scholarly journals Robust Evaluation for Transportation Network Capacity under Demand Uncertainty

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Muqing Du ◽  
Xiaowei Jiang ◽  
Lin Cheng ◽  
Changjiang Zheng
Keyword(s):  
Demand Uncertainty ◽  
Travel Demand ◽  
Transportation Networks ◽  
Transportation Network ◽  
Network Capacity ◽  
Traffic Jam ◽  
Reserve Network ◽  
Bounded Set ◽  
Robust Model ◽  
And Performance

As more and more cities in worldwide are facing the problems of traffic jam, governments have been concerned about how to design transportation networks with adequate capacity to accommodate travel demands. To evaluate the capacity of a transportation system, the prescribed origin and destination (O-D) matrix for existing travel demand has been noticed to have a significant effect on the results of network capacity models. However, the exact data of the existing O-D demand are usually hard to be obtained in practice. Considering the fluctuation of the real travel demand in transportation networks, the existing travel demand is represented as uncertain parameters which are defined within a bounded set. Thus, a robust reserve network capacity (RRNC) model using min–max optimization is formulated based on the demand uncertainty. An effective heuristic approach utilizing cutting plane method and sensitivity analysis is proposed for the solution of the RRNC problem. Computational experiments and simulations are implemented to demonstrate the validity and performance of the proposed robust model. According to simulation experiments, it is showed that the link flow pattern from the robust solutions to network capacity problems can reveal the probability of high congestion for each link.

Robust Pricing of Transportation Networks under Uncertain Demand

2008 ◽  
Vol 2085 (1) ◽  
pp. 21-30 ◽  
Author(s):  
Lauren M. Gardner ◽  
Avinash Unnikrishnan ◽  
S. Travis Waller
Keyword(s):  
Demand Uncertainty ◽  
Travel Demand ◽  
Transportation Networks ◽  
Random Variable ◽  
User Equilibrium ◽  
Uncertain Demand ◽  
Optimal Pricing ◽  
Elastic Demand ◽  
Marginal Costs ◽  
Pricing Scheme

Traditionally, tolls on transportation networks are determined on the basis of a single value of travel demand, deterministic elastic demand relationships, or informal scenario analysis. However, since the demand on the network cannot be forecast perfectly, pricing may prove to be suboptimal when the realized value of demand deviates significantly from the planned value. Therefore, there is a need for a robust pricing scheme that accounts for demand uncertainty. Optimal pricing is examined through marginal costs in which origin-destination travel demand is a random variable to understand better the direct impact and sensitivity of the uncertainty. Three methods are evaluated for determining robust prices: inflation or deflation of the planning demand, averaging tolls from various planning demands, and genetic algorithms. The performance of these three methods is evaluated by analyzing user equilibrium for various future travel demand scenarios. From the results of the analysis, a more robust pricing scheme that accounts for variations in demand is developed.

scholarly journals Megaregional Passenger Transportation Hub Location Problem Considering Congestion Effects

2021 ◽  
Vol 33 (4) ◽  
pp. 551-563
Author(s):  
Huang Yan ◽  
Xiaoning Zhang
Keyword(s):  
Location Problem ◽  
Travel Demand ◽  
Programming Model ◽  
Transportation Network ◽  
Network Capacity ◽  
Mixed Integer ◽  
Hub Location ◽  
Hub Location Problem ◽  
Passenger Transportation ◽  
Congestion Effects

The need to make effective plans for locating transportation hubs is of increasing importance in the megaregional area, as recent research suggests that the growing intercity travel demand affects the efficiency of a megaregional transportation system. This paper investigates a hierarchical facility location problem in a megaregional passenger transportation network. The aim of the study is to determine the locations of hub facilities at different hierarchical levels and distribute the demands to these facilities with minimum total cost, including investment, transportation, and congestion costs. The problem is formulated as a mixed-integer nonlinear programming model considering the service availability structure and hub congestion effects. A case study is designed to demonstrate the effectiveness of the proposed model in the Wuhan metropolitan area. The results show that the congestion effects can be addressed by reallocating the demand to balance the hub utilisation or constructing new hubs to increase the network capacity. The methods of appropriately locating hubs and distributing traffic flows are proposed to optimise the megaregional passenger transportation networks, which has important implications for decision makers.

