Cooperative adaptive cruise control (CACC) has shown great potential in improving freeway capacity. Although the benefit of CACC is obvious, its potential side effects are not yet well studied. One of the major factors that have been overlooked is merging behaviour. A driving simulator study has been recently conducted at the Federal Highway Administration of the United States and reveals that there is unique driving behaviour when joining and leaving a CACC platoon. Unlike the conventional merging model which is a passive decision action, merging into a CACC platoon is a proactive action. Without simulating this unique behaviour, any simulation evaluation on CACC is biased. To improve the validity of future CACC simulation evaluation, this research constructs a merging model. The model consists of two parts: the longitudinal trajectory model and the merging duration prediction model. The model was constructed for both human manual driver and CACC automated controller. The evaluation of the proposed model shows that the model is 96.5% accurate in terms of merging duration prediction and 95.2% accurate in terms of speed prediction.

中文翻译：

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建模行为的联合自适应巡航控制排

自适应巡航控制系统（CACC）在提高高速公路通行能力方面显示出巨大潜力。尽管CACC的好处是显而易见的，但其潜在的副作用尚未得到很好的研究。被忽略的主要因素之一是行为合并。美国联邦公路管理局最近进行了一项驾驶模拟器研究，结果表明，加入和离开CACC排时，驾驶行为是独特的。与传统的合并模型（它是一种被动的决策动作）不同，合并到CACC排中是一种主动的动作。在不模拟这种独特行为的情况下，对CACC进行的任何模拟评估都是有偏差的。为了提高未来CACC仿真评估的有效性，本研究构建了一个合并模型。该模型包括两个部分：纵向轨迹模型和合并持续时间预测模型。该模型是为人工驾驶员和CACC自动化控制器构建的。对该模型的评估表明，该模型在合并持续时间预测方面的准确度为96.5％，在速度预测方面的准确度为95.2％。