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Optimal public-transport operational strategies to reduce cost and vehicle’s emission

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  • Chunyan Tang
  • Avishai Ceder
  • Ying-En Ge

Abstract

Public transport passenger demand is inevitably made non-uniform because of spatial and temporal land use planning. This non-uniformity warrants the use of public transport operational strategies to attain operating efficiency. The optimization of these strategies is commonly being done from the operator perspective, and indirectly from the user perspective. However, the environmental perspective of these strategies, in terms of vehicle’s emission, has not been investigated. This study proposed a methodology to analyze the benefits of using transit operational strategies to reduce operating cost and eventually also to reduce undesirable emissions. First, a strategy-based optimization model is established to minimize the number of transit vehicles required. Four candidate operational strategies are considered in this model, including full route operation (FRO), short turn, limited stop, and a combination of limited stop and short turn. Second, the pollutant emissions of transit vehicles are estimated by the MOVES emission model. The developed methodology is applied to a real life case study in Dalian, China. Results show that the use of operational strategies can not only significantly save the number of vehicles by 12.5%, but also reduce emissions of pollutants (i.e., CO2, HC, CO, NOx, PM2.5) by approximately 13%, compared with applying FRO strategy exclusively. In addition, both benefits can be further enhanced through the use of an efficient payment mode (e.g., off-board or contactless card) or improving bus performance in deceleration/acceleration as well as doors opening and closing at a stop.

Suggested Citation

  • Chunyan Tang & Avishai Ceder & Ying-En Ge, 2018. "Optimal public-transport operational strategies to reduce cost and vehicle’s emission," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-17, August.
    • Handle: RePEc:plo:pone00:0201138
    DOI: 10.1371/journal.pone.0201138
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    References listed on IDEAS

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    Cited by:

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    5. Guo, Qianwen & Sun, Yanshuo & Schonfeld, Paul & Li, Zhongfei, 2021. "Time-dependent transit fare optimization with elastic and spatially distributed demand," Transportation Research Part A: Policy and Practice, Elsevier, vol. 148(C), pages 353-378.
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