Definition and Evaluation Modeling of Transportation Network Layout Adaptability

2011 ◽  
Vol 71-78 ◽  
pp. 3938-3941 ◽  
Author(s):  
Jie Gao ◽  
Mei Xiang Wu ◽  
Chen Qiang Yin
Keyword(s):  
Heuristic Algorithm ◽  
Coefficient Of Variation ◽  
Large Scale ◽  
Transportation Networks ◽  
Transportation Network ◽  
Optimization Methods ◽  
Network Capacity ◽  
Network Layout ◽  
Proposed Model ◽  
Coordination Degree

According to the reliability theories and the characteristics of transportation networks, the layout adaptability is defined as the coupling and coordination degree of transportation network capacity and demand firstly. Then a layout adaptability model is built adopting the optimization methods, degree of layout adaptability index and coefficient of variation are used to evaluate the adaptability of scale and distribution respectively. Meanwhile, the heuristic algorithm suitable for large scale is designed to solve the proposed model. At last, a numerical example and its results are provided to demonstrate the validity of the proposed model and algorithm.

scholarly journals MODELING AND ESTIMATING THE CAPACITY OF URBAN TRANSPORTATION NETWORK WITH RAPID TRANSIT

Transport ◽  
2014 ◽  
Vol 29 (2) ◽  
pp. 165-174 ◽  
Author(s):  
Lin Cheng ◽  
Muqing Du ◽  
Xiaowei Jiang ◽  
Hesham Rakha
Keyword(s):  
Travel Behavior ◽  
Travel Demand ◽  
Transportation Network ◽  
Urban Transportation ◽  
Network Capacity ◽  
Rapid Transit ◽  
Demand Model ◽  
Trip Distribution ◽  
Capacity Model ◽  
The Impact

To study the impact of the rapid transit on the capacity of current urban transportation system, a two-mode network capacity model, including the travel modes of automobile and transit, is developed based on the well-known road network capacity model. It considers that the travel demand accompanying with the regional development will increase in a variable manner on the trip distribution, of which the travel behavior is represented using the combined model split/trip distribution/traffic assignment model. Additionally, the choices of the travel routes, trip destinations and travel modes are formulated as a hierarchical logit model. Using this combined travel demand model in the lower level, the network capacity problem is formulated as a bi-level programming problem. The latest technique of sensitivity analysis is employed for the solution of the bi-level problem in a heuristic search. Numerical computations are demonstrated on an example network, and the before-and-after comparisons of building the new transit lines on the integrated transportation network are shown by the results.

scholarly journals Exploring the Topological Characteristics of Complex Public Transportation Networks: Focus on Variations in Both Single and Integrated Systems in the Seoul Metropolitan Area

2019 ◽  
Vol 11 (19) ◽  
pp. 5404 ◽  
Author(s):  
Jungyeol Hong ◽  
Reuben Tamakloe ◽  
Soobeom Lee ◽  
Dongjoo Park
Keyword(s):  
Public Transportation ◽  
Spatial Configuration ◽  
Transportation Networks ◽  
Transportation Network ◽  
Spatial Accessibility ◽  
Structural Defects ◽  
Centrality Measures ◽  
Integrated Networks ◽  
Public Transportation Network ◽  
And Performance

Many cities have integrated their public transportation modes to provide increased accessibility and reduced commute times. However, current transport network topology studies have focused on unimodal networks. Therefore, it is of significant interest for policymakers to examine the topology of integrated public transportation networks and to assess strategies for improving them. The objective of this study was to discuss a comprehensive analysis of an integrated public transportation network using graph theory, compare its characteristics to unimodal networks, and draw insights for improving their performance. Results demonstrate pertinent information concerning the structural composition of the Seoul Metropolitan Area’s (SMA) public transportation network. Despite the integration, the spatial configuration of the network was found to have low fault tolerance. However, the highly agglomerated community structure validated the robustness of integrated networks. Network centrality measures confirmed that integration improves connectivity and spatial accessibility to suburbs within the city. The study found that the SMA’s current public transportation network possesses structural defects that need to be addressed to improve its resilience and performance. Based on the outcomes of this study, the strategic creation or relocation of stations, and the construction of more links, is imperative for the enhancement of mobility.

