To better understand the characteristics of car–truck heterogeneous traffic flow that is very common on freeway, a cellular automata-based traffic flow model is proposed for single lane traffic in this paper. The proposed model discriminates the four types of car–truck following combination, car-following-car (CC), car-following-truck (CT), truck-following-car (TC) and truck-following-truck (TT). The four combinations are considered in terms of the safety distance, reaction time and randomization probability. The parameter values in the proposed model are derived from NGSIM data. Simulations are conducted based on the new model and some new conclusions about the characteristics of the car–truck traffic flow are drawn. First, in the density range of (23–36) vehs/km, the fundamental diagram mainly depends on the car–truck following combination, especially, on the proportion of CC combination. In this range, the fundamental diagram curves with the same proportion of CC gather into a cluster, and the flow rate increases with the increment of the proportion of CC for the same traffic density. Second, traffic congestion can be effectively reduced up to 6.3% by increasing the proportion of TC or CT combination. This finding provides a possible way to alleviate traffic congestion on freeway. Third, reducing randomization probability of the four combinations can effectively increase traffic capacity and alleviate traffic congestion.

为了更好地理解高速公路上非常常见的车厢异构交通流的特征，本文提出了一种基于细胞自动机的单车道交通流模型。拟议的模型区分了随车组合的四种类型，随车（CC），随车（CT），随车（TC）和随车（TT）。根据安全距离，反应时间和随机化概率来考虑这四个组合。所提出模型中的参数值是从NGSIM数据中得出的。在新模型的基础上进行了仿真，并得出了有关卡车交通流量特性的一些新结论。首先，在（23–36）vehs / km的密度范围内，基本图主要取决于组合后的汽车—卡车，特别是CC组合的比例。在此范围内，具有相同CC比例的基本图曲线会聚在一起，并且在相同交通密度下，流量会随着CC比例的增加而增加。其次，通过增加TC或CT组合的比例，可以有效地将交通拥堵减少至6.3％。这一发现为减轻高速公路上的交通拥堵提供了一种可能的方法。第三，降低这四个组合的随机化概率可以有效地增加流量容量，减轻流量拥塞。通过增加TC或CT组合的比例，可以将交通拥堵有效地减少到6.3％。这一发现为减轻高速公路上的交通拥堵提供了一种可能的方法。第三，降低这四个组合的随机化概率可以有效地增加流量容量，减轻流量拥塞。通过增加TC或CT组合的比例，可以将交通拥堵有效地减少到6.3％。这一发现为减轻高速公路上的交通拥堵提供了一种可能的方法。第三，降低这四个组合的随机化概率可以有效地增加流量容量，减轻流量拥塞。