Simulation analysis of trajectory planning strategy for collaborative lane changing of intelligent connected vehicles

This article proposes a new trajectory planning strategy for the collaborative lane changing problem of intelligent connected vehicles in complex traffic environments, and verifies its effectiveness through simulation analysis. The study first analyzed the key influencing factors in the lane changing process of intelligent connected vehicles, including the relative position, velocity, acceleration, and road conditions between vehicles. Based on these factors, a collaborative lane changing trajectory planning algorithm was designed, which can perceive the surrounding traffic environment in real time, dynamically adjust the lane changing trajectory, and ensure the safety and comfort of the lane changing process. In the simulation analysis, a traffic scenario containing multiple lanes and multiple intelligent connected vehicles was constructed, and the lane changing process under different traffic densities and speed conditions was simulated. The simulation results show that the proposed collaborative lane changing trajectory planning strategy can significantly improve the success rate of lane changing while reducing the impact on surrounding traffic flow. In addition, the study also explored the influence of different parameter settings on lane changing effects, including lateral acceleration threshold, trajectory planning time step, etc. By adjusting these parameters, the lane changing trajectory can be further optimized, improving the lane changing performance and safety of intelligent connected vehicles.