TY - JOUR
T1 - Agent-Based Simulation to Improve Policy Sensitivity of Trip-Based Models
AU - Moeckel, Rolf
AU - Kuehnel, Nico
AU - Llorca, Carlos
AU - Moreno, Ana Tsui
AU - Rayaprolu, Hema
N1 - Publisher Copyright:
© 2020 Rolf Moeckel et al.
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85081154124&partnerID=8YFLogxK
U2 - 10.1155/2020/1902162
DO - 10.1155/2020/1902162
M3 - Article
AN - SCOPUS:85081154124
SN - 0197-6729
VL - 2020
JO - Journal of Advanced Transportation
JF - Journal of Advanced Transportation
M1 - 1902162
ER -