves as a foundational resource for researchers in the field.