Impacts of Model Resolution on Transportation Network Criticality Rankings

2017 ◽  
Vol 2653 (1) ◽  
pp. 93-100 ◽  
Author(s):  
Jonathan Dowds ◽  
Karen Sentoff ◽  
James L. Sullivan ◽  
Lisa Aultman-Hall
Keyword(s):  
Travel Demand ◽  
Transportation Network ◽  
Network Connectivity ◽  
Network Robustness ◽  
Demand Models ◽  
Lower Volume ◽  
Travel Delay ◽  
The Impact ◽  
Aggregate Nature ◽  
Demand Aggregation

Objective rankings of the criticality of transportation network infrastructure are essential for efficiently allocating limited adaptation resources and must account for network connectivity and travel demand. Road link criticality can be quantified by the total travel delay caused when the capacity of a road segment or link is disrupted or removed. These methods can use standard travel demand models, but the exclusion of lower-volume roads and the aggregate nature of traffic analysis zones may distort resulting criticality rankings. To test the impact of link exclusion and demand aggregation, the authors applied the network robustness index, a well-established link criticality measure, to a hypothetical network with varying levels of network resolution and demand aggregation. The results show a statistically significant change in criticality rankings when demand is aggregated and especially when links are excluded from the network, suggesting that criticality rankings may be distorted when estimated with typical demand models. Application to a road network in Vermont supports the finding on the impact of network resolution on criticality rankings.

scholarly journals Rewiring Strategy Based on Directed Betweenness to Mitigate Disruptions of Large-Scale Supply Chain Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Hui Xia
Keyword(s):  
Supply Chain ◽  
Empirical Data ◽  
Large Scale ◽  
Network Connectivity ◽  
The Other ◽  
Network Robustness ◽  
Data Driven ◽  
Supply Chain Network ◽  
Supply Chain Networks ◽  
The Impact

In current large-scale supply chain networks, unexpected disruptions degrade the supply availability and network connectivity for modern enterprises. How to improve the robustness of supply chain networks is very important for modern enterprises. In this paper, we explore how to improve the robustness of supply chain networks from a topological perspective. Firstly, through the empirical data-driven study, we show that the directed betweenness metric is more suitable than the other topological metrics in evaluating the robustness of supply chain networks. Then, we propose a rewiring algorithm based on directed betweenness to improve network robustness under the impact of disruptions. The experimental results in the large-scale supply chain network show that the rewiring algorithm based on directed betweenness effectively improves the network robustness.

scholarly journals The impact of COVID-19 on the worldwide air transportation network

2021 ◽  
Vol 8 (11) ◽  
Author(s):  
Xiaoge Bao ◽  
Peng Ji ◽  
Wei Lin ◽  
Matjaž Perc ◽  
Jürgen Kurths
Keyword(s):  
Structural Characteristics ◽  
Average Distance ◽  
Transportation Network ◽  
Optimal Strategies ◽  
Air Transportation ◽  
Network Robustness ◽  
Low Degree ◽  
Flight Cancellations ◽  
The Individual ◽  
The Impact

Air travel has been one of the hardest hit industries of COVID-19, with many flight cancellations and airport closures as a consequence. By analysing structural characteristics of the Official Aviation Guide flight data, we show that this resulted in an increased average distance between airports, and in an increased number of long-range routes. Based on our study of network robustness, we uncover that this disruption is consistent with the impact of a mixture of targeted and random global attack on the worldwide air transportation network. By considering the individual functional evolution of airports, we identify anomalous airports with high centrality but low degree, which further enables us to reveal the underlying transitions among airport-specific representations in terms of both geographical and geopolitical factors. During the evolution of the air transportation network, we also observe how the network attempted to cope by shifting centralities between different airports around the world. Since these shifts are not aligned with optimal strategies for minimizing delays and disconnects, we conclude that they are consistent with politics trumping science from the viewpoint of epidemic containment and transport.

Developing an Empirical Pipeline and Rail Crude Oil Mode Split and Route Assignment Model

2018 ◽  
Vol 2672 (9) ◽  
pp. 261-272
Author(s):  
Adam Morrison ◽  
Chris Bachmann ◽  
Frank Saccomanno
Keyword(s):  
Crude Oil ◽  
Transportation Network ◽  
Network Connectivity ◽  
Modal Shift ◽  
Rail Network ◽  
Assignment Model ◽  
Mode Split ◽  
Demand Models ◽  
Oil Flow ◽  
Keystone Xl

In recent years, improvements in pipeline capacities and connectivity have been inhibited by environmental and political concerns (e.g., the Dakota and Keystone XL pipeline expansion projects). This has resulted in a greater dependency on rail transport, and this modal shift of crude oil from pipeline to rail is likely to become more pronounced in the future. Therefore, there is a need to assess the impacts of future changes in pipeline/rail network connectivity, modal attributes, and shipment protocols, on the expected pattern of crude oil shipments. This paper presents a rule-based mode split and route assignment model that reflects real-world allocation, assignment, and apportionment rules. The decision-making process underlying this model is the shipper, who is prioritized by the carrier when there is limited pipeline capacity available. The proposed algorithm allows for the inclusion of crude oil shipments and the pipeline network into conventional freight demand models by capturing the complex interactions of crude shippers, pipeline carriers, and regulatory bodies. This paper demonstrates how the model can be used to predict changes in Canadian crude oil flow patterns and mode shares subject to changes in specific transportation network attributes or crude oil demands.

