Communication Range of Connected Autonomous Vehicles and its Impact on CO₂ Emissions Reduction

In this study, a traffic flow analysis was conducted using a multi-agent simulation to evaluate the effect of reducing CO2 emissions through the penetration of connected autonomous vehicles (CAVs) equipped with vehicle-to-vehicle (V2V) communication functionality. By exchanging local information among CAVs, alleviating traffic congestion without the need for cooperative vehicle control, and reducing CO2 emissions by up to 20% is possible. In addition, we analysed the impact of CAV penetration rate and communication range on CO2 emissions, demonstrating that the reduction effect in CO2 emissions tends to appear more prominently once the penetration of CAVs reaches a certain threshold. In particular, when the communication range is narrow, a significantly high penetration rate is required before the benefits of CO2 reduction become evident. Furthermore, a wider communication range is not necessarily more desirable. These findings suggest that limiting the communication range may enable more efficient use of road traffic information. Although each CAV acts solely based on its own self-interest, route selection based on local information leads to the emergence of swarm intelligence, resulting in improved efficiency at the collective level.