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Abstract

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.

Keywords

planning and analysis transportation network modeling equilibrium mathematical modeling network assignment networks

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References

Yang

Bell

M. G. H.

A Capacity Paradox in Network Design and How to Avoid It. Transportation Research Part A: Policy and Practice, Vol. 32A, No. 7, 1998, pp. 539–545. https://doi.org/10.1016/S0965-8564(98)00017-2.

Chen

Jansuwan

Yang

Ryu

Transportation Network Redundancy: Complementary Measures and Computational Methods. Transportation Research Part B: Methodological, Vol. 114, 2018, pp. 68–85. https://doi.org/10.1016/j.trb.2018.05.014.

Chen

Yang

H. K.

Tang

W. H.

A Capacity Related Reliability for Transportation Networks. Journal of Advanced Transportation, Vol. 33, No. 2, 1999, pp. 183–200. https://doi.org/10.1002/atr.5670330207.

Ceylan

Bell

M. G. H.

Reserve Capacity for a Road Network under Optimized Fixed Time Traffic Signal Control. Journal of Intelligent Transportation Systems: Technology, Planning, and Operations, Vol. 8, No. 2, 2004, pp. 87–99. https://doi.org/10.1080/15472450490437780.

Ford

L. R.

Fulkerson

D. R.

Flows in Networks. Princeton University Press, NJ, 1962.

Asakura

Maximum Capacity of Road Network Constrained by User Equilibrium Conditions. Proc., 24th Annual Conference of the UTSG, Newcastle, 1992.

Wong

S. C.

Yang

Reserve Capacity of a Signal-Controlled Road Network. Transportation Research Part B: Methodological, Vol. 31, No. 5, 1997, pp. 397–402. https://doi.org/10.1016/S0191-2615(97)00002-7.

Gao

Z. Y.

Song

Y. F.

A Reserve Capacity Model of Optimal Signal Control with User-Equilibrium Route Choice. Transportation Research Part B: Methodological, Vol. 36, No. 4, 2002, pp. 313–323.

Kasikitwiwat

Chen

Analysis of Transportation Network Capacity Related to Different System Capacity Concepts. Journal of the Eastern Asia Society of Transportation Studies, Vol. 6, 2005, pp. 1439–1454.

10.

Yang

Bell

M. G. H.

Meng

Modeling the Capacity and Level of Service of Urban Transportation Networks. Transportation Research Part B: Methodological, Vol. 34, No. 4, 2000, pp. 255–275. https://doi.org/10.1016/S0191-2615(99)00024-7.

11.

Chen

Yang

H. K.

Tang

W. H.

Capacity Reliability of a Road Network: An Assessment Methodology and Numerical Results. Transportation Research Part B: Methodological, Vol. 36, No. 3, 2002, pp. 225–252. https://doi.org/10.1016/S0191-2615(00)00048-5.

12.

Chiou

S. -W.

Reserve Capacity of Signal-Controlled Road Network. Applied Mathematics and Computation, Vol. 190, No. 2, 2007, pp. 1602–1611. https://doi.org/10.1016/j.amc.2007.02.041.

13.

Cheng

Jiang

Rakha

Modeling and Estimating the Capacity of Urban Transportation Network With Rapid Transit. Transport, Vol. 29, No. 2, 2014, pp. 165–174. https://doi.org/10.3846/16484142.2014.930069.

14.

Wang

Maximizing Network Throughput Under Stochastic User Equilibrium With Elastic Demand. Networks and Spatial Economics, Vol. 18, No. 1, 2018, pp. 115–143. https://doi.org/10.1007/s11067-017-9372-z.

15.

Florian

Nguyen

A Combined Trip Distribution Modal Split and Trip Assignment Model. Transportation Research, Vol. 12, No. 4, 1978, pp. 241–246.

16.

Sheffi

Powell

W. B.

An Algorithm for The Equilibrium Assignment Problem with Random Link Times. Networks, Vol. 12, No. 2, 1982, pp. 191–207.

17.

Maher

SAM—A Stochastic Assignment Model. In Mathematics in Transport Planning and Control ( Griffiths

J. D.

, ed.), Oxford University Press, Oxford, 1992.

18.

Rosa

Maher

M. J.

Algorithms for Solving the Probit Path-based Stochastic User Equilibrium Traffic Assignment Problem with One or More User Classes. Proc., 15th International Symposium on Transportation and Traffic Theory, Australia, 2002, pp. 371–392.

19.

Kitthamkesorn

Chen

Ryu

Modeling Mode and Route Similarities in Network Equilibrium Problem with Go-Green Modes. Networks and Spatial Economics, Vol. 16, No. 1, 2016, pp. 33–60. https://doi.org/10.1007/s11067-013-9201-y.

20.

Liu

Chen

Meng

Kim

Remote Park-and-Ride Network Equilibrium Model and its Applications. Transportation Research Part B: Methodological, Vol. 117, 2018, pp. 37–62. https://doi.org/10.1016/j.trb.2018.08.004.

21.

Daganzo

C. F.

Sheffi

On Stochastic Models of Traffic Assignment. Transportation Science, Vol. 11, 1977, pp. 253–274.

22.

Fisk

Some Developments in Equilibrium Traffic Assignment. Transportation Research Part B: Methodological, Vol. 14, No. 3, 1980, pp. 243–255.

23.

Prashker

J. N.

Bekhor

Investigation of Stochastic Network Loading Procedures. Transportation Research Record: Journal of Transportation Research Board, 1998. 1645: 94–102.

24.

Tan

Chen

A Faster Path-Based Algorithm with Barzilai-Borwein Step Size for Solving Stochastic Traffic Equilibrium Models. European Journal of Operational Research, Vol. 290, No. 3, 2021, pp. 982–999. https://doi.org/10.1016/j.ejor.2020.08.058.

25.

Friesz

T. L.

Tobin

R. L.

Cho

H. J.

Mehta

N. J.

Sensitivity Analysis Based Heuristic Algorithms for Mathematical Programs With Variational Inequality Constraints. Mathematical Programming, Vol. 48, No. 2, pp. 265–284.

26.

Jiang

Cheng

Estimating the Capacity of Urban Transportation Networks With an Improved Sensitivity Based Method. Discrete Dynamics in Nature and Society, Vol. 2015, 2015. https://doi.org/10.1155/2015/827094.

27.

Tam

M. L.

Lam

W. H. K.

Maximum Car Ownership under Constraints of Road Capacity and Parking Space. Transportation Research Part A: Policy and Practice, Vol. 34, No. 3, 2000, pp. 145–170. https://doi.org/10.1016/S0965-8564(98)00070-6.

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Multimodal Urban Transportation Network Capacity Model Considering Intermodal Transportation

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