Modeling biomass transport on single lane forest roads and monitoring GPS accuracy for vehicle tracking under different forest canopy conditions Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/5m60qv33c

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  • The transportation of wood and biomass resources from landing and other collection locations to processing and distribution sites is a substantial cost within the wood supply chain. These high costs provide a basis for research aimed at improving biomass transportation planning decisions and potentially reducing biomass transportation costs. Chip vans have been identified to be the most cost-efficient mode of transporting biomass provided the roads are suitable for the trucks which are generally built for highway use. Research to develop chip van performance simulation models for travel time prediction could potentially reduce biomass transportation costs by improving transportation planning decisions. GPS technology has the ability to record information such as location (longitude, latitude and elevation), movement (speed, heading) and travel time which makes it an attractive tool for data collection to develop, test and validate vehicle simulation models. In spite of several studies investigating the accuracy and performance of GPS under different forest conditions, the reliability of GPS receiver measurements for moving vehicles under forest canopy and in mountainous terrain has not been examined. This dissertation includes two manuscripts. One manuscript presents a Chip Van Travel Time Prediction Simulation Model (CHIP-VAN) that was developed using data collected by GPS receivers to track and monitor chip vans. The vans were exclusively used for transporting chipped (ground) biomass from forest operation sites in western Oregon. The other manuscript examines the accuracy and reliability of GPS for vehicle tracking under different forest canopy conditions and mountainous terrain. The model, CHIP-VAN, is developed based on the maximum limiting speeds on each road segment as limited by road grade, stopping sight distance (SSD) and road alignment as well as modeling the driver's behavior as these road conditions change. A two pass simulation was used in the model; the first pass simulation calculates the maximum limiting speeds on each road segment and the second pass simulates the driver's behavior and calculates the travel time. To emulate the driver's behavior, four cases that determine whether a driver will accelerate, decelerate or continue at current speed, were developed. The model has been tested for validation using the data collected for the study. The validation tests suggest that the model is appropriate for predicting travel time for chip vans on single lane forest roads with acceptable accuracy. The findings in the second study demonstrate that the GPS tracking accuracy of vehicles on forested roads are clearly influenced by the composition of the surrounding canopy, with the strongest influence being from heavy forest canopy cover. Accuracy is generally improved in areas with less forest canopy. The study concludes that the consumer-grade GPS receiver measurements determined are acceptable for tracking and improving biomass transport from forest supply locations to distribution and processing centers. The analysis of the range of accuracies found for vehicles operating within heavy forest canopy cover demonstrates that the accuracies are probably acceptable for many forest transportation monitoring and planning applications, including the mapping of forest road locations and other forest transportation operations. It is expected that the CHIP-VAN model and GPS accuracy studies will aid forest transportation managers in decision making and transportation planning in biomass operations. Most importantly it is hoped that the results of this research will increase transportation management planning efficiency for biomass and lead to improved methods for developing biomass cost assessments
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