Group airport passengers travel recommendation method based on secondary induction

CHAI Lin-guo; RUI Tao; SHANGGUAN Wei; CAI Bai-gen

doi:10.19818/j.cnki.1671-1637.2023.06.020

Volume 23 Issue 6

Dec. 2023

Turn off MathJax

Article Contents

Article Navigation > Journal of Traffic and Transportation Engineering > 2023 > 23(6): 301-313

Next Previous

CHAI Lin-guo, RUI Tao, SHANGGUAN Wei, CAI Bai-gen. Group airport passengers travel recommendation method based on secondary induction[J]. Journal of Traffic and Transportation Engineering, 2023, 23(6): 301-313. doi: 10.19818/j.cnki.1671-1637.2023.06.020

Citation:

CHAI Lin-guo, RUI Tao, SHANGGUAN Wei, CAI Bai-gen. Group airport passengers travel recommendation method based on secondary induction[J]. Journal of Traffic and Transportation Engineering, 2023, 23(6): 301-313. doi: 10.19818/j.cnki.1671-1637.2023.06.020

Citation:

PDF( 7090 KB)

Group airport passengers travel recommendation method based on secondary induction

doi: 10.19818/j.cnki.1671-1637.2023.06.020

CHAI Lin-guo^{1, 2
,},
RUI Tao³,
SHANGGUAN Wei^{1, 2
,
,},
CAI Bai-gen^{1, 2}

1.
School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing 100044, China
2.
State Key Laboratory of Advanced Rail Autonomous Operation, Beijing Jiaotong University, Beijing 100044, China
3.
Wuhan Branch of China Railway Major Bridge Reconnaissance and Design Institute Co., Ltd., Wuhan 430073, Hubei, China

Funds:

National Key Research and Development Program of China 2018YFB1601200

More Information

Author Bio:
CHAI Lin-guo(1988-), male, associate professor, PhD, lgchai@bjtu.edu.cn
Received Date: 2023-06-25
Publish Date: 2023-12-25

Abstract

Abstract

In view of the personalized travel needs of passengers and the requirements of rapid airport evacuation, a travel recommendation method for group airport passengers based on the secondary induction was proposed on the basis of the fixed allocation of each travel mode of landside transportation, so as to provide algorithmic support for customized passenger services. Based on the original passenger data, and combined with the rough set theory, the knowledge reduction of feature attributes was carried out to improve the performance of the algorithm. The improved Bayesian classification algorithm was used to quantify the travel mode recommendation degree based on the calculation of the independent feature probability of passengers, and the passenger travel recommendation sequence based on the primary induction was generated. In view of the constraint of fixed capacity allocation of each travel mode on the landside of the airport, the passenger travel recommendation sequence was input into the secondary-induced travel recommendation model of passengers based on the improved non-dominated sorting genetic algorithm (NSGA-Ⅱ) to deeply match the transport capacity and passenger flow, and the passenger travel recommendation results were optimized again. Based on the principle of universality, the small-scale (100 people) and large-scale (1 000 people) passenger samples were used for model validation. Analysis results show that good results can be obtained under the inputs of passenger flows with different scales. The correct rate of passenger travel mode recommendation in the small-scale sample is 77.41%. Under the large-scale sample, the correct rate of passenger travel mode recommendation is 79.62%. After the secondary induction, the matching degree between the recommended travel distribution of passenger flow and the transport capacity greatly improves compared with the real travel and the primary induction distribution. On the basis of high matching between the passenger flow and the transport capacity, the passenger travel preference needs are realized. The algorithm has good performance and provides a practical method to improve the passenger flow evacuation of hub airports.

