Abstract: Aiming at the traffic flow mixed with regular manual driving vehicles and intelligent assistant driving vehicle platoons, the characteristics of traffic capacity were analyzed. A probabilistic analytical expression of traffic flow mixed with intelligent assistant driving vehicles platoons was built. Meanwhile, the intelligent driver model and full velocity difference model were applied respectively as the car-following models of intelligent assistant driving vehicles and manual driving vehicles. Then, the fundamental diagram model of the mixed traffic flow was deprived. Based on this, the traffic capacity of mixed flow was analyzed. Finally, for the intelligent assistant driving vehicle market rate p, the maximum fleet size S of intelligent assistant driving fleet and the intelligent assistant driving level e, the parameter sensitivity analysis was carried out respectively. The research results show that the traffic capacity of the mixed flow improves with the increase of p. When p≤0.2, the traffic capacity improvement is not significant; when p≥0.4, the traffic capacity improves significantly. With the increase of p, the optimal value of the maximum platoon size S is also different. When p≤0.4, the optimal value of S is 2; when p≥0.6, the optimal value of S is 4. The effect of e on traffic capacity is greatly restricted by p. When p≤0.2, e has no significant effect on the improvement of traffic capacity; when p≥0.4, e has a significant impact on traffic capacity.

Key words: traffic engineering; traffic capacity; intelligent assistant driving vehicle platoons; fundamental diagram model; mixed traffic flow

摘要： 针对常规人工驾驶车辆和智能辅助驾驶车队的混合交通流，分析了它们的通行能力特性。通过构建含有智能辅助驾驶车队的混合流及其概率解析表达，应用智能驾驶员模型和全速度差模型分别作为智能辅助驾驶车辆和人工驾驶车辆的跟驰模型，推导了混合流的基本图模型，以此分析混合流通行能力。针对智能辅助车辆市场占有率p、智能辅助驾驶车队最大车队规模S、智能辅助驾驶等级e，分别进行参数敏感性分析。研究结果表明：混合流的通行能力随着p的增加而上升，当p≤0.2时，通行能力提升不显著，当p≥0.4时，通行能力提升显著；随着p增加，S最优取值也不同，当p≤0.4时，S最优值为2，当p≥0.6时，S最优值为4；e对通行能力作用效果受到p的制约很大，当p≤0.2时，e对通行能力的提升作用不显著，当p≥0.4时，e对通行能力的影响较为显著。

关键词: 交通工程；通行能力；智能辅助驾驶车队；基本图模型；混合交通流