Modeling Park-and-Ride Services in a Multimodal Transport Network with Elastic Demand

2007 ◽  
Vol 1994 (1) ◽  
pp. 101-109 ◽  
Author(s):  
Zhi-Chun Li ◽  
William H. K. Lam ◽  
S. C. Wong ◽  
Dao-Li Zhu ◽  
Hai-Jun Huang
Keyword(s):  
Transport Network ◽  
Elastic Demand ◽  
Park And Ride ◽  
Multimodal Transport

scholarly journals Modeling an elastic-demand bimodal transport network with park-and-ride trips

2007 ◽  
Vol 12 (2) ◽  
pp. 158-166 ◽  
Author(s):  
William H. K. Lam ◽  
Zhichun Li ◽  
S. C. Wong ◽  
Daoli Zhu
Keyword(s):  
Transport Network ◽  
Elastic Demand ◽  
Park And Ride

scholarly journals Modeling a Distance-Based Preferential Fare Scheme for Park-and-Ride Services in a Multimodal Transport Network

2021 ◽  
Vol 13 (5) ◽  
pp. 2644
Author(s):  
Xinyuan Chen ◽  
Ruyang Yin ◽  
Qinhe An ◽  
Yuan Zhang
Keyword(s):  
Public Transport ◽  
Urban Areas ◽  
Choice Behavior ◽  
Programming Model ◽  
Choice Model ◽  
User Equilibrium ◽  
Transport Network ◽  
Park And Ride ◽  
Multimodal Transport ◽  
Transport Modes

This paper investigates a distance-based preferential fare scheme for park-and-ride (P&R) services in a multimodal transport network. P&R is a sustainable commuting approach in large urban areas where the service coverage rate of conventional public transport modes (e.g., train and bus) is poor/low. However, P&R services in many cities are less attractive compared to auto and other public transport modes, especially for P&R facilities sited far away from the city center. To address this issue, this paper proposes a distance-based preferential fare scheme for P&R services in which travelers who choose the P&R mode get a discount. The longer the distance they travel by train, the better the concessional price they get. A multimodal transport network equilibrium model with P&R services is developed to evaluate the impacts of the proposed distance-based fare scheme. The travelers’ mode choice behavior is modeled by the multinomial logit (MNL) discrete choice model, and their route choice behavior is depicted by the user equilibrium condition. A mathematical programming model is then built and subsequently solved by the outer approximation method. Numerical simulations demonstrate that the proposed distance-based preferential fare scheme can effectively motivate travelers to use a P&R service and significantly enhance the transport network’s performance.

scholarly journals Modelling Rail-Based Park and Ride with Environmental Constraints in a Multimodal Transport Network

2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Xinyuan Chen ◽  
Inhi Kim
Keyword(s):  
Public Transport ◽  
Transport Network ◽  
Transport Systems ◽  
Environmental Constraints ◽  
Complementarity Conditions ◽  
Modal Split ◽  
Nonlinear Complementarity ◽  
Park And Ride ◽  
Continuity Properties ◽  
Multimodal Transport

Environmental sustainability is a significant aspect in the sustainable development of modern urban cities, especially in the road transport system. As traffic demands increase, public transport requires more promotion to accommodate the increasing travel demands while maintaining the environmental quality. Public transport, however, is less attractive in vast suburb areas mainly due to its longer travel distance and waiting time. Therefore, this paper proposes a rail-based Park-and-Ride (RPR) scheme to promote public transport in the multimodal transport network. To remedy the heterogeneous distribution of vehicle pollutants in the network, regulations in environmental sensitive districts are required and studied in this paper. To quantitatively evaluate and analyse this joint RPR and environmental regulation strategy in multimodal transport systems, this paper develops an environmental constrained combined modal split and traffic assignment (EC-CMSTA) model. The proposed formulation adopts the concept of fix-point to reformulate the nonlinear complementarity conditions associated with the combined modal split and user equilibrium conditions, which is subsequently incorporated into a VI formulated nonlinear complementarity conditions associated with environmental constraints. The proposed VI formulation can handle a general constraint structure, which enhances the modelling adaptability and flexibility. The strictly monotone and Lipschitz continuity properties of this model are rigorously proved, giving rise to efficient algorithms for the model. A customized projection based self-adaptive gradient projection (SAGP) algorithm is then developed. Numerical studies demonstrate that the EC-MSTA model could enhance the behavioural modelling of network users’ travel decisions and assist in quantitatively evaluating the effectiveness of RPR schemes and environmental regulations.

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