Collaborative merging strategy for freeway ramp operations in a connected and autonomous vehicles environment

In a connected vehicle environment, vehicles are able to communicate and exchange detailed information such as speed, acceleration, and position in real time. Such information exchange is important for improving traffic safety and mobility. This allows vehicles to collaborate with each other, which can significantly improve traffic operations particularly at intersections and freeway ramps. To assess the potential safety and mobility benefits of collaborative driving enabled by connected vehicle technologies, this study developed an optimization-based ramp control strategy and a simulation evaluation platform using VISSIM, MATLAB, and the Car2X module in VISSIM. The ramp control strategy is formulated as a constrained nonlinear optimization problem and solved by the MATLAB optimization toolbox. The optimization model provides individual vehicles with step-by-step control instructions in the ramp merging area. In addition to the optimization-based ramp control strategy, an empirical gradual speed limit control strategy is also formulated. These strategies are evaluated using the developed simulation platform in terms of average speed, average delay time, and throughput and are compared with a benchmark case with no control. The study results indicate that the proposed optimal control strategy can effectively coordinate merging vehicles at freeway on-ramps and substantially improve safety and mobility, especially when the freeway traffic is not oversaturated. The ramp control strategy can be further extended to improve traffic operations at bottlenecks caused by incidents, which cause approximately 25% of traffic congestion in the United States.