Multivehicle cooperative control strategy in freeway merging areas under visible light communication environment

The efficiency of multivehicle merging in freeway merging areas has always been a major challenge in traffic research. The emergence of connected and autonomous vehicles (CAVs) provides an effective solution for this problem. However, the dynamic merging interaction among CAVs, autonomous vehicles (AVs), and manual vehicles (MVs) in mixed traffic environments will become a major challenge in the future, because they lack effective communication with one another in the traditional CAV communication using radio frequency signals for interaction. Visible-light communication (VLC) can compensate for the shortcomings of traditional CAV communication, such as limited spectrum resources, communication security, and radiation effects. This study explored the application of VLC to the transformation of AVs into CAVs. It developed a dual-lane vehicle-to-vehicle VLC (V2V-VLC) model that determines the communication range by incorporating the signal-to-noise ratio and bit error rate to characterise the VLC channel conditions. Furthermore, a multivehicle networking strategy based on V2V-VLC was proposed, and a VLC-based speed control strategy (VLC-SCS) was designed to improve the merging efficiency of vehicles with different driving styles in the merging areas. The Simulation of Urban Mobility platform was used to simulate a freeway merging area in Suzhou, China. The simulation results showed that the inflow efficiency of traffic flow can be effectively improved when the penetration rate of CAV (VLC-SCS) is 25%, compared with the case when that of MV is 100%. The optimisation effect observed at 100% penetration rate of CAV (VLC-SCS) was comparable to that of CAV equipped with cooperative adaptive cruise control (CACC) at 75% penetration rate. This study provides theoretical and technical support for the practical application of V2V-VLC in transportation systems.