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Cooperative Merging Strategy for Connected Vehicles at Highway On-Ramps

机译:高速公路匝道上的互联车辆合作合并策略

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摘要

As traffic demands increase rapidly on highways, effective merging strategies are necessary to cooperate with intelligent vehicles and improve traffic operations. Existing merging algorithms for connected vehicles rarely consider the inflow from on-ramps. Also, the merging order of vehicles is generally generated based on very simple rules. In this paper, a cooperative merging strategy is developed for vehicles wirelessly connected to other vehicles and roadside infrastructure. The cooperative merging is formulated as an optimization problem, which takes as objectives the minimization of travel time of mainline vehicles and maximization of the number of merging vehicles. This problem is solved by a genetic algorithm. The effectiveness of this strategy is verified in MATLAB with various simulation scenarios. By comparing the simulation results with a platoon-velocity-based merging strategy, the cooperative merging scheme proves to improve traffic performance in terms of traffic efficiency and fuel consumption. Significant improvements are obtained, especially when mainline and on-ramp demand are both particularly high. To conclude, the proposed strategy is applicable to cooperative merging operations under saturated traffic conditions.
机译:随着高速公路上交通需求的快速增长,必须有有效的合并策略来与智能车辆合作并改善交通运营。现有的用于连接车辆的合并算法很少考虑坡道上的流入。而且,通常基于非常简单的规则来生成车辆的合并顺序。本文针对无线连接到其他车辆和路边基础设施的车辆开发了一种协作合并策略。协作合并被表述为一个优化问题,该优化问题的目标是使主干车辆的行驶时间最小化和合并车辆的数量最大化。该问题通过遗传算法解决。该策略的有效性已在MATLAB的各种仿真方案中得到了验证。通过将仿真结果与基于行速度的合并策略进行比较,协作合并方案证明可以提高交通效率和燃油消耗。获得了显着的改进,尤其是当干线和入口需求都特别高时。总之,所提出的策略适用于在饱和交通条件下的合作合并操作。

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