Variable Speed Limit Strategy With Dynamic Control Cycle Based on Predictive Control

In recent years, variable speed limit (VSL) strategies have proven to be an efficient control measure to mitigate traffic congestion at freeway bottlenecks. In general, the VSL change time is a constant value. However, there are certain limitations in traffic situations handled by a constant cycle VSL. Therefore, in this paper, we develop a dynamic cycle strategy of VSL based on predictive control. We first analyze the applicable situation of the dynamic control cycle and establish a probability model to determine the range of cycle selection. Then, the cell transmission model predicts the parameters of macroscopic traffic flow. Finally, an optimization algorithm is designed that is suitable for this strategy, which optimizes the cycle and speed limit options. An objective optimization function is formulated to minimize the total travel time. A sensitivity analysis is applied to compare different control strategies under a variety of road bottleneck structures by both the numerical analysis and simulation experiments. The simulation results show that the strategies and algorithms proposed in this paper can effectively reduce traffic congestion duration and enhance the service level of a freeway network.

Automated summary

Variable speed limit (VSL) strategies have been proven to be effective in mitigating traffic congestion at freeway bottlenecks. In this paper, a dynamic cycle strategy of VSL based on predictive control is developed, which includes an analysis of applicable situations, a probability model for cycle selection, and the use of a transmission model to predict traffic flow. An optimization algorithm is also designed to optimize the cycle and speed limit options. Simulation results demonstrate that the proposed strategies and algorithms can effectively reduce traffic congestion and improve the service level of freeway networks.