LAUSR

Advanced Driver Assistance Systems (ADAS) are a collection of intelligent solutions integrated into next-generation vehicles to assist in safe driving. When building ADAS systems, the main goals are that they are stable, flexible, easy to maintain, and allow for error tracing. If a driving assistance algorithm is designed to be implemented on one machine or in one model, there is a potential disadvantage that if one component fails, then the entire system would stop. We work on modularizing the ADAS system to be flexible to accommodate any changes or improvements based on up-to-date requirements. Using advanced current edge (or network) devices, we propose a Detection-based Driving Assistance algorithm, which can collaborate or integrate with an existing system in a vehicle. The core of any process is to ensure that the system has a predictable level of functionality and that any misbehavior can be easily traced to the root cause. The proposed system shows fast, real-time performance on edge devices with limited computing power.