Container Transportation Network Equilibrium Analysis Considering Draft of Vessel

This paper analyzes container transportation network equilibrium considering draft of vessels. Concept of load factor (λ) of ship is included in the model. Three players are considered, i.e. port administrator, ship companies (carriers), and shippers. Interaction of these players leads to Nash equilibrium problem. The result of the model calculation indicates that Hong Kong and Singapore port dominates container throughput in the world and the big vessel (3000 - 6000 TEU) is dominant in these ports. Conversely, the smaller port with depth less than 15 m dominated by 1000 TEU vessels. The result is inline with the reality. The other finding from the study is 6000 TEU vessels can enter port with depth less than 15 m such as port of Shanghai. Again, it is inline with reality. Validation of the model shows that coefficient of determination (R2) is 0.95. It indicates the model provides good accuracy

A Model of the Rise and Fall of Roads

Transportation network planning decisions made at one point of time can have profound impacts in the future. However, transportation networks are usually assumed tobe static in models of land use. A better understanding of the natural growth pattern of roads will provide valuable guidance to planners who try to shape the future network. This paper analyzes the relationships between network supply and travel demand, and describes a road development and degeneration mechanism microscopically at the linklevel. A simulation model of transportation network dynamics is developed, involving iterative evolution of travel demand patterns, network revenue policies, cost estimation,and investment rules. The model is applied to a real-world congesting network – the Twin Cities transportation network which comprises nearly 8,000 nodes and more than 20,000 links, using network data collected since year 1978. Four experiments are carried out with different initial conditions and constraints, the results from which allow us toexplore model properties such as computational feasibility, qualitative implications, potential calibration procedures, and predictive value. The hypothesis that roadhierarchies are emergent properties of transportation networks is confirmed, and the underlying reasons discovered. Spatial distribution of capacity, traffic flow, andcongestion in the transportation network is tracked over time. Potential improvements to the model in particular and future research directions in transportation network dynamicsin general are also discussed.Transportation network dynamics, Urban planning, Road suppl

Paving New Ground

This paper explores the inter-connectedness and co-evolution of transportation networks and land use through the application of a Markov Chain model to the Twin Cities from 1958 through 1990. This model investigates how individual cells, with both land use and transportation network attributes, change over time. Cells with more transportation network available are more likely to develop, and cells that are developed are more likely to attract additional highway investment.Transportation Network Growth, Transportation-Land Use Interaction, Markov Chain

The worldwide air transportation network: Anomalous centrality, community structure, and cities' global roles

We analyze the global structure of the world-wide air transportation network, a critical infrastructure with an enormous impact on local, national, and international economies. We find that the world-wide air transportation network is a scale-free small-world network. In contrast to the prediction of scale-free network models, however, we find that the most connected cities are not necessarily the most central, resulting in anomalous values of the centrality. We demonstrate that these anomalies arise because of the multi-community structure of the network. We identify the communities in the air transportation network and show that the community structure cannot be explained solely based on geographical constraints, and that geo-political considerations have to be taken into account. We identify each city's global role based on its pattern of inter- and intra-community connections, which enables us to obtain scale-specific representations of the network.Comment: Revised versio

Chapter 13 - Sharing strategies: carsharing, shared micromobility (bikesharing and scooter sharing), transportation network companies, microtransit, and other innovative mobility modes

Shared mobility—the shared use of a vehicle, bicycle, or other mode—is an innovative transportation strategy that enables users to gain short-term access to transportation modes on an “as-needed” basis. It includes various forms of carsharing, bikesharing, scooter sharing, ridesharing (carpooling and vanpooling), transportation network companies (TNCs), and microtransit. Included in this ecosystem are smartphone “apps” that aggregate and optimize these mobility options, as well as “courier network services” that provide last mile package and food delivery. This chapter describes different models that have emerged in shared mobility and reviews research that has quantified the environmental, social, and transportation-related impacts of these services

The Weakest Link: A Model of the Decline of Surface Transportation Networks

This study explores the economic mechanisms behind the decline of a surface transportation network, based on the assumption that the decline phase is a spontaneous process driven by decentralized decisions of individual travelers and privatized links. A simulation model is developed with a degeneration process by which the weakest link is removed iteratively from the network. Experiments reveal how the economic efficiency of a network evolves during the degeneration process and suggest an 'optimal' degenerated network could be derived during the decline phase in terms of maximizing total social welfare. Keywords: decline, transportation network, degeneration, welfare, accessibilityNetworks, Transportation, Structure, Entropy, Pattern, Continuity

Robustness and Closeness Centrality for Self-Organized and Planned Cities

Street networks are important infrastructural transportation systems that cover a great part of the planet. It is now widely accepted that transportation properties of street networks are better understood in the interplay between the street network itself and the so called \textit{information} or \textit{dual network}, which embeds the topology of the street network navigation system. In this work, we present a novel robustness analysis, based on the interaction between the primal and the dual transportation layer for two large metropolis, London and Chicago, thus considering the structural differences to intentional attacks for \textit{self-organized} and planned cities. We elaborate the results through an accurate closeness centrality analysis in the Euclidean space and in the relationship between primal and dual space. Interestingly enough, we find that even if the considered planar graphs display very distinct properties, the information space induce them to converge toward systems which are similar in terms of transportation properties