Co-simulation Platform for Developing InfoRich Energy-Efficient Connected and Automated Vehicles
This work addresses the difficulty of verifying energy-efficient CAVs for automotive researchers and engineers, though it is incremental as it builds on existing simulation methods.
The paper tackles the challenge of testing energy-efficient autonomous driving systems by developing a co-simulation platform called InfoRich, which integrates sensor data, V2X communications, and maps to evaluate eco-autonomous driving strategies under realistic scenarios.
With advances in sensing, computing, and communication technologies, Connected and Automated Vehicles (CAVs) are becoming feasible. The advent of CAVs presents new opportunities to improve the energy efficiency of individual vehicles. However, testing and verifying energy-efficient autonomous driving systems are difficult due to safety considerations and repeatability. In this paper, we present a co-simulation platform to develop and test novel vehicle eco-autonomous driving technologies named InfoRich, which incorporates the information from on-board sensors, V2X communications, and map database. The co-simulation platform includes eco-autonomous driving software, vehicle dynamics and powertrain (VD&PT) model, and a traffic environment simulator. Also, we utilize synthetic drive cycles derived from real-world driving data to test the strategies under realistic driving scenarios. To build road networks from the real-world driving data, we develop an Automated Parser and Calculator for Map/Scenario named AutoPASCAL. Overall, the simulation platform provides a realistic vehicle model, powertrain model, sensor model, traffic model, and road-network model to enable the evaluation of the energy efficiency of eco-autonomous driving.