北京市居民地铁出行出发时间弹性时空分布特征研究

伴随城市转型进程的加快,交通需求不断膨胀,导致大城市交通拥堵日趋严重,以调节出行者的选择行为为核心要素的交通需求管理理念成为相关政策的重要理论基础,但现有研究也表明,交通需求管理对出行弹性较高的出行具有显著调节作用,而对出行弹性较低的出行调节作用并不明显。因此,加强出行弹性等居民出行行为研究日益迫切,而公交刷卡数据等新的时空数据为居民复杂出行行为的挖掘提供了新的契机。本文利用北京市2014年3月地铁刷卡数据,以出行者出发时刻的可变性来测度出发时间选择的可改变程度,对居民地铁出行出发时间选择弹性进行测度,并结合GIS空间分析技术对其时空分布特征进行分析。研究表明：① 北京市地铁出行的居民出行弹性平均值为0.521,出发时间选择弹性整体上较大,表明北京居民出发时间选择相对较为灵活;② 北京市居民地铁出行弹性存在时空差异,居民个体休息日出行弹性高于工作日,一天中高峰时段出行弹性高于非高峰时段;③ 居民出行弹性存在空间自相关,倾向于在空间上发生集聚,存在明显的冷热点区域;内城居民的出行弹性明显高于城市外围居民。

Spatial and Temporal Distribution Characteristics of Residents' Depart Times Elasticity in Beijing

With the acceleration of the urbanization, residents' traffic demand has been continuously increasing, resulting in increasingly severe traffic congestion in large cities. The concept of traffic demand management(TDM） has become an important theoretical basis for relevant policies, but the existing research also shows that TDM has a significant adjustment effect on travel with higher flexibility, while the regulation of travel with lower flexibility is not obvious.Research on mobility behaviors such as travel flexibility has become increasingly urgent, and the new spatio-temporal data, such as smart traffic card data, has provided new opportunities to explore the complex of the residents' travel behavior. Travel elasticity refers to the traveler’s preference for the choice of decision variables over a long period of time. It is the selected probability and discreteness of the selection in the travel decision. It is usually used to measure the room for changes in the travel choice behavior, including time elasticity, travel mode flexibility, route flexibility, fare elasticity, etc. In this paper, we measured the travel elasticity of the residents' departure time who takes the subway to work and analyzed the spatial and temporal distribution features based on the smart traffic card data of residents in Beijing in March 2014. The results showed: (1) The average travel elasticity of residents in Beijing who go to work by subway is 0.521. It shows that the overall travel of residents is still relatively flexible, and it also confirms the effectiveness of this research method in revealing the characteristics of residents' travel behavior. (2) There are spatial and temporal differences in the flexibility of Beijing residents. The elasticity of the individual's is higher in the rest days than that of the working day. The elasticity during the peak hours is higher than that in off-peak hours. (3) There are also spatial agglomerations of travel flexibility. Travel elasticity has spatial autocorrelation, tends to agglomerate in space, and there are obvious hot spot areas. At the same time ,the inner city residents' travel flexibility is significantly higher than that of the outskirts of the city.