Using i-dolly for local distribution of container trailers to logistic terminals from a dry port
Reference number | |
Coordinator | Volvo Technology AB - Advanced Technology & Research |
Funding from Vinnova | SEK 7 493 444 |
Project duration | October 2017 - August 2021 |
Status | Completed |
Venture | Transport Efficiency |
End-of-project report | 2017-03036eng.pdf (pdf, 4559 kB) |
Important results from the project
The project has aimed to develop a self-propelled dolly (iDolly) for distribution of containers from a dry port to nearby logistics terminals. The project has shown what eligibility requirements and needs need to be met to fit into the logistics system, how an iDolly should be designed technically, including specific aspects of automation. The possible impact on the infrastructure has also been studied. Several vehicle tests and demonstrations have been carried out, but full autonomous driving on site in the industrial area could not be carried out as a special permit is required.
Expected long term effects
The project has resulted in valuable knowledge about how an interconnected logistics system works. The project has also resulted in concrete design solutions for iDolly. Furthermore, a number of different control models have been developed and simulations have been carried out for autonomous operation of an iDolly. The knowledge has in turn also been used for the development of a new product. However, the project shows that neither technology nor logistics systems are yet ripe for full automation. It is probably best to take this in steps via electrified and remotely operated vehicles.
Approach and implementation
The project has used several different approaches for implementation and analysis. Theoretical studies formed an important basis for the regulatory models that were developed. Modeling and simulation have also been used in a broader perspective to analyze, for example, logistics flows. Both scaled-down vehicles and full-scale vehicles have been used for tests and demonstrations. Collaboration between most project partners to understand how the logistics system can be developed, ie empirical data, has also played a central role in modeling, data collection and analysis.