TY - JOUR
T1 - Multimodal Urban Transportation Network Capacity Model Considering Intermodal Transportation
AU - Zhou, Jiankun
AU - Du, Muqing
AU - Chen, Anthony
N1 - Funding Information:
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research is supported by the Natural Science Foundation of China (No. 71801079), the Fundamental Research Funds for the Central Universities (No. B200202079), the Research Grants Council of the Hong Kong Special Administrative Region (No. 15212217), and the Research Institute for Sustainable Urban Development at the Hong Kong Polytechnic University (1-BBWF).
Publisher Copyright:
© National Academy of Sciences: Transportation Research Board 2022.
PY - 2022/9
Y1 - 2022/9
N2 - Transportation network capacity is an important indicator from measuring the performance of a transportation system. Previous studies on the capacity of multimodal networks have not considered transfers between different transportation modes. In fact, because of the diversified development of the urban transportation system, travelers are no longer limited to a single transportation mode in daily travel. This paper thus proposes an improved network capacity model considering intermodal transportation in urban multimodal transportation systems. The proposed network capacity model is formulated as a bi-level programming problem, in which the lower-level model is a combined modal split and traffic assignment (CMSTA) model. The CMSTA model consists of a cross-nested logit (CNL) in the phase of mode split to account for intermodal transportation and a path-size logit (PSL) in the phase of traffic assignment to account for route overlapping. Also, we consider the flow interaction of different modes (e.g., car and bus) when they share the same links. The Barzilai–Borwein step size method is used to efficiently solve the lower-level CMSTA model (i.e., the CNL-PSL model) of which the objective function is complicated. The numerical results demonstrate the advantages and features of the proposed model. The model is also applied to a real network case to assess the network capacity of the multimodal transportation system.
AB - Transportation network capacity is an important indicator from measuring the performance of a transportation system. Previous studies on the capacity of multimodal networks have not considered transfers between different transportation modes. In fact, because of the diversified development of the urban transportation system, travelers are no longer limited to a single transportation mode in daily travel. This paper thus proposes an improved network capacity model considering intermodal transportation in urban multimodal transportation systems. The proposed network capacity model is formulated as a bi-level programming problem, in which the lower-level model is a combined modal split and traffic assignment (CMSTA) model. The CMSTA model consists of a cross-nested logit (CNL) in the phase of mode split to account for intermodal transportation and a path-size logit (PSL) in the phase of traffic assignment to account for route overlapping. Also, we consider the flow interaction of different modes (e.g., car and bus) when they share the same links. The Barzilai–Borwein step size method is used to efficiently solve the lower-level CMSTA model (i.e., the CNL-PSL model) of which the objective function is complicated. The numerical results demonstrate the advantages and features of the proposed model. The model is also applied to a real network case to assess the network capacity of the multimodal transportation system.
KW - equilibrium
KW - mathematical modeling
KW - network assignment
KW - networks
KW - planning and analysis
KW - transportation network modeling
UR - http://www.scopus.com/inward/record.url?scp=85132871981&partnerID=8YFLogxK
U2 - 10.1177/03611981221086931
DO - 10.1177/03611981221086931
M3 - Journal article
AN - SCOPUS:85132871981
SN - 0361-1981
VL - 2676
SP - 357
EP - 373
JO - Transportation Research Record
JF - Transportation Research Record
IS - 9
ER -