We discuss an early version of an open-source autonomous vehicle simulation framework whereby piloting control programs (PCPs) and vehicle response can be evaluated and improved in a safe environment. Through the interaction of hundreds of autonomous and avatar agents in a simulated environment, edge cases for self-driving vehicles can be analyzed thus accelerating research, development and technology deployment. The Connected Autonomous Vehicle Emulator (CAVE) builds upon four foundational components: (i) physics engine and dynamic vehicle support using Chrono and Chrono::Vehicle; (ii) virtual sensors support to provide self-driving algorithms with realistic data; (iii) multi-agent and vehicle-to-vehicle simulated communication support through a fast, low-latency server-client model; and, (iv) virtual environment for both physics and sensing to support edge cases for self-driving vehicles where physical testing is not feasible, including varying environmental conditions such as snow, rain, or fog.

This content is only available via PDF.
You do not currently have access to this content.