轨道新线对公共交通乘客吸引力影响因素研究

Assessment of Impact Factors on Passenger Attraction of New Metro Line

研究轨道交通新线对公共交通乘客的吸引力影响因素,有助于理解公共交通乘客的出行方式选择行为,预判新线开通带来的客流变化,以提高公共交通运力投放效率和整体服务水平。本文利用公交智能卡数据构建量化评价轨道新线吸引力影响因素的分类与回归树(Classification and Regression Tree,CART)模型,实证分析轨道新线吸引力与乘客特征间的相关关系。首先,从长时期的刷卡记录中挖掘乘客类型、出行习惯、出行特征和职住地轨道可达性等乘客特征指标;其次,以开通后的乘车次数表征新线吸引力,基于上述特征指标构建整体精度为82.6%的轨道新线吸引力影响因素解析决策树模型;最后,依据决策树结构和指标权重量化解析影响轨道新线对公共交通乘客吸引力的关键因素。分析结果表明,居住地距新线距离是影响新线对其吸引力最重要的因素,其次是居住地的轨道可达性水平及乘客联乘出行比例;而出行时间、出行距离等因素对轨道新线吸引力的影响较小。此外,轨道新线对老年乘客的吸引力与其他群体存在明显差异。本文研究成果对优化公共交通规划与运营组织具有重要指导意义。

Understanding the factors that impact the competitiveness of new metro lines can not only provide insight into passengers'commuting choices and enable us to anticipate the impact of future metro routes but also optimize the overall public transport capacity and service quality.This paper utilizes a classification and regression tree(CART)model to analyze the relationship between the new metro line's competitiveness and individual passengers'travel characteristics.At first,the individual passenger's travel characteristics,such as passenger types,travel habits,travel types,and home-work metro accessibility,are collected from each individual's long-term smart card data.Secondly,the competitiveness of the new metro line is represented by its ridership.The CART model is then built based on the abovementioned characteristics and it is proven robust with an 82.6%classification accuracy.At last,a comprehensive analysis of the model structure and factors weights reveals the significance of the factors that impact the attractiveness of the new metro line.The results indicate that the distance between the residence and the new line is the most critical factor in the new line's competitiveness.The metro accessibility of the residence and the rate of multimodal traveling are two factors that have a minor impact.In addition,the trip's duration and distance have little impact,while the level of interest for older passengers differs from other age groups.The study's findings will undoubtedly improve the planning and operation of public transportation.