Abstract: Collaborative optimization of speed planning and energy management in car following scenarios can help improve energy efficiency. However, fluctuations in the speed of vehicles ahead can affect the speed planning of the ego-vehicle and further affect the safety, economy, and comfort of following car. For the following scenario consisting of multiple preceding vehicles, firstly, the eXtreme Gradient Boosting is used to predict the speed of the preceding vehicle by comparing with other prediction methods. On this basis, combined with variable workshop time distance and artificial potential field method, a variable workshop time distance strategy considering the influence of multiple preceding vehicles is established. Then, the objective functions is constructed considering vehicle safety, comfort, and economy, and model predictive control is used to implement coordinated optimization of vehicle speed planning and energy management. Finally, a comprehensive analysis was conducted on hierarchical control, collaborative control, and collaborative control with different workshop time distance strategies. The results show that compared with the fixed workshop time distance strategy, the collaborative control strategy using variable workshop time distance not only optimizes the speed of the ego vehicle, but also reduces the vehicle costs by 4.3%.

Key words: hybrid electric vehicles, car following scenario, speed planning, energy management, collaborative optimization