Distributed Simulation Platform for Autonomous Driving
This addresses the problem of high-cost and time-consuming testing for autonomous vehicle developers, though it is incremental as it builds on existing frameworks like Spark and ROS.
The authors tackled the need for efficient testing of autonomous driving algorithms by developing a distributed simulation platform using Spark and ROS, which enables scalable data playback to replace expensive real-world tests.
Autonomous vehicle safety and reliability are the paramount requirements when developing autonomous vehicles. These requirements are guaranteed by massive functional and performance tests. Conducting these tests on real vehicles is extremely expensive and time consuming, and thus it is imperative to develop a simulation platform to perform these tasks. For simulation, we can utilize the Robot Operating System (ROS) for data playback to test newly developed algorithms. However, due to the massive amount of simulation data, performing simulation on single machines is not practical. Hence, a high-performance distributed simulation platform is a critical piece in autonomous driving development. In this paper we present our experiences of building a production distributed autonomous driving simulation platform. This platform is built upon Spark distributed framework, for distributed computing management, and ROS, for data playback simulations.