Accuracy and Performance of Improved Speed-Flow Curves

1998 ◽  
Vol 1646 (1) ◽  
pp. 9-17 ◽  
Author(s):  
Richard G. Dowling ◽  
Rupinder Singh ◽  
Willis Wei-Kuo Cheng
Keyword(s):  
Travel Demand ◽  
Traffic Assignment ◽  
Demand Model ◽  
Power Functions ◽  
Flow Curves ◽  
Speed Flow ◽  
Demand Models ◽  
Higher Power ◽  
The Impact ◽  
Travel Demand Model

Skabardonis and Dowling recommended updated Bureau of Public Road speed-flow curves for freeways and signalized arterials to improve the accuracy of speed estimates used in transportation demand models. These updated curves generally involved the use of higher power functions that show relatively little sensitivity to volume changes until demand exceeds capacity, when the predicted speed drops abruptly to a very low value. Skabardonis and Dowling demonstrated that the curves provide improved estimates of vehicle speeds under both uncongested and queueing conditions; however, they did not investigate the impact of these curves on the performance of travel demand models. Practitioners have been concerned about the impacts of such abrupt speed-flow curves on the performance of their travel demand models. Spiess has stated that higher power functions are more difficult computationally for computers to evaluate and that more abrupt speed-flow curves adversely affect the rate of convergence to equilibrium solutions in the traffic assignment process. In this paper the impact of the Skabardonis and Dowling updated speed-flow curves on the performance of selected travel demand models is investigated. The updated speed-flow curves were found to significantly increase travel demand model run times. However, it is demonstrated that an alternative speed-flow equation developed by Akçelik has similar or better accuracy and provides much superior convergence properties during the traffic assignment process. The Akçelik curve significantly reduced travel demand model run times.

scholarly journals Impact of Weather Conditions on Travel Demand – The Most Common Research Methods and Applied Models

2020 ◽  
Vol 32 (5) ◽  
pp. 711-725
Author(s):  
Dragana Petrović ◽  
Ivan Ivanović ◽  
Vladimir Đorić ◽  
Jadranka Jović
Keyword(s):  
Research Methods ◽  
Travel Demand ◽  
Weather Conditions ◽  
Travel Behaviour ◽  
Transport Systems ◽  
Small Samples ◽  
Local Conditions ◽  
Modal Split ◽  
Demand Models ◽  
The Impact

This paper presents an overview of the applied research methodologies and developed travel demand models that take weather impact into account. The paper deals with trip generation and modal split as elements of travel demand that best describe changes in the travel behaviour in different weather conditions. The authors herein emphasize the importance of research in local conditions in all climate zones, especially in areas where climate and modal split characteristics are different from those in common research areas. This review is designed as a brief guide on how the impact of weather can be explored in order to encourage conducting research even in the countries where there is no systematic traffic and travel data collection. The stated adaptation technique followed by the panel household travel surveys may be particularly appropriate for those countries. It is concluded that small budgets should not be considered an obstacle, because it is possible to draw reliable conclusions based even on small samples. Moreover, modern research methods enable a cheaper survey process together with the possibility of obtaining higher quality of results. The increasing popularity of research in this field should contribute to the creation of more resilient transport systems all over the world. A special contribution of this paper is the review of research studies carried out in central, western and southern Europe and not mentioned in any review paper before.

scholarly journals Hierarchical Passenger Hub Location Problem in a Megaregion Area Considering Service Availability

2021 ◽  
Vol 33 (2) ◽  
pp. 247-258
Author(s):  
Huang Yan ◽  
Xiaoning Zhang ◽  
Xiaolei Wang
Keyword(s):  
Travel Demand ◽  
Transportation Network ◽  
Mixed Integer ◽  
Service Availability ◽  
Hub Location ◽  
Hub Location Problem ◽  
Passenger Transportation ◽  
Linear Programming Formulation ◽  
Wuhan Metropolitan Area ◽  
The Impact

The rapid growth of the intercity travel demand has resulted in enormous pressure on the passenger transportation network in a megaregion area. Optimally locating hubs and allocating demands to hubs influence the effectiveness of a passenger transportation network. This study develops a hierarchical passenger hub location model considering the service availability of hierarchical hubs. A mixed integer linear programming formulation was developed to minimize the total cost of hub operation and transportation for multiple travel demands and determine the proportion of passengers that access hubs at each level. This model was implemented for the Wuhan metropolitan area in four different scenarios to illustrate the applicability of the model. Then, a sensitivity analysis was performed to assess the impact of changing key parameters on the model results. The results are compared to those of traditional models, and the findings demonstrate the importance of considering hub choice behavior in demand allocation.

