基于地理流空间的巡游车与网约车人群出行模式研究

Human Travel Patterns by E-hailing Cars and Traditional Taxis based on Geographic Flow Space

城市出租汽车是居民出行的重要方式之一,地理流空间理论为发掘人群出行特征,优化车辆运营效率提供了新视角。本文利用厦门市出租汽车轨迹数据,采用地理流空间分析理论,对人群出行的整体随机性质进行了分析,基于流相似性度量识别并分析了丛集、汇聚、发散和社区4种典型模式及混合模式的空间分布特征,对比了基于巡游车和网约车2种车辆的人群出行模式。结果表明流空间理论能够系统性发现人群出行典型模式及混合模式,主要体现在:①基于2类车辆的人群出行流在空间中呈现出显著的非随机特征;②巡游车和网约车的典型模式在空间分布上有明显差别,网约车的有关模式分布范围更广,在厦门岛外各区中心及岛内东部软件园等区域附近较为突出,且网约车由于其订单由用户需求驱动,更容易发现潜在的高出行需求区域,同时出行结构更容易形成社区模式,而巡游车主要分布在传统岛内知名城市地标附近;③同一区域内巡游车和网约车出行混合模式普遍存在,约占典型模式的四分之一左右,而且不同类型车辆的主要混合模式存在差异,综合考虑混合模式能够提高城市公共设施规划的精确性和科学性。本文结果可以为车辆调度优化和城市交通规划提供支持,也表明地理流空间理论能够更有效揭示地理流对象的空间模式特征。

Traditional taxis and the e-hailing cars are two main transport vehicles for the public in current taxi market,which aim to satisfy the customized travel demand in daily lives of citizens in urban public transportation system.Due to the differences in service modes and commercial patterns,the two vehicles are appropriate for different target groups.Investigating the spatial and temporal characteristics of these two types of vehicle based on human travel flows can support the applications such as optimization of the urban public transportation and land use planning.The geographical flow space theory proposed recently provides a new theoretical perspective as well as a systematical analysis framework in studying the flow patterns of the travels by different types of vehicles.In this paper,we adopt this formulated theory framework to describe the travel flow.We select five typical flow patterns,namely random,clustering,aggregation,divergence,and community patterns,to reveal their spatial distribution characteristics and compare the differences in their travel patterns.The trajectory dataset of traditional taxis and the e-hailing cars in Xiamen City is employed to validate the effectiveness of the geographical flow space theory.We find that:(1)the travel flows of the two types of vehicles present significant non-random characteristics in flow space;(2)people tend to choose e-hailing cars for long distance travel,while prefer the traditional taxis for short and medium distance travels;(3)the two types of cars show different spatial distribution characteristics of the four typical flow patterns.The travels by e-hailing cars are more widely distributed and exhibit clustering patterns around the sub-centers at the suburban areas outside the core Xiamen Island and the east-southern software park area inside the Xiamen Island.Due to the travel demand driven model,the e-hailing cars satisfy the emerging high travel demand areas and tend to form community patterns.While the traditional cars are mainly distributed around the well-known city landmarks(e.g.,Zengcuoan,Zhongshan road)on the Island;(4)approximately a quarter of the local areas have more than one typical flow patterns.Different types of cars exhibit different co-location flow patterns and spatial distribution characteristics.The mixed flow patterns derived from the geographical flow theory provide a more comprehensive perspective to better understand the travel flows,which can mitigate the misleading information from each isolated flow pattern.The above findings imply that the geographical flow theory can help to better understand the characteristics of the geographical flows and can be used to improve the applications based on related results.