Toward Communication-Efficient Data Transmission for Autonomous Driving Systems: Techniques, Challenges, and Trends

The next generation of smart mobility services — particularly Autonomous Driving Systems (ADSs) — faces stringent bandwidth, latency, and energy constraints, making efficient vehicular communication paramount for safety and real-time decision-making. High-resolution cameras, LiDAR, and multiple sensors generate enormous data streams; however, transmitting all raw data in real time is neither practical nor reliable. Beyond powerful perception models, ADS requires smarter communication mechanisms and protocols to determine what data to share, when to share it, and with whom — whether across onboard units, edge servers, or the cloud platforms. This article reviews state-of-the-art approaches to communication-efficient data transmission in autonomous driving, analyzing their trade-offs among performance, adaptability, and deployment feasibility. It also highlights emerging research directions and open challenges that must be addressed to enable future ADS deployment within robust and reliably connected transportation infrastructures.