Variable speed limit control method of freeway merging area in a car-truck mixed heterogeneous traffic environment

To alleviate traffic congestion and enhance safety in freeway merging areas under car-truck mixed heterogeneous traffic environment, this study proposes a variable speed limit (VSL) control method. First, a lane-level cell transmission model (CTM) is developed to predict traffic states, accounting for four distinct vehicle types: human-driven cars (HCs), human-driven trucks (HTs), connected autonomous cars (CACs), and connected autonomous trucks (CATs). Second, a collision risk prediction model for the merging area is constructed uses traffic simulation data through count model fitting. An optimal VSL control function is formulated to enhance traffic efficiency and safety. This function and CTM are then integrated into a model predictive control (MPC) framework, establishing a comprehensive VSL control method. Finally, simulations conducted using Python and SUMO verify the effectiveness of the proposed method. The results show that, compared with the no-control scenario, the VSL method significantly reduces total travel time (TTT) and collision risk (TCR) at the macroscopic level. At the microscopic level, it increases the average speed and reduces travel delay, time-exposed time-to-collision (TET), and time-integrated time-to-collision (TIT), thereby further validating the effectiveness of the method. The proposed research framework offers theoretical insights and technical guidance for future freeway traffic management in a car-truck mixed heterogeneous traffic environment.