Roger Stough

George Mason University, Fairfax, VA, USA

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Publications (4)1.02 Total impact

  • Article: Traffic Grammar and Algorithmic Complexity in Urban Freeway Flow Patterns
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    ABSTRACT: This paper uses techniques from formal language theory to describe the linear spatial patterns in urban freeway traffic flows in order to understand and analyze “hidden order” in such high volume systems. A method for measuring randomness based on algorithmic entropy is introduced and developed. These concepts are operationalized using Pincus’ approximate entropy formulation in an appropriate illustration. These measures, which may be viewed as counterintuitive, are believed to offer robust and rigorous guidance to enhance the overall understanding of efficiency in urban freeway traffic systems. Utilization of such measures should be facilitated by information generated by real time intelligent transportation systems (ITS) technologies and may prove helpful in real time traffic flow management.
    Networks and Spatial Economics 04/2012; 7(4):333-351. · 1.02 Impact Factor
  • Chapter: Hidden Order in Traffic Flows Using Approximate Entropy: An Illustration
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    ABSTRACT: The dynamic nature of traffic flows on urban freeways is self-evident. The plots of workday traffic on segments of major roads against time of day display the familiar contours of lumpy, peaked curves. Over the years the peaks have become blunt and the valleys filled, suggesting nearly day long high-volume traffic. At the same time that the average travel speed on congested freeways has gone up, average commute time has either remained steady or increased marginally and the number of accidents per 100 million VMTs has gone down or remained constant (Gordon et al. 1991; BTS 2006). Traffic at high volumes and high speeds or under designed roads should result in more accidents and slower travel times. This has not occurred but traffic has continued to increase. Congested traffic patterns suggest an inherent disorder or randomness. Could it be that there is a hidden order in the congested traffic patterns? It would be helpful to analyze and understand these linear spatial patterns to see the degree to which order/disorder associated with these patterns can be determined.
    07/2009: pages 143-159;
  • Source
    Article: Network Usage Patterns and the Substitution and Complementarity Effects Between Telecommunications and Transportation: A Demand Side Approach
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    ABSTRACT: The conventional literature on telecommunication does not appear to have focused on the various sources of interactions between telecommunication networks and other networked infrastructure. Further, much of the transportation literature suggests that transportation and telecommunication infrastructures are substitutes. The focus of this paper is to examine the scope of interaction between two types of infrastructures. In our previous paper we tested for network interaction effects by using a translog production function. The results suggested that there is a significant interaction between these two networked infrastructures. In this paper, further analysis suggests that the sources of interaction are related to the usage patterns of the two networks.
    06/2000;
  • Article: High-technology employment and hub airports
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    ABSTRACT: Deregulation of the US domestic air transport market in 1978 brought significant benefits to air travelers. The scheduled airlines have been given the freedom to improve their efficiency through being able to adopt efficient network strategies and more effective operating practices. This study examines empirically the advantages enjoyed by those passengers having access to a major hub airport. These often include more direct services, more frequent services and a wider range of interconnecting destinations. We seek to examine the benefits that local urban areas enjoy as the result of a major airline selecting the region as the fulcrum point for its hub-and-spoke services.
    Journal of Air Transport Management.

Institutions

  • 2009–2012
    • George Mason University
      • School of Public Policy
      Fairfax, VA, USA