Traffic Assignment of Multi-Modal Transport Networks Based on An Augmented Link-Based Super-Network Model

Abstract

Multi-modal transport is getting more popular due to the emergence of new traffic
modes. The increase of modes also adds complexity for the transport researchers.
This paper proposes an augmented link-based super-network approach for modeling
multi-modal transport networks, addressing the scalability and versatility issues of
conventional methods. This approach is used to calculate the user equilibrium for
urban transport networks traffic assignment with multiple traffic modes, a difficult
problem due to the intractable enumeration of feasible paths between origindestination
pairs and restricted transfers between different traffic modes. In the supernetwork
representation of multi-modal transport networks, the travel cost of any
feasible route between the origin and destination is formulated as the sum of cost
functions of the augmented links, thus avoiding the enumeration of feasible paths.
Additionally, restrictions on traffic mode transfers can be embedded in the link-based
model by excluding infeasible transfer links or adding penalties for undesired transfers.
The user equilibrium of the augmented link-based super-network model is formulated
as a variational inequality problem, solved using the extra-gradient algorithm. A multimodal
transport network is considered in the case study. Simulation results validate the
effectiveness of the proposed model, demonstrating its scalability and versatility in
addressing complex multi-modal transport networks with diverse traffic modes.
We anticipate that our method can serve as an efficient modeling approach for more
general and complex multi-modal transport networks, facilitating traffic management
and network design.