Final Report - Cooperative Automated Driving Use Cases for V2X Communication
One of the main challenges today on the way towards full traffic automation is the comprehensive environmental perception of its participants, which in turn can help to improve the safety and assistance in applications such as Advanced Driver Assistance Systems. In order to be able to assist the driver or even take decisions themselves, vehicles have to perceive their surroundings and detect possible dangers and hazards as precisely as possible. Most of the sensor systems often fall short when meeting the strict functional requirements imposed by such systems. Vehicle-to-Everything communication has emerged as a promising technology to mitigate this gap, allowing traffic participants to share information that help to increase their environmental perception and support their decision-making basis. Examples of Vehicle-to-Everything applications are cooperative awareness, collaborative positioning, and collective perception, allowing vehicles to share data about their own state, detected objects in their surroundings, among others.
With this in mind, this pre-study aims to answer the following central research question: What are the latency requirements for collective perception systems to enable Advanced Driver Assistance Systems function to fulfil the state-of-the-art safety norms in a realistic traffic use case? With the goal of solving the above question, the pre-study focusses on establishing a tool chain data-scenarios-simulation-requirements that help us to understand the needed pieces/shortcomings of the data and tools. Such a study would enable to set the requirement on latency of Vehicle-to-Everything communication systems based on safety requirement of Advanced Driver Assistance Systems functions. Halmstad University is the responsible for the pre-study and the co-production involve two parties, namely Viscando AB and Zenseact AB, that are interested on the achievement of the present pre-study.