Overview
The development of autonomous-driving systems necessitates the processing of substantial sensor data and the generation of vehicle-control commands within specific temporal constraints. Autonomous vehicles are increasingly defined by their software architecture, which often incorporates diverse software platforms, each possessing distinct characteristics. A cloud-based platform has been introduced to address the complexities inherent in these systems, specifically focusing on the identification and precise localization of delays.
Research Context
Autonomous-driving systems operate under stringent time limits for data processing and command generation. The increasing reliance on software to define vehicle functionalities leads to development environments that integrate multiple software platforms. These platforms can have varying operational characteristics, contributing to the challenge of managing system performance and timing.
Approach
The research involved the development of a cloud-based platform designed to pinpoint delays within autonomous-driving software. The platform's objective is to enable the identification and localization of these delays across complex software architectures.
Findings
The cloud-based platform developed is capable of pinpointing delays across complex autonomous-driving software. It facilitates the identification and localization of these delays.
Why This Matters
The ability to pinpoint and localize delays in autonomous-driving software is critical for ensuring that vehicle-control commands are generated within strict time limits. This capability is particularly relevant given the high volume of sensor data that these systems must process and the integration of multiple software platforms in their development.