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Investigating traffic congestion: Targeting technological and social interdependencies through general morphological analysis

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  • Duczynski, Guy

Abstract

Many (all?) large cities are experiencing traffic congestion in one form or another. This is typically manifested in the morning and afternoon commutes as the largest numbers of public transport passengers (on rail, tram, bus and ferry) and private car users seek to negotiate transport corridors that are not designed for those volumes within those compressed time frames. It has become known as ‘gridlock’ and is characteristic of a system pushed well beyond a tipping point. The problem has both technological and social origins with one contributing to and indeed magnifying the other. It is a ‘wicked, messy’ problem and one that has not responded to (and likely never will) conventional planning practices. This paper investigates the utility of General Morphological Analysis to present the causal factors from a systems-based perspective; expose the underlying and unfavourable conditions that conspire in knowable ways to create this congestion; and offer a more favourable set of conditions based on necessary technological and social adjustments that can eliminate, or at least reduce, the congestion. The method outlined encourages planners to appreciate the complexity of the problem space and design meaningful lines of effort based on a deepened appreciation of numerous interdependencies. The research findings can benefit any large city experiencing congestion and low participation levels in public transport.

Suggested Citation

  • Duczynski, Guy, 2018. "Investigating traffic congestion: Targeting technological and social interdependencies through general morphological analysis," Technological Forecasting and Social Change, Elsevier, vol. 126(C), pages 161-167.
  • Handle: RePEc:eee:tefoso:v:126:y:2018:i:c:p:161-167
    DOI: 10.1016/j.techfore.2017.05.019
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    References listed on IDEAS

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    1. T Ritchey, 2006. "Problem structuring using computer-aided morphological analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(7), pages 792-801, July.
    2. Taylor, Brian D., 2002. "Rethinking Traffic Congestion," University of California Transportation Center, Working Papers qt2fb4t8wd, University of California Transportation Center.
    3. Richard Arnott & Tilmann Rave & Ronnie Schöb, 2005. "Alleviating Urban Traffic Congestion," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262012197, December.
    4. O'Neal, Charles R., 1970. "New approaches to technological forecasting-- Morphological analysis : An integrative approach," Business Horizons, Elsevier, vol. 13(6), pages 47-58, December.
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