Cooperative Merging Strategy for Freeway Ramp in a Mixed Traffic Environment

In order to improve traffic efficiency and reduce traffic accidents, a hierarchical cooperative merging framework was proposed under a mixed traffic condition that is composed of both connected and automated vehicles (CAV) and human-driven vehicles (HDV). The framework integrated the merging sequence scheduling algorithm and the cooperative merging algorithm and adjusted it in real time according to the vehicle type and state. Firstly, a realtime merging sequence scheduling algorithm based on heuristic was proposed to optimize the merging sequence, which can address the drawback that traditional merging sequence scheduling algorithms cannot adapt to the random disturbance of HDV driving behavior. Next, Using the merging sequence scheduling algorithm, the cooperative merging vehicle group as well as the vehicle type was determined according to the position of the vehicles. The cooperative merging algorithm of CAV- CAV, CAV- HDV, and HDV- HDV was established to describe the merging strategy under the mixed traffic flow by mathematical models. Simulation investigations demonstrate that compared with the no-control situation and the "first-in-first-out" strategy, the total delay is reduced by 21.66% and 39.88%, respectively. The length of the cooperative control area has a influence on the fuel consumption, and the energy consumption decreases with the increase of the distance, and there is a minimum value, namely 300 m, after reaching the minimum value, the energy consumption will gradually increase; the increase of the time headway has a certain influence on reducing the energy consumption of the vehicles. Among them, time headway between HDVs has a greater influence on fuel consumption than time headway between CAVs.