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Data-Driven Optimization for Intelligent and Efficient Transports (DOIT)

Reference number
Coordinator Scania CV Aktiebolag - Avd REPI, Systems Development, Pre-Development ITS
Funding from Vinnova SEK 6 150 533
Project duration March 2014 - January 2018
Status Completed
Venture Transport Efficiency
End-of-project report 2013-05624.pdf (pdf, 624 kB)

Important results from the project

The primary objective of the DoIT project is demonstrate the implementation of a data driven approach and how this can to applied within the heavy duty transport domain. This primary objective has been fulfilled by the development and research into assignment planning optimization and fuel prediction models.

Expected long term effects

The project has resulted in a number of contributing factors including; -increased knowledge of big data and machine learning methods -development of data-driven fuel models for optimizing resource utilization and route planning; and minimization of fuel consumption -web based application demonstrating the solution as they apply to various use cases -publications have been submitted by SICS in relation to WP3 data analysis and WP4 data driven planning and optimization (T2017:06,T2017:07,T2018:01) -Two patient applications have been submitted by Scania

Approach and implementation

The project has been executed as defined in the original base report. This included organizing the project into five work packages with their own set of objectives and deliverables. The work packages were then allocated across resources at Scania and SICS. SICS was responsible for driving the research and development of algorithms. While Scania in a project management capacity ensured project milestones and objectives were achieved. Additionally Scania designed and developed a solution architecture that demonstrated the application of these algorithms created by SICS.

External links

The project description has been provided by the project members themselves and the text has not been looked at by our editors.

Last updated 15 January 2020

Reference number 2013-05624