Survey on Congestion Detection and Control in Connected Vehicles

TL;DR

This survey reviews recent congestion detection and control techniques in vehicular ad hoc networks, highlighting challenges, existing solutions, and future research directions to improve communication reliability in connected vehicles.

Contribution

It provides a comprehensive classification and analysis of current congestion management methods in VANETs, identifying gaps and proposing future research directions.

Findings

Existing approaches have limitations in scalability and responsiveness.

Hierarchical schemes help classify congestion control techniques.

Future directions include adaptive and machine learning-based solutions.

Abstract

The dynamic nature of vehicular ad hoc network (VANET) induced by frequent topology changes and node mobility, imposes critical challenges for vehicular communications. Aggravated by the high volume of information dissemination among vehicles over limited bandwidth, the topological dynamics of VANET causes congestion in the communication channel, which is the primary cause of problems such as message drop, delay, and degraded quality of service. To mitigate these problems, congestion detection, and control techniques are needed to be incorporated in a vehicular network. Congestion control approaches can be either open-loop or closed loop based on pre-congestion or post congestion strategies. We present a general architecture of vehicular communication in urban and highway environment as well as a state-of-the-art survey of recent congestion detection and control techniques. We also identify the drawbacks of existing approaches and classify them according to different hierarchical schemes. Through an extensive literature review, we recommend solution approaches and future directions for handling congestion in vehicular communications.