FullText(HTML)

References(30)

References

[1]	HE Yu-gang. Civil aviation transportation industry and economic growth: an investigation from China[J]. Journal of Tourism and Industry Research, 2018, 38(4): 5-14.
[2]	CHOO S, YOU S, LEE H. Exploring characteristics of airport access mode choice: a case study of Korea[J]. Transportation Planning and Technology, 2013, 36(4): 335-351. doi: 10.1080/03081060.2013.798484
[3]	TABARES D A. An airport operations proposal for a pandemic-free air travel[J]. Journal of Air Transport Management, 2021, 90: 101943. doi: 10.1016/j.jairtraman.2020.101943
[4]	ZHAO Yi-fei, XIAO Tong-tong, WAN Jun-qiang. Evolution of air traffic control system of Chinese Civil Aviation[J]. Journal of Traffic and Transportation Engineering, 2020, 20(2): 100-120. (in Chinese) doi: 10.19818/j.cnki.1671-1637.2020.02.009
[5]	LIU Xiao-ming, XIA Hong-shan. Estimating methods of passenger throughput for hub airport based on reverse gravity model[J]. Journal of Traffic and Transportation Engineering, 2008, 8(2): 85-89. (in Chinese) doi: 10.3321/j.issn:1671-1637.2008.02.018
[6]	LI Guo-dong, HU Ya-ru. Empirical study on the balance degree between China's civil aviation industry development and population distribution[J]. China Transportation Review, 2018, 40(1): 11-16, 67. (in Chinese)
[7]	LIU Yu, WANG Wei-jie, HUANG Hong-zhong, et al. A new simulation model for assessing aircraft emergency evacuation considering passenger physical characteristics[J]. Reliability Engineering and System Safety, 2014(121): 187-197.
[8]	FAN Ai-hua, CHEN Xu-mei, WANG You-an, et al. All-stop, skip-stop, or transfer service: an empirical study on preferences of bus passengers[J]. IET Intelligent Transport Systems, 2018, 12(10): 1255-1263. doi: 10.1049/iet-its.2018.5213
[9]	GAN Jin-jun, ZHOU Zhong-yu. On organic unity of airport with four features and air traffic control with four strengths[J]. Journal of Civil Aviation, 2021, 5(4): 29-31. (in Chinese)
[10]	WU Xiao-kun, ZHAO Tian-fang, CHEN Wei-neng, et al. Toward predicting active participants in tweet streams: a case study on two civil rights events[J]. IEEE Transactions on Knowledge and Data Engineering, 2020, DOI: 10.1109/TKDE.2020.3017635.
[11]	LIU Xiao-fei, ZHU Fei, FU Yu-chen, et al. Personalized recommendation algorithm based on user preference feature mining[J]. Computer Science, 2020, 47(4): 50-53. (in Chinese)
[12]	WU Cheng-lang, CHEN Yi-meng. Effects of passenger characteristics and terminal layout on airport retail revenue: an agent-based simulation approach[J]. Transportation Planning and Technology, 2019, 42(2): 167-186. doi: 10.1080/03081060.2019.1565163
[13]	WANG Liu, ZHANG Yong, ZHAO Xia, et al. Irregular travel groups detection based on cascade clustering in urban subway[J]. IEEE Transactions on Intelligent Transportation Systems, 2020, 21(5): 2216-2225. doi: 10.1109/TITS.2019.2933497
[14]	YUAN Fu-yong, FENG Jing, FU Qian-qian. Influence index model of micro-blog user[J]. New Technology of Library and Information Service, 2012(6): 60-64. (in Chinese)
[15]	QIU Ying-hui, HE Zhen-huan. A research on passenger's travel choice behavior in high-speed railway based on passenger survey questionnaire[C]//IEEE. 2nd International Conference on Applied Mathematics, Modeling and Simulation (AMMS). New York: IEEE, 2018: 277-283.
[16]	GOSLING G D. Use of air passenger survey data in forecasting air travel demand[J]. Transportation Research Record, 2018(2449): 79-87.
