Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/73759
Title: | Spatial agent-based model for environmental assessment of passenger transportation | Authors: | Lu, M Hsu, SC |
Issue Date: | Dec-2017 | Source: | Journal of urban planning and development, Dec. 2017, v. 143, no. 4, 04017016, p. 2 | Abstract: | This study presents an urban transportation simulation model for lifecycle environmental performance evaluation (ALENT). ALENT integrates geographic information to quantify stations' accessibility levels and construct real-world intercity transportation maps. A conceptual meta-theory from psychology is adopted to form the behavioral rules of passengers choosing different transport modes as influenced in part by passengers' social networks. Operation scenarios are simulated for the year in which Hong Kong's high-speed railway (HSR) is introduced, viewed from a lifecycle assessment perspective. The simulation results suggest that the occupancy rate of the HSR should be maintained-more than 80%-to lower the overall environmental impacts. The through train may need to be shut down to mitigate the system environmental impacts by up to 30%. ALENT can be used as a decision support tool for establishing sustainable passenger transportation systems. | Keywords: | Agent-based modeling (ABM) High-speed railway (HSR) Lifecycle environmental analysis Logit model |
Publisher: | American Society of Civil Engineers | Journal: | Journal of urban planning and development | ISSN: | 0733-9488 | EISSN: | 1943-5444 | DOI: | 10.1061/(ASCE)UP.1943-5444.0000403 | Rights: | © 2017 American Society of Civil Engineers. This material may be downloaded for personal use only. Any other use requires prior permission of the American Society of Civil Engineers. This material may be found at https://ascelibrary.org/doi/10.1061/%28ASCE%29UP.1943-5444.0000403. |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Hsu_A_Spatial_Agent-based.pdf | Pre-Published version | 1.08 MB | Adobe PDF | View/Open |
Page views
108
Last Week
0
0
Last month
Citations as of Apr 21, 2024
Downloads
75
Citations as of Apr 21, 2024
SCOPUSTM
Citations
9
Last Week
0
0
Last month
Citations as of Apr 19, 2024
WEB OF SCIENCETM
Citations
9
Last Week
0
0
Last month
Citations as of Apr 18, 2024
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.