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.

Model-Based Long-Range Transportation Planning Tool for New Jersey

2002 ◽  
Vol 1817 (1) ◽  
pp. 93-101
Author(s):  
Anthony J. De John ◽  
Robert Miller ◽  
Kyle B. Winslow ◽  
Jennifer J. Grenier ◽  
Deborah A. Cano
Keyword(s):  
New Jersey ◽  
Long Range ◽  
Travel Demand ◽  
Management Strategies ◽  
Transportation System ◽  
Transportation Systems ◽  
Analysis Tool ◽  
Demand Model ◽  
Demand Models ◽  
The Impact

The New Jersey Department of Transportation (NJDOT) updates its long-range transportation plan every 5 years. The plan sets forth strategies, provides a framework for directing investment, and identifies financial resources needed to sustain the plan’s vision. Setting the direction of a long-range transportation program revolves around forecasting future transportation conditions and managing investments to address future needs. An analysis tool was needed to help assess the impact of growth on the statewide transportation system and predict system performance based on multimodal strategic investments. The development and use of an analysis tool based on a travel demand model to assess congestion and mobility issues in 2025 are described. The analysis tool linked the state’s three metropolitan planning organization (MPO) regional travel demand models to perform a statewide assessment. Although the models were run independently, methods were developed to provide a common basis for forecasting future travel conditions. The models used MPO-generated trend-based growth in population and employment through 2025. Multimodal transportation supply and demand strategies, including transit improvements, capacity improvements, transportation demand management strategies, and intelligent transportation systems-transportation system management strategies, were simulated and tested to assess what types and combinations of improvements would be needed to relieve congestion and improve mobility. The tool proved very helpful in defining transportation needs and providing input to a financial assessment. The testing indicated that no single strategy is likely to improve future travel conditions, but a combination of multimodal strategies offers significant improvements over congestion levels predicted for 2025 if no improvements are made.

scholarly journals What affects how far individuals walk?

2021 ◽  
Vol 3 (3) ◽  
Author(s):  
Aryan Hosseinzadeh
Keyword(s):  
Influencing Factors ◽  
Transportation Network ◽  
Network Connectivity ◽  
Decision Makers ◽  
Walking Distance ◽  
Contributing Factors ◽  
Environmental Indices ◽  
Factors Associated ◽  
Mode Of Transportation ◽  
The Impact

AbstractThe number of studies that explore contributing factors that encourage individuals to do more walking trips is proliferated in recent years. However, there is still a lot to know about differentiating between short and long walking trips and their associated influencing factors. The current research investigated the impact of the influencing factors on the share of short and long walking trips across four different trips in 112 traffic analysis zones of Rasht, Iran. The share of walking trips was defined as the proportion of walking trips that originated/ended in an area on all trips that originated/ended in that area. In four trip purposes in short, long, and all trips, the factors associated with the share of walking in origins and destinations were investigated in 24 separate models. The factors included built environmental indices, such as transportation network connectivity and land-use variables, as well as socio-demographic. To differentiate between short and long walking trips, 600 m walking distance was recognized as a proxy. According to the results, the population density was found significantly increase share of walking in both the origins and destinations of short walking trips. Moreover, the models’ goodness of fits were relatively higher in short walking trips comparing long walking trips. This research's findings would give a profound assessment to city planners and decision makers who favor expanding walking as a sustainable mode of transportation.

scholarly journals Windowed Transportation Planning Model

1997 ◽  
Vol 1607 (1) ◽  
pp. 45-54 ◽  
Author(s):  
David M. Levinson ◽  
Yuanlin Huang
Keyword(s):  
Traffic Congestion ◽  
Transportation Planning ◽  
Travel Demand ◽  
Transportation Network ◽  
Demand Management ◽  
Local Area ◽  
Planning Model ◽  
Travel Demand Management ◽  
Traffic Calming ◽  
The Impact

A transportation planning model that integrates regional and local-area forecasting approaches is developed and applied. Although regional models have the scope to model the interaction of demand and congestion, they lack spatial detail. Local-area analysis typically does not consider the feedback between new project loadings and existing levels of traffic. A windowed model, which retains regional trip distribution information and the consistency between travel demand and congestion, permits the use of a complete transportation network and block-level traffic zones while retaining computational feasibility. By combining the two methods a number of important policy issues can be addressed, including the implications of traffic calming, changes in flow due to alternative traffic operation schemes, the influence of microscale zoning changes on nearby intersections, and the impact of travel demand management on traffic congestion.

Sign in / Sign up

Export Citation Format

Share Document