The invention discloses a mixed traffic flow fusion method based on vehicle-road cooperation, and the method is characterized in that the method comprises the following steps: carrying out the modeling of a vehicle-road cooperation mixed traffic flow, and constructing a vehicle following model based on IDM, CCAC and ACC; in time feature selection, spatial-temporal features of urban traffic flow are extracted from three dimensions of hour, day and weekly by using a residual network, and comprehensive analysis of flow data of different time dimensions is realized; in the external feature reconstruction, external information is added, a multi-layer perceptron is adopted to extract external features, and the external features and time features have the same dimension through reconstruction; and converting external information into vector representation by using a full-connection neural network model, and fusing the mixed driving information, the time characteristics and the external information in a weighted summation mode to obtain mixed traffic flow fusion data in a vehicle-road coordination environment. According to the fusion method, information of various data sources can be better utilized, and more reliable decision support is provided for vehicle-road cooperation.
本发明一种基于车路协同的混合交通流融合方法,其特征在于:包括以下步骤:对车路协同的混合交通流进行建模,基于IDM、CCAC和ACC,构建车辆跟驰模型;在时间特征选择中,利用残差网络从小时、天、周三个维度提取了城市交通流的时空特征,实现了对不同时间维度的流量数据的综合分析;在外部特征重构中,通过加入外部信息,采用多层感知器提取外部特征,并通过重构使其与时间特征具有相同维度;利用全连接神经网络模型将外部信息转换成向量表示,并通过加权求和的方式将混合驾驶信息、时间特征与外部信息相融合,得到车路协同环境下混合交通流融合数据。这种融合方法能够更好地利用多种数据源的信息,为车路协同提供更可靠的决策支持。
Vehicle-road collaborative mixed traffic flow data fusion method
车路协同混合交通流数据融合方法
2024-08-09
Patent
Electronic Resource
Chinese
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