scholarly journals A Practical Traffic Assignment Model for Multimodal Transport System Considering Low-Mobility Groups

Mathematics ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 351 ◽  
Author(s):  
Tao Zhang ◽  
Yang Yang ◽  
Gang Cheng ◽  
Minjie Jin
Keyword(s):  
Transport System ◽  
Traffic Assignment ◽  
Transportation Network ◽  
Travel Costs ◽  
Assignment Model ◽  
Proposed Model ◽  
Multimodal Transport ◽  
Logit Function ◽  
Private Car

In this study, we created a practical traffic assignment model for a multimodal transport system considering low-mobility groups with the aim of providing the foundation of transportation network design for low-mobility individuals. First, the route choice equilibrium for walking, non-vehicle, and private car modes is described using the logit function, which is formulated as a variational inequality problem considering different low-mobility groups. Then, the practicalities related to travel times at intersections, traffic barricades between different lanes, and fuel fees of private cars are integrated to design a generalized travel cost function. Last, the method of successive weight averages is used to solve the proposed model. The model and its solution are verified based on a real case study of the city of Wenling in China. The sensitivity of adjustment parameters related to travel costs are analyzed, the practicality of the proposed model is explored, and the results of traffic assignment for different low-mobility groups are discussed.

scholarly journals A simulation-based dynamic traffic assignment model with combined modes

2014 ◽  
Vol 26 (1) ◽  
pp. 65-73 ◽  
Author(s):  
Meng Meng ◽  
Chunfu Shao ◽  
Jingjing Zeng ◽  
Chunjiao Dong
Keyword(s):  
Simulation Model ◽  
Traffic Assignment ◽  
Dynamic Traffic Assignment ◽  
Transportation Network ◽  
Time Dependent ◽  
Dynamic Traffic ◽  
Mesoscopic Simulation ◽  
Assignment Model ◽  
Management Measures ◽  
Private Car

This paper presents a dynamic traffic assignment (DTA) model for urban multi-modal transportation network by con­structing a mesoscopic simulation model. Several traffic means such as private car, subway, bus and bicycle are con­sidered in the network. The mesoscopic simulator consists of a mesoscopic supply simulator based on MesoTS model and a time-dependent demand simulator. The mode choice is si­multaneously considered with the route choice based on the improved C-Logit model. The traffic assignment procedure is implemented by a time-dependent shortest path (TDSP) al­gorithm in which travellers choose their modes and routes based on a range of choice criteria. The model is particularly suited for appraising a variety of transportation management measures, especially for the application of Intelligent Trans­port Systems (ITS). Five example cases including OD demand level, bus frequency, parking fee, information supply and car ownership rate are designed to test the proposed simulation model through a medium-scale case study in Beijing Chaoy­ang District in China. Computational results illustrate excel­lent performance and the application of the model to analy­sis of urban multi-modal transportation networks.

scholarly journals Multimodal Capacitated Hub Location Problems with Multi-Commodities: An Application in Freight Transport

2020 ◽  
Vol 2020 ◽  
pp. 1-9 ◽  
Author(s):  
Alan Osorio-Mora ◽  
Francisco Núñez-Cerda ◽  
Gustavo Gatica ◽  
Rodrigo Linfati
Keyword(s):  
Latin American ◽  
Location Problems ◽  
Transport Cost ◽  
Mixed Integer ◽  
Hub Location ◽  
Proposed Model ◽  
Multimodal Transport ◽  
Two Factors ◽  
Commercial Solver

Hub location problems (HLPs) support decision making on multimodal transport strategic planning. It is related to the location of hubs and the allocation of origin/destination (O/D) flow in a system. Classical formulations assume that these flows are predefined paths and direct delivery is not available. This applied research presents a mixed integer linear programming (MILP) model for a capacitated multimodal, multi-commodity HLP. Furthermore, an application on the export process in a Latin American country is detailed. The new proposed model, unlike the traditional HLP, allows direct shipment, and its O/D flows are part of the decision model. Situations with up to 100 nodes, six products, and two transport modes are used, working with initial and projected flows. All instances can be solved optimally using the commercial solver, Gurobi 7.5.0, in computational times less than a minute. Results indicate that only one hub is profitable for the case study, both for the initial and projected scenarios. The installation of a hub generates transport savings over 1% per year. Two factors affect the location decision: low concentration and distance between the hubs and destinations. Long distances involve an exhaustive use of trains instead of trucks, which leads to lower transport cost per unit.

