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A method to assess demand growth vulnerability of travel times on road network links

Listed author(s):
  • Watling, David
  • Balijepalli, N.C.
Registered author(s):

    Many national governments around the world have turned their recent focus to monitoring the actual reliability of their road networks. In parallel there have been major research efforts aimed at developing modelling approaches for predicting the potential vulnerability of such networks, and in forecasting the future impact of any mitigating actions. In practice—whether monitoring the past or planning for the future—a confounding factor may arise, namely the potential for systematic growth in demand over a period of years. As this growth occurs the networks will operate in a regime closer to capacity, in which they are more sensitive to any variation in flow or capacity. Such growth will be partially an explanation for trends observed in historic data, and it will have an impact in forecasting too, where we can interpret this as implying that the networks are vulnerable to demand growth. This fact is not reflected in current vulnerability methods which focus almost exclusively on vulnerability to loss in capacity. In the paper, a simple, moment-based method is developed to separate out this effect of demand growth on the distribution of travel times on a network link, the aim being to develop a simple, tractable, analytic method for medium-term planning applications. Thus the impact of demand growth on the mean, variance and skewness in travel times may be isolated. For given critical changes in these summary measures, we are thus able to identify what (location-specific) level of demand growth would cause these critical values to be exceeded, and this level is referred to as Demand Growth Reliability Vulnerability (DGRV). Computing the DGRV index for each link of a network also allows the planner to identify the most vulnerable locations, in terms of their ability to accommodate growth in demand. Numerical examples are used to illustrate the principles and computation of the DGRV measure.

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    Article provided by Elsevier in its journal Transportation Research Part A: Policy and Practice.

    Volume (Year): 46 (2012)
    Issue (Month): 5 ()
    Pages: 772-789

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    Handle: RePEc:eee:transa:v:46:y:2012:i:5:p:772-789
    DOI: 10.1016/j.tra.2012.02.009
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    1. Chen, Anthony & Yang, Hai & Lo, Hong K. & Tang, Wilson H., 2002. "Capacity reliability of a road network: an assessment methodology and numerical results," Transportation Research Part B: Methodological, Elsevier, vol. 36(3), pages 225-252, March.
    2. Jenelius, Erik & Petersen, Tom & Mattsson, Lars-Göran, 2006. "Importance and exposure in road network vulnerability analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(7), pages 537-560, August.
    3. Michael Taylor & Somenahalli Sekhar & Glen D'Este, 2006. "Application of Accessibility Based Methods for Vulnerability Analysis of Strategic Road Networks," Networks and Spatial Economics, Springer, vol. 6(3), pages 267-291, September.
    4. Clark, Stephen & Watling, David, 2005. "Modelling network travel time reliability under stochastic demand," Transportation Research Part B: Methodological, Elsevier, vol. 39(2), pages 119-140, February.
    5. Berdica, Katja, 2002. "An introduction to road vulnerability: what has been done, is done and should be done," Transport Policy, Elsevier, vol. 9(2), pages 117-127, April.
    6. Agachai Sumalee & Fumitaka Kurauchi, 2006. "Guest Editorial: Reliability and Emergency Issues in Transportation Network Analysis," Networks and Spatial Economics, Springer, vol. 6(3), pages 169-172, September.
    7. W. Szeto & L. O'Brien & M. O'Mahony, 2006. "Risk-Averse Traffic Assignment with Elastic Demands: NCP Formulation and Solution Method for Assessing Performance Reliability," Networks and Spatial Economics, Springer, vol. 6(3), pages 313-332, September.
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