The invention discloses a bus running state evaluation method based on GPS data. The method comprises the steps: dividing bus running states into an aggregation state, an aggregation transition state,a normal state, a large-interval transition state and a large-interval state; determining an operation state threshold: dividing the data set of the eigenvalue headway into different categories, sorting the clustering centers of each category from small to large, and taking the average value of the clustering centers of the adjacent categories as each state threshold; determining indexes, and establishing a bus space-time cluster probability model, space probability distribution fitting and time probability distribution fitting; and finally, establishing a multi-classification Logistic bus cluster prediction model, judging the state transition probability of the bus running state on the line according to the established prediction model, and evaluating the bus running state. The method isconvenient and fast, and the bus service level is improved; the method has higher prediction precision, so passengers can better know the bus operation condition and reasonably regulate and control the travel time.
本发明公开了一种基于GPS数据的公交运行状态评估方法,包括公交运行状态划分为集结态、集结过渡态、常态、大间隔过渡态和大间隔状态;运行状态阈值确定:将特征值车头时距的数据集划分为不同的类别,各类别聚类中心从小到大排序,相邻类别聚类中心平均值即为各状态阈值。确定指标、建立公交时空集簇概率模型、空间概率分布拟合和时间概率分布拟合;最后建立多分类Logistic公交集簇预测模型,根据所建立的预测模型判定公交运行状态在线路上的状态转移概率,作出公交运行状态评估。本发明方便快捷,提升公交服务水平;具有较高预测精度,使乘客能够更好地了解公交运行情况,合理调控出行时间。
Bus running state evaluation method based on GPS data
一种基于GPS数据的公交运行状态评估方法
2020-06-26
Patent
Electronic Resource
Chinese
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