  A unified system integrating a compact object detector and a surrounding
environmental condition classifier for enhancing the robustness of object
detection scheme in advanced driver assistance systems (ADAS) is proposed in
this paper. ADAS are invented to improve traffic safety and effectiveness in
autonomous driving systems where object detection plays an extremely important
role. However, modern object detectors integrated in ADAS are still unstable
due to high latency and the variation of the environmental contexts in the
deployment phase. Our system is proposed to address the aforementioned
problems. The proposed system includes two main components: (1) a compact
one-stage object detector which is expected to be able to perform at a
comparable accuracy compared to state-of-the-art object detectors, and (2) an
environmental condition detector that helps to send a warning signal to the
cloud in case the self-driving car needs human actions due to the significance
of the situation. The empirical results prove the reliability and the
scalability of the proposed system to realistic scenarios.
