Optimized route selection for logging trucks

Sammanfattning: The forestry sector is playing an important role in the transition to a bioeconomy.In the supply chain of forest raw material, logging transport is a crucial component. The forestry sector must improve transport efficiency to mitigate its impact on the environment, to reduce costs and road safety risks,and to remain competitive. Forestry transport in Sweden is paid according to payload and distance travelled. The forestry sector has developed a system for distance measurement, Calibrated Route Finder (CRF), which balances quantitative factors, such as distance, functional road class and road width, with qualitative factors, such as stress and traffic safety. An inverse optimization process is used to translate best-practice routes into a weighted objective that is used when new routes are generated. The objectives of this thesis have been to improve CRF, by including features describing road curvature and hilliness, and addressing illegal or impossible turns in intersections. Methods have been developed to calculate curvature and hilliness using available data in the national road data base. The study has proposed an augmentation of the road data network so that illegal, non-logical and undesirable turns and short-cuts can be considered. The augmented network also enables detailed descriptions of increased time and fuel consumption in relation to intersections, which provides opportunities to generate routing with a focus on minimizing cost or greenhouse emissions. Two of the major cost elements in logging transport are time and fuel consumption, and this study has shown that fuel consumption is mainly affected by road gradient and truck weight, while operating speed is mainly affected by horizontal curvature and surface roughness. A new variable was introduced, integrated gradient, which describes the vertical work performed by the truck on undulating road sections better than the gradient variable.

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