Agent-Based Simulation to Improve Policy Sensitivity of Trip-Based Models
Joint Authors
Moreno, Ana T.
Moeckel, Rolf
Kuehnel, Nico
Llorca, Carlos
Rayaprolu, Hema
Source
Journal of Advanced Transportation
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-02-25
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
The most common travel demand model type is the trip-based model, despite major shortcomings due to its aggregate nature.
Activity-based models overcome many of the limitations of the trip-based model, but implementing and calibrating an activity-based model is labor-intensive and running an activity-based model often takes long runtimes.
This paper proposes a hybrid called MITO (Microsimulation Transport Orchestrator) that overcomes some of the limitations of trip-based models, yet is easier to implement than an activity-based model.
MITO uses microsimulation to simulate each household and person individually.
After trip generation, the travel time budget in minutes is calculated for every household.
This budget influences destination choice; i.e., people who spent a lot of time commuting are less likely to do much other travel, while people who telecommute might compensate by additional discretionary travel.
Mode choice uses a nested logit model, and time-of-day choice schedules trips in 1-minute intervals.
Three case studies demonstrate how individuals may be traced through the entire model system from trip generation to the assignment.
American Psychological Association (APA)
Moeckel, Rolf& Kuehnel, Nico& Llorca, Carlos& Moreno, Ana T.& Rayaprolu, Hema. 2020. Agent-Based Simulation to Improve Policy Sensitivity of Trip-Based Models. Journal of Advanced Transportation،Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1175384
Modern Language Association (MLA)
Moeckel, Rolf…[et al.]. Agent-Based Simulation to Improve Policy Sensitivity of Trip-Based Models. Journal of Advanced Transportation No. 2020 (2020), pp.1-13.
https://search.emarefa.net/detail/BIM-1175384
American Medical Association (AMA)
Moeckel, Rolf& Kuehnel, Nico& Llorca, Carlos& Moreno, Ana T.& Rayaprolu, Hema. Agent-Based Simulation to Improve Policy Sensitivity of Trip-Based Models. Journal of Advanced Transportation. 2020. Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1175384
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1175384