Scenario-Based Integrated Assignment Model for Bi-Class User Rail Transit Networks

2013 ◽  
Vol 361-363 ◽  
pp. 1963-1966
Author(s):  
Wei Zhu
Keyword(s):  
Urban Rail Transit ◽  
Rail Transit ◽  
Transit Networks ◽  
Assignment Model ◽  
Urban Rail ◽  
Proposed Model ◽  
Scale Network ◽  
Algorithm Framework ◽  
Real Scale

An integrated assignment model for urban rail transit (URT) networks was proposed and discussed in four typical scenarios with the consideration of passenger difference between native and non-native. An overall algorithm framework for the model was also developed, which introduced three critical route choice models and combined them appropriately to different scenarios. A case study was performed on a real-scale network of Shanghai during the Expo 2010. The results revealed that the proposed model can deliver more appropriate solution to the assignment problem compared to the existing practice in the real world.

scholarly journals A Bicycle Origin–Destination Matrix Estimation Based on a Two-Stage Procedure

2020 ◽  
Vol 12 (7) ◽  
pp. 2951
Author(s):  
Seungkyu Ryu
Keyword(s):  
Gravity Model ◽  
Transportation Network ◽  
Modal Shift ◽  
Two Stage ◽  
Matrix Estimation ◽  
Second Stage ◽  
Local Mobility ◽  
Proposed Model ◽  
Path Flow Estimator

As more people choose to travel by bicycle, transportation planners are beginning to recognize the need to rethink the way they evaluate and plan transportation facilities to meet local mobility needs. A modal shift towards bicycles motivates a change in transportation planning to accommodate more bicycles. However, the current methods to estimate bicycle volumes on a transportation network are limited. The purpose of this research is to address those limitations through the development of a two-stage bicycle origin–destination (O–D) matrix estimation process that would provide a different perspective on bicycle modeling. From the first stage, a primary O–D matrix is produced by a gravity model, and the second stage refines that primary matrix generated in the first stage using a Path Flow Estimator (PFE) to build the finalized O–D demand. After a detailed description of the methodology, the paper demonstrates the capability of the proposed model for a bicycle demand matrix estimation tool with a real network case study.

scholarly journals Transport networks and their use: how real can modelling get?

2008 ◽  
Vol 366 (1872) ◽  
pp. 1879-1892 ◽  
Author(s):  
Richard E Allsop
Keyword(s):  
Steady State ◽  
Time Dependence ◽  
Transport System ◽  
Traffic Assignment ◽  
Analytical Modelling ◽  
Transport Systems ◽  
Transport Networks ◽  
Variable Demand ◽  
Assignment Model

The context for modelling transport systems and their use is set out. Such modelling is based on representing the transport system by a network of nodes and links, and the characteristics of this representation needed to reflect the principal realities of the system are outlined. The characteristics of use of the system that need to be reflected are described. Purposes of the modelling are set out and its evolution is described, starting from the basic traffic assignment model and discussing its generalizations and extensions in the search for greater realism—first in steady-state modelling for fixed demand, and then considering variable demand and time dependence. Further progress towards appropriate realism is seen as requiring communication and cooperation between the modellers and the users of models, helped perhaps by combining the advantages of analytical modelling and microsimulation.

Traffic assignment model for combined mode with travel condition constraints

2020 ◽  
Vol 34 (04) ◽  
pp. 2050003 ◽  
Author(s):  
Xiaohua Yu ◽  
Hua Wang ◽  
Zhenzhen Ge ◽  
Jianmin Guo
Keyword(s):  
Traffic Assignment ◽  
Transportation Network ◽  
Network Size ◽  
Route Choice Behavior ◽  
Assignment Model ◽  
Traffic Allocation ◽  
Implementation Effect ◽  
Practical Factors ◽  
Network Transformation ◽  
Combined Mode

Combined-mode traffic assignment is one of the key links for multi-modal transportation planning. In order to quantitatively evaluate the implementation effect of combined-mode transportation and explore its assignment mechanism, a combined-mode traffic assignment model with travel constraints is proposed. First, the practical factors of combined mode in real world are discussed and integrated into the analysis of multi-modal network transformation as related constraints. Second, the physical transportation network is translated to equivalent super network (SN) and state-augmented network (SAN) based on the graph theory. Moreover, the network size constrained by the actual conditions is conducive to further analysis of combined-mode trips. Third, a tri-level combined-mode traffic assignment model is formulated based on the simulation platform of SAN. The first level of the model is to address the combined-mode choice, the second level is to transfer choice on SAN, and the third level is to characterize auto travelers’ route choice behavior. By analyzing the impedance in multi-level network, an MSA algorithm solving Nest-Logit model is proposed. Finally, numerical example is performed to validate the model. The method proposed in this paper considers the travel similarity, reduces the network scale, conforms to the travel logic and makes up for the shortcomings of traditional traffic allocation methods.

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