可持续TOD建设视角下的轨道站点客流潜力模型构建

轨道是缓解城市交通问题的重要设施，增加出行者选择轨道出行的概率，有利于交通与土地利用协调和TOD可持续发展。本文提出站点客流潜力的概念，并根据复杂网络特征和出行模式构建站点客流潜力模型，通过协调潜力值与实际客流为TOD研究提供新视角。以北京市轨道站点POI数据构建Space-L模型，并依据站点客流潜力模型计算北京市364个站点的客流潜力。研究发现：① 本文提出的站点客流潜力具有吸引力和承载力两类内涵，能定量分析站点空间与站域客流的协调情况；② 北京市站点客流潜力值空间分布为“核心-边缘”模式，区间概率分布为等差数列分类的指数分布和等比数列分类的正态分布；③ 根据出行目的设置四类出行情景。不同情景下出行者选择轨道出行的概率具有差异，早高峰和晚高峰情景下轨道出行概率大，受潜力值影响小，非工作出行情景下轨道出行概率小，受潜力值影响大。实例分析表明相比于单独考虑复杂网络特征，潜力值具有更好的可解释性和科学性；④ 耦合度C 0.5时认定站点失调，其中标准化的实际客流与潜力值的比值Z >1，表示客流过饱和，如西二旗等，会造成站点拥堵，Z 1表示站点交通地理优势未充分发挥，如北运河西等。北京市轨道交通需协调优化以提升效率，实现TOD可持续发展。

Modelling the Passenger Flow Potential of Rail Stations from the Perspective of Sustainable TOD Construction

Rail transit is an important facility to alleviate urban traffic problems, and increasing the probability of passengers choosing rail transit to travel is conducive to the coordination of transportation and land use and the sustainable development of TOD. This paper proposes the concept of rail transit station passenger flow potential and constructs a station passenger flow potential calculation model based on the connotation of complex network eigenvalues and travel patterns, which provides a new perspective for TOD research by coordinating potential values with actual passenger flows. The Space-L model is constructed using POI data of Beijing railway stations, and the passenger flow potential of 364 stations in Beijing is calculated based on the station passenger flow potential model. The results show that 1) The station passenger flow potential values proposed in this paper have the dual connotation of attractiveness and carrying capacity, and can be used to quantitatively analyse the coordination between the Station Space and Station Area Traffic; 2) The spatial distribution of station passenger flow potential values in Beijing shows a "core-edge" pattern, with the most compact circles in non-work travel scenarios. The probability of the interval shows an exponential distribution for the isometric classification and a normal distribution for the isometric classification; 3) Four travel scenarios are set up according to the purpose of travel. The probability of travellers choosing rail travel differs in different scenarios. The probability of choosing rail travel is higher in the morning peak and evening peak scenarios and is less influenced by the potential value, while the probability of choosing rail travel is lower in the non-work travel scenario and is more influenced by the potential value, which is in line with reality. The verification example shows that the potential value has better interpretability and scientific validity than simply considering complex network features; 4) The coupling degree of C< 0.5 identifies the station as out of tune, where the ratio of actual passenger flow to potential value Z >1, indicating that the station is over-saturated and are prone to congestion problems, such as Xi'erqi Station, Tiantongyuanbei Station, Tiantongyuan Station, Fengtai Kejiyuan Station, etc. If Z 1, it means that the geographical advantages of the station's traffic have not been fully exploited and the passenger flow can be further improved, such as Beijingnan Station, Beiyunhexi Station, Wangjingdong Station, etc. Our results indicate that Beijing's rail transport needs to be optimised in order to improve its efficiency and achieve sustainable TOD construction.