基于遗传算法的高速公路网入口匝道优化控制

为了实施高速公路路网交通流的优化控制,采用MATANET模型进行路网交通流建模,应用非线性最优控制方法,构造了路网入口匝道的协调控制模型. 该模型应用全局实时交通数据,以缩短行程时间和减少入口匝道排队长度为控制目标,能够提高交通运行效率和有效处理偶发性拥挤. 针对模型的非线性,应用遗传算法对性能指标进行优化,探究不同性能指标的优化对路网交通运行状况的影响. 以南京市周边高速公路路网作为应用实例,验证了所研究模型与优化方法的可行性.

Optimizing On-Ramp Metering of Freeway Network Using Genetic Algorithm

In order to optimize the control of freeway network traffic flow, MATNET model was used for traffic flow modeling, and nonlinear optimal control was applied to build on-ramp coordination control model. Aiming for shortening travel time and reducing the on-ramp queue length, global real-time traffic data was used in this model, which can improve the operating efficiency of network traffic, and deal with incidental congestion effectively. Considering the nonlinearity of the model, genetic algorithm was used to optimize performance indexes to explore the effect of optimizing different performance index on traffic flow parameters change. At last, the surrounding network traffic of Nanjing was taken as an example to indicate the feasibility of the proposed model and optimization method.