基于机场客流量与司机收益的决策模型  

Decision Making Model Based on Airport Passenger Flow and Driver Income

作　　者：牟丹 浦春雪 于晶 张丽春[1] MOU Dan;PU Chunxue;YU Jing;ZHANG Lichun(Mathematics and Statistics College of Beihua University,Jilin 132013,China)

机构地区：[1]北华大学数学与统计学院,吉林吉林132013

出　　处：《北华大学学报（自然科学版）》2022年第2期253-258,共6页Journal of Beihua University（Natural Science）

基　　金：吉林省高等教育教改研究项目(SJYB2020001);吉林省教育科学规划项目(GH20282);北华大学教改研究重点课题(XJZD2021024).

摘　　要：为提高司机总收益及运营效率,研究机场客流量与司机收益以及乘车效率之间关系,建立司机决策模型.通过灰色预测模型预测机场客流量变化以及所需出租车量;运用AR时间序列模型得到自回归模型,预测各因素下出租车数量变化,建立司机选择决策模型;利用北京首都国际机场数据检验模型,考虑出租车载客所需时间、车辆调度时间、载客出租车离去消散时间等因素,基于排队论,建立多点纵列式排队服务系统,以提高总乘车效率.On the purpose of improving driver’s total income and operating efficiency,the relationship among airport passenger flow,driver’s income and riding efficiency were investigated,and a model for driver determinations was established.The grey prediction model was used to predict the change of airport passenger flow with the corresponding taxi requirement.After gaining the autoregressive model via the AR time series model,we forecasted the variability of taxi number including all sorts of factors so as to build the driver selection decision model accordingly.Meanwhile,utilizing the data of Beijing Capital Airport,the accuracy of the model was validated.Taking the taxi passenger carrying time,vehicle scheduling time,taxi departure dissipation time and so forth into account,we constructed a multi-point longitudinal queuing service system based on the queuing theory,which improved the total efficiency in ride.

关 键 词：灰色预测模型 AR时间序列模型 自回归模型 多点纵列式排队服务系统 

分 类 号：U492.43[交通运输工程—交通运输规划与管理]