【摘要】 人口老龄化的加剧对城市交通提出了新的挑战，提供适老化的轨道交通服务是应对人口老龄化的有效措施。现有研究强调了建成环境对居民地铁出行行为的影响，但老年人特殊的生理特征使其更易受建成环境的影响，现有研究结论是否适用于老年群体尚不清楚。论文以武汉市为例，基于轨道交通刷卡数据等多源大数据，利用机器学习中的梯度提升决策树模型，探索站域建成环境对老年人工作日及周末轨道交通出行行为的影响。研究发现：(1)老年人地铁出行距离从工作日到周末呈现增长趋势，但老年人出行频率周末低于工作日；(2)老年人出行时长集中在45 min以内，跨江出行较少，目的地集中于同区滨江公共服务设施完善的区域，且出行时刻与城市高峰呈现出明显的错峰出行特征；(3)“建筑容积率”与“购物中心数量”是正向影响老年人轨道交通客流量最重要的变量，在工作日与周末呈现类似的趋势；(4)所有建成环境变量对老年人地铁客流展现出显著的非线性效应，当建筑容积率达到2.0、购物中心数为18个时，对老年人地铁客流吸引力最大；(5)与其他人群研究结论不同的是，“公交站点密度”与“土地利用混合度”对老年人轨道交通客流量的影响并不显著。研究结果可以更好地理解老年人地铁出行时空特征及建成环境的影响，对于应对人口老龄化具有十分积极的作用。更多还原

【Abstract】 The increasing aged population poses new challenges to urban transportation, and the provision of agefriendly metro services is an effective measure to cope with population aging. Existing studies have emphasized the influence of the built environment on residents’ metro travel behavior. The special physiological characteristics of the elderly make them more easily affected by the built environment, and it is unclear whether the findings of existing studies are applicable to the elderly people. Taking Wuhan City as an example, this study explored the influence of the built environment of the stations on older people’s weekday and weekend metro travel behavior based on multi-source big data such as metro smart card data and using a gradient boosting decision tree model in machine learning. The results indicate that: 1) Elderly people’s metro travel distance showed a significant increase from weekdays to weekends, but their travel frequency was lower on weekends than on weekdays. 2) The travel length of the elderly was concentrated within 45 minutes. The cross-river travel of elderly was less, and the destination of this group was concentrated in the areas with better public service facilities along the riverfront in the same district, and the travel time showed obvious temporal mismatch with the urban commuting peak. 3) Building floor area ratio and the number of shopping centers were the most important variables, and they showed similar trends on weekdays and weekends. 4) All built environment variables showed significant non-linear effects on elderly’s ridership, with the highest effect occurring when the floor area ratio reached 2.0 and the number of shopping centers was 18. 5) Unlike other studies, the effects of density of bus stops and land use mixture on the ridership of the elderly were not significant. The results of the study can help better understand the spatiotemporal characteristics of metro travel for the elderly and the impact of the built environment, which has a very positive effect on coping with population aging.更多还原