A Method for Improved Air Luggage Check-in Service Based on Optimized Urban Mobile Stations

HU Xiaobing; ZHANG Xuemei; ZHOU Hang; MA Yiming

doi:10.3963/j.jssn.1674-4861.2022.03.014

Volume 40 Issue 3

Jun. 2022

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Article Navigation > Journal of Transport Information and Safety > 2022 > 40(3): 136-145

HU Xiaobing, ZHANG Xuemei, ZHOU Hang, MA Yiming. A Method for Improved Air Luggage Check-in Service Based on Optimized Urban Mobile Stations[J]. Journal of Transport Information and Safety, 2022, 40(3): 136-145. doi: 10.3963/j.jssn.1674-4861.2022.03.014

Citation:

HU Xiaobing, ZHANG Xuemei, ZHOU Hang, MA Yiming. A Method for Improved Air Luggage Check-in Service Based on Optimized Urban Mobile Stations[J]. Journal of Transport Information and Safety, 2022, 40(3): 136-145. doi: 10.3963/j.jssn.1674-4861.2022.03.014

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A Method for Improved Air Luggage Check-in Service Based on Optimized Urban Mobile Stations

doi: 10.3963/j.jssn.1674-4861.2022.03.014

HU Xiaobing^{1, 2
,},
ZHANG Xuemei^{1, 2},
ZHOU Hang^{1, 3
,
,},
MA Yiming^{1, 3}

1.
Laboratory of Complex System Safety and Intelligent Decisions, Civil Aviation University of China, Tianjin 300300, China
2.
College of Safety Science and Engineering, Civil Aviation University of China, Tianjin 300300, China
3.
College of Electronic Information and Automation, Civil Aviation University of China, Tianjin 300300, China

Received Date: 2021-10-21
Available Online: 2022-07-25

Abstract

Abstract

To enhance the quality and competitiveness of air transport service and overcome the limitations of low service coverage, high costs, and complex site selection of traditional air terminals, this paper proposes a novel method for improved air luggage check-in service based on Urban Mobile Stations (UMS). Specifically, the proposed UMS can adapt the check-in locations to the real-time passenger positions, which is formulated as a UMS dynamic siting optimization problem over the road network. The average distance and the maximal acceptable distance from passengers to UMS are considered, incorporating the constraints on the locations of service, time-varying distribution of passengers, and the service capacity of stations. Then, a hybrid optimization algorithm satisfying the requirement of real-time computation is developed, which combines the ripple spreading algorithm (RSA) and the adaptive genetic algorithm (AGA). The RSA is used to solve the many-to-many path optimization problem of passenger and UMS stations, and the AGA is employed to optimize the UMS locations. Case studies based on the road network of Tianjin City and simulated random road networks are used for the comparison between the proposed method and the traditional method. The results show that the average distances from passengers to stations are reduced by 30.9%, the number of scenarios exceeding the maximum acceptable distance is decreased by 43.7%, and the average running time of solving the UMS optimization problem is shortened by 41.2% when using the proposed method. These facts show the advantages of the proposed UMS method, meeting the real-time passengers' demands.
- intelligent transportation,
- city air terminal,
- urban mobile station,
- ripple spreading algorithm,
- adaptive genetic algorithm,
- luggage check-in service

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References

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