[17]	ARAGHI Y, KROESEN M, MOLIN E, et al. Revealing heterogeneity in air travelers' responses to passenger-oriented environmental policies: a discrete-choice latent class model[J]. International Journal of Sustainable Transportation, 2016, 10(9): 765-772. doi: 10.1080/15568318.2016.1149645
[18]	WEI Wei, WANG Cheng. Design of air passenger travel choice intention prediction system based on deep learning[J]. Scientific Programming, 2022, 2022: 7340552.
[19]	ZHONG Xiang, HAN Xu, ZHU Cai-yun, et al. Airport passenger grouping model based on dichotomic K-means algorithm[J]. Journal of Civil Aviation University of China, 2018, 36(3): 37-40. (in Chinese)
[20]	WU Qi-lin, LU Hai-qin, WANG Yang, et al. Research on intercity travel mode dynamic choice behavior with introduced loyalty variable[J]. Journal of Highway and Transportation Research and Development, 2014, 31(11): 123-129. (in Chinese)
[21]	YIN Xi-chen. Travel recommendation method and application based on passenger profile and trip chain model[D]. Beijing: Beijing Jiaotong University, 2021. (in Chinese)
[22]	WU Xiang-juan, WANG Yu-ping, WANG Zi-qing. A centerline symmetry and double-line transformation based algorithm for large-scale multi-objective optimization[J]. Connection Science, 2022, 34(1): 1454-1481. doi: 10.1080/09540091.2022.2075828
[23]	MARTINEZ-ALVAREZ A, CRESPO-CANO R, DIAZ-TAHOCES A, et al. Automatic tuning of a retina model for a cortical visual neuroprosthesis using a multi-objective optimization genetic algorithm[J]. International Journal of Neural Systems, 2016, 26(7): 1650021. doi: 10.1142/S0129065716500210
[24]	OLIVETO P S, SUDHOLT D, ZARGES C. On the benefits and risks of using fitness sharing for multimodal optimisation[J]. Theoretical Computer Science, 2018, 773(2019): 53-70.
[25]	ZHU Shu-wei, XU Li-hong, GOODMAN E D, et al. A new many-objective evolutionary algorithm based on generalized pareto dominance[J]. IEEE Transactions on Cybernetics, 2022, 52(8): 7776-7790. doi: 10.1109/TCYB.2021.3051078
[26]	YUAN Yuan, XU Hua, WANG Bo, et al. A new dominance relation-based evolutionary algorithm for many-objective optimization[J]. IEEE Transactions on Evolutionary Computation, 2016, 20(1): 16-37. doi: 10.1109/TEVC.2015.2420112
[27]	LIU Yin-bin, YU Mi-mi, LI Hong-bo, et al. A literature review of multi-objective project scheduling: a perspective on complex system optimization[J]. Journal of Systems Science, 2020, 28(3): 84-89, 111. (in Chinese)
[28]	ZHANG Quan-feng. The research and implementation of capital International Airport roadside passenger transportation techniques[D]. Chengdu: University of Electronic Science and Technology, 2015. (in Chinese)
[29]	NEI Lei, GAO Yi, SHE Liang. Study on the forecast of the passenger flow to Beijing Airport by airport express line and its operation capital plan[J]. Journal of Transportation Systems Engineering and Information Technology, 2009, 9(4): 151-158. (in Chinese)
[30]	DEB K, PRATAP A, AGARWAL S, et al. A fast and elitist multiobjective genetic algorithm: NSGA-Ⅱ[J]. IEEE Transactions on Evolutionary Computation, 2002, 6(2): 182-197.

Relative Articles

Supplements(0)

Cited By

Get Citation

PDF

XML

Article Metrics

Article views (666) PDF downloads(63)

Group airport passengers travel recommendation method based on secondary induction

doi: 10.19818/j.cnki.1671-1637.2023.06.020

Abstract

References

Catalog

Article Metrics

Related

Group airport passengers travel recommendation method based on secondary induction

doi: 10.19818/j.cnki.1671-1637.2023.06.020

Abstract

References

Catalog

Article Metrics

Related

Export File

Citation

Format

Content