NEtworK Optimization for CarSharing Integration into a Multimodal TRANSportation System (EkoCS-Trans)
| Reference number | |
| Coordinator | Linköpings universitet - Department of Science and Technology |
| Funding from Vinnova | SEK 5 524 678 |
| Project duration | November 2018 - June 2023 |
| Status | Ongoing |
| Venture | 2018-02510-en |
Purpose and goal
The project´s goal is to research conditions that allow an increased availability and usage of the environmentally friendly transportation mode carsharing (CS) in Sweden as part of a multimodal transportation systemto design a CS system that taps the full demand potential. To this end, we will develop a decision support tool for the design of a CS network. This will consist of two integrated parts: We will add CS usage to an an existing transport model system, and we will develop a precise mathematical framework for the optimization of the design of a CS system.
Expected results and effects
This project will (i) enable Swedish businesses to design a CS system that taps the full travel demand potential (i.e., attracts a wider customer base) and (ii) equip Swedish authorities with planning tools to prepare for the broad adaptation of shared vehicles. These measures will in turn allow for the environmental and societal benefits of massive CS, for example, statistically significantly reduced household GHG emissions, a reduction in privately owned vehicles, reduced congestion, improved air quality, and freed urban space.
Planned approach and implementation
The project will be realized within the Communications and Transport Systems (KTS) division at the Department of Science and Technology (ITN), Linköping University, and within the division Traffic Analysis and Logistics (TAL) of the Swedish National Road and Transport Research Institute (VTI). The project will mainly be performed as a PhD study, and consists of three (overlapping) work packages: CS model development, Optimization Methods, and a Case Study Stockholm. A reference group will be involved throughout all work.