Best Neighbor Heuristic Search for Finding Minimum Paths in Transportation Networks

1998 ◽  
Vol 1651 (1) ◽  
pp. 48-52 ◽  
Author(s):  
Jeffrey L. Adler
Keyword(s):  
Heuristic Search ◽  
Transportation Networks ◽  
Transportation Network ◽  
Search Problems ◽  
A Algorithm ◽  
Running Time ◽  
Search Effort ◽  
Wide Range ◽  
Path Search ◽  
Sparse Networks

For a wide range of transportation network path search problems, the A* heuristic significantly reduces both search effort and running time when compared to basic label-setting algorithms. The motivation for this research was to determine if additional savings could be attained by further experimenting with refinements to the A* approach. We propose a best neighbor heuristic improvement to the A* algorithm that yields additional benefits by significantly reducing the search effort on sparse networks. The level of reduction in running time improves as the average outdegree of the network decreases and the number of paths sought increases.

Network dynamics on the Chinese air transportation multilayer network

2021 ◽  
pp. 2150070
Author(s):  
Yong Yang ◽  
Kai-Jun Xu ◽  
Chen Hong
Keyword(s):  
Success Rate ◽  
Transportation Networks ◽  
Human Mobility ◽  
Transportation Network ◽  
Air Transportation ◽  
Transfer Number ◽  
Multilayer Network ◽  
Scheduling Model ◽  
Network Mechanism ◽  
Random Failures

Air transportation networks play important roles in human mobility. In this paper, from the perspective of multilayer network mechanism, the dynamics of the Chinese air transportation network are extensively investigated. A multilayer-based passengers re-scheduling model is introduced, and a multilayer cooperation (MC) approach is proposed to improve the efficiency of network traffic under random failures. We use two metrics: the success rate and the extra transfer number, to evaluate the efficiency of re-scheduling. It is found that a higher success rate of passengers re-scheduling can be obtained by MC, and MC is stronger for resisting the instability of the capacity of links. Furthermore, the explosion of the number of extra transfer can be well restrained by MC. Our work will highlight a better understanding of the dynamics and robustness of the Chinese air transportation network.

Analysis of Identification Methods of Key Nodes in Transportation Network

2022 ◽  
Author(s):  
Qiang Lai ◽  
Hong-hao Zhang
Keyword(s):  
Transportation Networks ◽  
Transportation Network ◽  
Practical Significance ◽  
Node Degree ◽  
Connected Subgraph ◽  
Network Efficiency ◽  
Identification Methods ◽  
Identification Method ◽  
Bus Networks ◽  
Key Nodes

Abstract The identification of key nodes plays an important role in improving the robustness of the transportation network. For different types of transportation networks, the effect of the same identification method may be different. It is of practical significance to study the key nodes identification methods corresponding to various types of transportation networks. Based on the knowledge of complex networks, the metro networks and the bus networks are selected as the objects, and the key nodes are identified by the node degree identification method, the neighbor node degree identification method, the weighted k-shell degree neighborhood identification method (KSD), the degree k-shell identification method (DKS), and the degree k-shell neighborhood identification method (DKSN). Take the network efficiency and the largest connected subgraph as the effective indicators. The results show that the KSD identification method that comprehensively considers the elements has the best recognition effect and has certain practical significance.

scholarly journals A Data-Driven Urban Metro Management Approach for Crowd Density Control

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Hui Zhou ◽  
Zhihao Zheng ◽  
Xuekai Cen ◽  
Zhiren Huang ◽  
Pu Wang
Keyword(s):  
Local Governments ◽  
Travel Demand ◽  
Transportation Network ◽  
Management Approach ◽  
Time Cost ◽  
Actual Case ◽  
Density Control ◽  
Crowd Density ◽  
Pedestrian Network ◽  
Southern City

Large crowding events in big cities pose great challenges to local governments since crowd disasters may occur when crowd density exceeds the safety threshold. We develop an optimization model to generate the emergent train stop-skipping schemes during large crowding events, which can postpone the arrival of crowds. A two-layer transportation network, which includes a pedestrian network and the urban metro network, is proposed to better simulate the crowd gathering process. Urban smartcard data is used to obtain actual passenger travel demand. The objective function of the developed model minimizes the passengers’ total waiting time cost and travel time cost under the pedestrian density constraint and the crowd density constraint. The developed model is tested in an actual case of large crowding events occurred in Shenzhen, a major southern city of China. The obtained train stop-skipping schemes can effectively maintain crowd density in its safety range.

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