Feasibility study for large-scale on-demand public transport for increased travel
Reference number | |
Coordinator | Nobina Sverige AB |
Funding from Vinnova | SEK 500 000 |
Project duration | March 2023 - September 2023 |
Status | Completed |
Venture | Accelerate - FFI |
Call | Accelerate the transition to sustainable road transport - autumn 2022 |
End-of-project report | 2023-00041svenska.pdf(pdf, 1229 kB) (In Swedish) |
Important results from the project
In this study, we explore how the city of Linköping can implement on-demand transportation on a larger scale. The study will present proposals along with simulations depicting the solution and estimated number of riders. The project´s objectives are as follows: 1. Increase public transportation ridership through improved accessibility. 2. Achieve economic sustainability for public transportation. 3. Facilitate faster implementation and greater effectiveness of large-scale on-demand solutions for public transportation.
Expected long term effects
The study resulted in five scenarios that have been developed as potentially suitable options for the large-scale on demand. The scenarios are as follows: 1) Senior Transportation 2) High Travel Time Ratio Journeys 3) First and Last Mile 4) Nighttime Replacement of Scheduled Routes 5) Combining Scenario 1 and 2. All of these scenarios have been simulated to understand factors such as the number of passengers and vehicle. Scenario 4 shows the highest potential for high ridership, but scenarios 2 and 3 also demonstrate significant potential for high ridership and efficiency.
Approach and implementation
We have utilized Spare Labs´ simulation tool, "Realize," to simulate the effects of a large-scale implementation. The simulations are based on several data points, such as population, population density, and travel time ratios, but vary depending on the scenario. Furthermore, we make assessments of the adoption rate that each scenario is likely to achieve and the service´s efficiency based on the type of solution. All scenarios have been simulated using the following parameters, expected ridership, number of veicles, vehicle hours, efficiency, waiting time, pooling rate.