基于模糊算法的停车诱导与交通流控制协同优化模型

Optimization Model of Parking Guidance Coordinated with Traffic Flow Control Based on Fuzzy Algorithm

在停车诱导和交通流控制双重目标函数约束下,建立了停车诱导与交通流控制协同优化模型。首先,以备选停车场泊位饱和度和路段交通流饱和度等作为约束条件,建立分层搜索模型,确定停车场初始解集。然后,采用模糊优选方法进行初始备选方案的排序研究,通过隶属函数对各备选停车场方案的原始数据进行标准化处理,并通过备选方案与基准方案的贴近度数值求得最优解。最后,以安徽省铜陵市中心城区某停车小区作为计算实例,证明了停车诱导与交通流控制协同优化模型能够成功地应用实施。

Based on the double object-function constraints of parking guidance and traffic flow control, optimization model of parking guidance coordinated with traffic flow control was constructed. Under restrictive conditions, such as spare parking saturation and traffic flow saturation of road segment, the hierarchy search model was established to confirm the initialized results. Sequence of initial spare project was studied by fuzzy algorithm. The original results of each spare park were standardized through subordinate function. The optimized results were got through the close rate between the spare project and standard project. At last, the model was validated by an example of parking section in central city of Tongling of Anhui Province. It shows that the model can be applied successfully.