【摘要】 准确获取交通状态是实现智能交通的重要环节之一.为实时检测车辆行驶状态,进而提取出当前道路的运行状况,来研究基于手机传感器的车辆行驶状态数据收集及交通状态识别.首先,应用手机内嵌的加速度传感器获取车辆的实时行驶状态数据,然后构建基于SVM的交通状态识别模型.最后,利用一组真实的车辆运行状态数据集,验证提出的交通识别模型,获得了良好的识别性能,平均准确率达到89.05%.更多还原

【Abstract】 Acquiring feasible traffic state data plays important role in developing smart transportation system.To obtain real-time vehicle running status and detect road condition based on the status data,in this work,we investigated sensors based methods for collecting vehicle running status and detecting traffic states.First,we developed an acceleration sensor based method that was responsible for collecting real-time status data vehicles.Second,a SVM-based model was created to detect traffic states.Last,experimental evaluation that was conducted on a set of real-time vehicle running status data showed that our proposed method was feasible and efficient for detecting traffic states,obtaining an average detection of 89.05%.更多还原