The invention provides a car-following model parameter calibration method based on a multi-dimensional search neighborhood artificial bee colony algorithm, and belongs to the field of traffic flow model parameter calibration, and the method comprises the following steps: improving an original artificial bee colony algorithm ABC to obtain a multi-dimensional search neighborhood artificial bee colony algorithm MDNABC; the acceleration of the vehicle is selected as a performance index, and a target function for vehicle following model parameter calibration is constructed; based on the NGSIM data set, the acceleration, the position and the vehicle distance information of the vehicle are obtained, and car-following data are formed; and substituting the car-following data into a car-following model, calibrating parameters of the car-following model by using an MDNABC algorithm, and judging a calibration result according to a target function. The MDNABC algorithm is applied to parameter calibration of the vehicle following model, the calibration result shows that the algorithm provided by the invention has a better calibration result compared with a traditional genetic algorithm, and the algorithm has obvious advantages in the aspects of solving speed and solving precision.
本发明提供了一种基于多维搜索邻域人工蜂群算法的跟驰模型参数标定方法,属于交通流模型参数标定领域,包括以下步骤:对原始人工蜂群算法ABC进行改进,得到多维搜索邻域人工蜂群算法MDNABC;选择车辆的加速度为性能指标,构建车辆跟驰模型参数标定的目标函数;基于NGSIM数据集获取车辆的加速度、位置和车间距信息,构成跟驰数据;将所述跟驰数据代入车辆跟驰模型,利用MDNABC算法对车辆跟驰模型参数进行标定,根据目标函数判断标定结果。本发明将MDNABC算法应用于车辆跟驰模型的参数标定,标定结果表明基于本发明提出的算法相比传统的遗传算法具有更好的标定结果,在求解速度和求解精度两方面,均具有明显优势。
Car-following model parameter calibration method based on multi-dimensional search neighborhood artificial bee colony algorithm
基于多维搜索邻域人工蜂群算法的跟驰模型参数标定方法
2023-09-22
Patent
Electronic Resource
Chinese
IPC: | G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS / G06F ELECTRIC DIGITAL DATA PROCESSING , Elektrische digitale Datenverarbeitung / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen |
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