AutonomouS and Connected vehiclE Testing using Infrastructure Sensor Measurements

Purpose and goal

The goals of the Ascetism project are to - identify and deploy roadside sensor-based naturalistic data collection solution to collect a dataset for extraction of critical merging scenarios for AV development - model the behaviour of human actors in merging situations - demonstrate the concept of verification and validation toolchain of AVs using extracted merging scenarios and behaviour models - identify the gaps in the currently available data, such as quality and quantity and required improvements in data collection systems to enable scenario-based verification of AVs

Expected results and effects

The project is expected to lead to solutions for using output data from cameras placed in the traffic infrastructure to generate scenarios for testing primarily self-driving vehicles. In extension, it may be possible to use the camera information and scenarios when planning road structures, ramps, roundabouts and the like, adapted both for automated and mixed traffic.

Planned approach and implementation

Scenarios and driver behaviour models will be derived from recorded data and scrutinised for integration into simulation and test track testing. This project will attempt to answer the following research questions: - How can naturalistic data from infrastructure sensors be used in scenario-based verification and validation of autonomous vehicles? - How do data properties, such as location, quantity, accuracy, number of recorded interactions, influence quality of simulations?