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Dynamic route planning in the Baltic Sea Region – A cost-benefit analysis based on AIS data

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  • Peter Andersson

    (Department of Management and Engineering, Linkoping University)

  • Pernilla Ivehammar

    (Department of Management and Engineering, Linkoping University)

Abstract

Increased international trade, together with a growing concern about global emissions, raises demands to make transportation at sea more efficient. Most ways to reduce emissions will increase sea transportation costs. Dynamic route planning at sea is a concept that allows simultaneous emissions reduction and savings for ship owners. With route plans and coordination centres, ships may take shorter routes and adjust to more efficient speeds, instead of anchoring and then awaiting for berth. Using data from ships’ Automatic Identification System (AIS) transmitters, we measure the sailed distance, as well as the number and the anchored time for cargo (general cargo, bulk, container and RoRo) and tanker ships on a representative day in the Baltic Sea Region. Benefits and costs are estimated using unit prices for emissions and other costs. We find that the benefits of dynamic route planning outweigh its costs; the most decisive factors are (i) by how much distances are reduced and (ii) the unit values of emissions. For each percentage point distances that can be reduced, benefits are estimated at €102 million per year. Adding benefits of adjusted arrival times and subtracting estimated costs, net gains are found in the range of €84–98 million per year. The availability of AIS data provides new opportunities to quantify the traffic at sea and evaluate proposals to make sea transportation more efficient. The methodology can, apparently, be applied to other areas with dense sea traffic.

Suggested Citation

  • Peter Andersson & Pernilla Ivehammar, 2017. "Dynamic route planning in the Baltic Sea Region – A cost-benefit analysis based on AIS data," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 19(4), pages 631-649, December.
  • Handle: RePEc:pal:marecl:v:19:y:2017:i:4:d:10.1057_mel.2016.18
    DOI: 10.1057/mel.2016.18
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    References listed on IDEAS

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    2. Xiaoyuan Wang & Xinyue Zhao & Gang Wang & Quanzheng Wang & Kai Feng, 2022. "Weather Route Optimization Method of Unmanned Ship Based on Continuous Dynamic Optimal Control," Sustainability, MDPI, vol. 14(4), pages 1-15, February.

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