Infrastructure Assisted Cooperative Driving Strategy for Connected Vehicles (ACDC)

Connected and Automated Driving (CAD) aims to provide innovative services that enable vehicles to be better informed about their surroundings and make faster, more accurate decisions in critical situations, thus reducing road casualties. Vehicle-to-Everything (V2X) communication facilitates CAD, allowing vehicles to communicate with each other. V2X has evolved rapidly over the past few years, offering promising applications ranging from the enhancement of road safety to increased comfort. One of these applications is the cooperative perception system (CPS), where vehicles and roadside infrastructures exchange sensory information using the V2X network to maximize the perception horizon. V2X can be performed between participants in the CAD ecosystem for dynamic real-time information exchange. However, communicating perception sensor data requires a significant amount of network bandwidth. With the recent deployment of low-latency and high-throughput network technologies such as 5G in many metropolitan areas, sensor data sharing between vehicles, infrastructures, and beyond is becoming a realistic option. Hence, sensor data sharing could be the next key enabler for minimizing existing driving challenges while increasing the awareness horizon beyond local sensing capacities. Nevertheless, a CPS can also generate lots of redundant data, and data transmission comes at the cost of processing overhead. Therefore, any novel CPS applications must be tested to ensure their reliability. Trials on actual vehicles are uncommon due to the complexity, cost, and risks associated with the experiments. Simulation is an excellent alternative to address this issue, and the research community frequently relies on it. In this context, the simulation environments should be as realistic as possible and mimic the challenges of actual deployment. So far, no existing framework combines synthetic car sensor data with the realistic network simulation needed to evaluate CPS. This Ph.D. project, “Infrastructure-Assisted Cooperative Driving Strategy for Connected Vehicles (ACDC),” will focus on designing such a framework to validate CPS solutions and determine how sensor data could be efficiently shared between vehicles and infrastructures using V2X facilities through a realistic communication channel. We believe that such a platform will open many exciting research avenues. Another goal of the project is to explore novel distributed learning techniques to distribute sensor information processing among vehicles, infrastructures, and beyond, and to find the best trade-off between data processing and transmission policies while ensuring low latency and high reliability.