5G for Connected Autonomous Vehicles in Complex Urban Environments

Important results from the project

The project´s objective was to explore methods for improving the motion planning and control of automated vehicles through information, by leveraging data collected from mobile devices of human road users, including pedestrians, cyclists and human drivers. The project has shown how such data can be used to build tools that predict the development of traffic around an autonomous vehicle and how such tools can be embedded in predictive motion planning algorithms.

Expected long term effects

In the long term, these project results could rekindle interest in connected autonomous vehicles.

Approach and implementation

The recruitment planned for this project (started in 2019) has been severely affected by the pandemic. The lack of available candidates for the planned postdocs and doctoral students has significantly delayed the planned activities. Such a delay has been partially compensated by Chalmers recruiting staff for the project and using them as natural resources. When the recruitment is completed, the project has delivered the expected results.