AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
Article Link
Collect
Submit Manuscript
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Full Length Article | Open Access

A demand forecasting model for urban air mobility in Chengdu, China

State Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100101, China
Key Laboratory of Regional Sustainable Development Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Civil Aviation Flight University of China, Guanghan, 618307, China
The Research Center for UAV Applications and Regulation, CAS, Beijing 100101, China
Show Author Information

HIGHLIGHTS

· We combine the NL model and the MNL model to solve the problem that no existing UAM share rate data in 2020.

· The shared model may facilitate pro-moting UAM in urban transportation system.

· With a fully shared operation, the UAM share rate increases by 0.73% for every kilometer increase in distance.

· UAM is more competitive than other modes for delivery distances exceeding 15 km.

Abstract

The successful application of new technologies such as remotely piloted aircraft systems, distributed electric propulsion systems, and automatic control systems on electric vertical take-off and landing(eVTOL) aircraft has prompted Urban Air Mobility (UAM) to be mentioned frequently. UAM is a newly raised transport mode of using eVTOL aircraft to transport people and cargo in urban areas, which is thought to share some of the traffic on the ground. One of the prerequisites for UAM to operate on a regular basis is that its demand can support the operating costs, so forecasting UAM demand is necessary. We conduct UAM demand forecasting based on the four-step method, focusing on improving the third-step modal split, and propose a demand forecasting model based on the logit model. The model combines a nested logit (NL) model with a multinomial logit (MNL) model to solve the problem of non-existent UAM sharing rates. We use Chengdu, China as an example, and focus on forecasting the UAM traffic demand in 2030 with the help of the four-step method. The results show that UAM is suitable for shared operation during the early stages. With a fully shared operation, the UAM share rate increases by 0.73% for every kilometer increase in distance. Moreover, UAM is more competitive than other modes for delivery distances exceeding 15 ​km. Finally, using the distributions of the share rate and traffic flow pattern from the simulation, we propose the routes that can be prioritized for UAM operations in Chengdu.

Graphical Abstract

References

【1】
【1】
 
 
Green Energy and Intelligent Transportation

{{item.num}}

Comments on this article

Go to comment

< Back to all reports

Review Status: {{reviewData.commendedNum}} Commended , {{reviewData.revisionRequiredNum}} Revision Required , {{reviewData.notCommendedNum}} Not Commended Under Peer Review

Review Comment

Close
Close
Cite this article:
Qu W, Huang J, Li C, et al. A demand forecasting model for urban air mobility in Chengdu, China. Green Energy and Intelligent Transportation, 2024, 3(3). https://doi.org/10.1016/j.geits.2024.100173

1126

Views

20

Crossref

23

Web of Science

24

Scopus

Received: 27 August 2023
Revised: 07 October 2023
Accepted: 08 January 2024
Published: 13 January 2024
© 2024 The Authors.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).