Journal of Jilin University(Engineering and Technology Edition) ›› 2026, Vol. 56 ›› Issue (8): 2106-2115.doi: 10.13229/j.cnki.jdxbgxb.20250061

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Trajectory data⁃driven taxi travel characteristics analysis and spatial⁃temporal distribution modeling

Jun-yue WANG(),Chun-jiao DONG(),Jing WANG,Ming-zhi WANG   

  1. Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport，Beijing Jiaotong University，Beijing 100044，China
  • Received:2025-01-17 Online:2026-08-01 Published:2026-09-02
  • Contact: Chun-jiao DONG E-mail:22110286@bjtu.edu.cn;cjdong@bjtu.edu.cn

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Abstract:

Based on the global positioning system （GPS） trajectory data of taxis in Beijing and the map matching function of ArcGIS， appropriate threshold values were selected， a taxi travel information database was constructed， and the travel characteristics of taxis were analyzed. Firstly， a taxi travel network was built， and spatial and temporal distribution features of travel trajectories were analyzed using kernel density and hot spot analysis methods， revealing the changing trend of taxi travel density during peak hours. Then， considering the impact of land use on taxi travel distribution， a dual-constraint population weight opportunity model based on land use was established to predict taxi travel distribution. The results show that the model improves the prediction accuracy of taxi inter-district travel， with the root mean square error reduced from 4.54 trips to 4.41 trips， and the similarity between the predicted results and actual data improved from 0.961 to 0.970. The average relative error in the number of trips decreased from 0.48% to 0.19%.

Key words: urban traffic, travel characteristics, population weighted opportunity model, land use characteristics, taxis

CLC Number: 

  • U491

Fig.1

Schematic diagram of taxi travel"

Fig.2

Characteristics of distribution of taxi travel behavior indicators"

Fig.3

Trajectory distribution of taxis during morning and evening rush hours"

Table 1

Relationship between different confidence level critical p-values and z-scores"

z得分p值置信度/%
<-1.65或>+1.65<0.1090
<-1.96或>+1.96<0.0595
<-2.58或>+2.58<0.0199

Fig.4

Taxi traffic density and hotspots in Beijing on September 25， 2019"

Fig.5

Schematic diagram of population from destination to origin"

Fig.6

Validity test and error analysis of opportunity model of population weight based on land use characteristics with double constraints"

Fig.7

Generation and attraction of taxis in each administrative region of Beijing"

[1] 马健霄, 赵飞燕, 尹超英, 等. 建成环境和出租车需求对网约车出行需求影响的时空间分异模式[J]. 交通运输系统工程与信息, 2023, 23(5): 136-145.
Ma Jian-xiao, Zhao Fei-yan, Yin Chao-ying, et al. Spatial-temporal heterogeneity effects of built environ-ment and taxi demand on ride-hailing demand[J]. Journal of Transportation Systems Engineering and Information Technology, 2023, 23(5): 136-145.
[2] Jiang B, Yin J, Zhao S. Characterizing the human mobility pattern in a large street network[J]. Physical Review E: Statistical, Nonlinear, and Soft Matter Physics, 2009, 80(2): No.021136.
[3] Bazzani A, Giorgini B, Rambaldi S, et al. Stati-stical laws in urban mobility from micro-scopic GPS data in the area of Florence[J]. Journal of Statistical Mechanics: Theory and Experiment, 2010, 2010(5): No.P05001.
[4] Liang X, Zheng X, Lv W, et al. The scaling of human mobility by taxis is exponential[J]. Physica A: Statistical Mechanics and its Applications, 2012, 391(5): 2135-2144.
[5] Simini F, González M C, Maritan A, et al. A universal model for mobility and migration patterns[J]. Nature, 2012, 484(7392): 96-100.
[6] Riccardo G, Armando B, Sandro R. Towards a statistical physics of human mobility[J]. International Journal of Modern Physics C, 2012, 23(9): No.1250061.
[7] Peng C, Jin X, Wong K, et al. Collective human mobility pattern from taxi trips in urban area[J]. PLoS One, 2012, 7(4): No.e34487.
[8] Ren Y, Ercsey-Ravasz M, Wang P, et al. Predicting commuter flows in spatial networks using a radiation model based on temporal ranges[J]. Nature Communications, 2014, 5(1): No.5347.
[9] Zhao Z, Yang Z, Zhang Z, et al. Emergence of sca ling in human-interest dynamics[J]. Scientific Reports, 2013, 3(1): No.3472.
[10] Yan X, Wang W, Gao Z, et al. Universal model of individual and population mobility on diverse spatial scales[J]. Nature Communications, 2017, 8(1): No.1639.
[11] Liu E, Yan X. A universal opportunity model for human mobility[J]. Scientific Reports, 2020, 10(1): 4657.
[12] 陶思然, 叶霞飞. 引入旅游偏好的城际客运出行分布预测模型[J]. 交通运输系统工程与信息, 2021, 21(4): 140-147.
Tao Si-ran, Ye Xia-fei. A forecasting model of intercity trip distribution with tourism preference[J]. Journal of Transportation Systems Engineering and Information Technology, 2021, 21(4): 140-147.
[13] 陈启香, 吕斌, 陈喜群, 等. 空间异质性建成环境对出租车与地铁竞合关系的影响[J]. 交通运输系统工程与信息, 2022, 22(3): 25-35.
Chen Qi-xiang, Lv Bin, Chen Xi-qun, et al. Impacts of built environment on competition and cooperation relationship between taxi and subway considering spatial heterogeneity[J]. Journal of Transportation Systems Engineering and Information Technology, 2022, 22(3): 25-35.
[14] 邢雪, 王菲, 李佳楠. 结合载客热点和POI的出租车停车位划定方法[J]. 吉林大学学报: 信息科学版, 2024, 42(1): 93-99.
Xing Xue, Wang Fei, Li Jia-nan. Cab fixed parking area delineation method combining passenger hotspot and POI data[J]. Journal of Jilin University (Infor- mation Science Edition), 2024, 42(1): 93-99.
[15] Xiao Z, Wu L, Jiang H, et al. Exploring intercity mobility in urban agglomeration: Evidence from private car trajectory data[J]. IEEE Transactions on Computational Social Systems, 2024, 11(2): 2940-2954.
[16] Deng J, Cui Y, Chen X, et al. Who are on the road? a study on vehicle usage characteristics based on one-week vehicle trajectory data[J]. International Journal of Digital Earth, 2023, 16(1): 1962-1984.
[17] 闫小勇. 超越引力定律: 空间交互和出行分布预测理论与方法[M]. 北京: 科学出版社, 2019.
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