TY - GEN
T1 - Transport modeling with a purpose
T2 - 25th International Conference on Urban Transport and the Environment, Urban Transport 2019
AU - Binder, Robert B.
AU - Lancaster, Zachary
AU - Tobey, Michael
AU - Jittrapirom, Peraphan
AU - Yamagata, Yoshiki
N1 - Publisher Copyright:
© 2019 WIT Press.
PY - 2019
Y1 - 2019
N2 - A new age of mobility is upon us, and the way we analyze our transportation network and future development projects must move into this new age. Large-scale changes to our transportation system are coming with the introduction of disruptive technologies and services like autonomous vehicles, electric vertical take-off and landing (eVTOL) air taxis, and Mobility-as-a-Service (MaaS) platforms. Transportation modeling has long been used as a tool to measure the impact, positively or negatively, of a proposed network change or new land development. Transportation modeling has become more complex as it has shifted from the traditional four-step model, but it is still used in new development traffic impact studies, activity-based models, and most recently, agent-based models like those of MATSim. This increased complexity has made way for more comprehensive measures of effectiveness that can be useful in planning and design. However, there tends to be a gap between design occurring, tool utilization, and actual implementation of new technologies and big data effectively into these proven modeling and simulation platforms. Among five specific issues in travel forecasting, modeling is used as a reactive tool instead of a proactive tool with the purpose of influencing design and planning. Urban Systems Design has the potential to fill these gaps in methodology, which are occurring together in the modeling, planning, and design professions. An example of these new methodologies is presented using the city of Urawa Misono in metropolitan Tokyo, Japan, as a case study. As technology becomes more enhanced, so shall our methodologies, as we attempt to enact system changes in a more complex way. The feedback loop of analysis and design within Urban Systems Design methodologies could produce greater outcomes for the transportation network, for new development, and increase both the mobility and accessibility for the users of our urban networks.
AB - A new age of mobility is upon us, and the way we analyze our transportation network and future development projects must move into this new age. Large-scale changes to our transportation system are coming with the introduction of disruptive technologies and services like autonomous vehicles, electric vertical take-off and landing (eVTOL) air taxis, and Mobility-as-a-Service (MaaS) platforms. Transportation modeling has long been used as a tool to measure the impact, positively or negatively, of a proposed network change or new land development. Transportation modeling has become more complex as it has shifted from the traditional four-step model, but it is still used in new development traffic impact studies, activity-based models, and most recently, agent-based models like those of MATSim. This increased complexity has made way for more comprehensive measures of effectiveness that can be useful in planning and design. However, there tends to be a gap between design occurring, tool utilization, and actual implementation of new technologies and big data effectively into these proven modeling and simulation platforms. Among five specific issues in travel forecasting, modeling is used as a reactive tool instead of a proactive tool with the purpose of influencing design and planning. Urban Systems Design has the potential to fill these gaps in methodology, which are occurring together in the modeling, planning, and design professions. An example of these new methodologies is presented using the city of Urawa Misono in metropolitan Tokyo, Japan, as a case study. As technology becomes more enhanced, so shall our methodologies, as we attempt to enact system changes in a more complex way. The feedback loop of analysis and design within Urban Systems Design methodologies could produce greater outcomes for the transportation network, for new development, and increase both the mobility and accessibility for the users of our urban networks.
KW - Big data
KW - Design
KW - MATSim
KW - Planning support system
KW - Smart city
KW - Tokyo
KW - Traffic impact analysis
KW - Transportation modeling
KW - Travel demand modeling
KW - Urban systems design
UR - http://www.scopus.com/inward/record.url?scp=85077328760&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85077328760&partnerID=8YFLogxK
U2 - 10.2495/UT190081
DO - 10.2495/UT190081
M3 - Conference contribution
AN - SCOPUS:85077328760
T3 - WIT Transactions on the Built Environment
SP - 85
EP - 96
BT - Urban Transport XXV
A2 - Passerini, G.
A2 - Borrego, Carlos
PB - WITPress
Y2 - 25 June 2019 through 27 June 2019
ER -
