高速公路的交通流存在很大的不确定性,模糊逻辑是解决其控制问题的有效方法。对传统的ALINEA模型进行了扩展,提出一种新的自适应模糊匝道控制器。当高速公路路段的临界密度不能被预先正确估计或者因交通环境的实时变化而难以估计时,提出的自适应模糊控制器将显示出其优越性。在仿真试验中,根据交通流的各种性能指标,将新的自适应控制器同传统的ALIN-EA方法做了详细的对比。 There is great uncertainty in the traffic flow of freeway, and fuzzy logic is an effective way to solve the control problem. The traditional ALINEA model is extended and a new adaptive fuzzy ramp controller is proposed. The proposed adaptive fuzzy controller will show its superiority when the critical density of freeway sections can not be estimated in advance or is difficult to estimate due to the real-time changes of traffic environment. In the simulation experiment, the new adaptive controller is compared with the traditional ALIN-EA method according to various performance indexes of traffic flow.