A multi-player simulation tool for interaction between vulnerable road users and automated vehicles
Reference number | |
Coordinator | Statens Väg- & Transportforskningsinstitut - Statens väg- och transportforskningsinstitut, LINKÖPING |
Funding from Vinnova | SEK 500 000 |
Project duration | July 2019 - March 2021 |
Status | Completed |
Venture | Electronics, software and communication - FFI |
Call | 2018-03501-en |
End-of-project report | 2018-05016sv.pdf(pdf, 536 kB) (In Swedish) |
Important results from the project
The aim of the project has been to develop a number of enabling tools for co-simulation with several actors, as well as a reusable environment with many areas of use. The goal was to create a useful simulation environment of the part of Vallastaden in Linköping that is currently operated by a self-driving bus in a pilot project. En Co-simulation architecture was developed and tested by simultaneously connecting 7 different actors and conducting a simulation with interaction between e.g. pedestrians, self-driving vehicles, truck simulator and additional simulated traffic.
Expected long term effects
Tools for both the creation of digital twins for driving simulation purposes, as well as a useful co-simulation architecture have been developed and successfully demonstrated. The developed methods will be used in future R&D project at Scania and VTI. Furthermore, the developed model of the University area in Linköping with a self-driving bus will be a useful tool for future studies of interaction between road users of various types and self-driving vehicles. Such studies will be important in order to introduce safe self-driving vehicles.
Approach and implementation
Development of tools to convert geodata into an environment useful for driving simulation Apply the tools on the relevant area and create reusable environment Develop the possibility of conducting co-simulation with several human-controlled actors in a connected Virtual Reality- (VR) and driving simulator Demonstrate a scenario Define a useful scenario to study the interaction between vulnerable road users and self-driving vehicles. The main method was software development. The last point used an internal workshop with traffic researchers.