Impact Of Weather Conditions On Advanced Driver Assistance Systems (ADAS) A Systematic Review Of Sensor Limitations And Performance Degradation

Abstract

Advanced driver assistance systems(ADAS) increase vehicle safety and provide for semi-autonomous driving.
They help drivers in braking, steering, and in avoidance of collisions, among others. However, one of the factors
that determine the effectiveness and reliability of the system actually lies in a non-technical context, the influence
of external weather conditions. Several adverse weather conditions, including heavy rain, fog, snow, and full
sunshine, can affect the performance of critical ADAS capabilities like ACC, LKA, AEB, and BSD. All these
subsystems use a combination of sensor technologies: cameras, RADAR, LIDAR, and ultrasonic sensors, which
are exposed to interference from environmental characteristics. This review attempts to critically evaluate the
extant research about the influence of various kinds of adverse weather conditions on the operation of each of the
subsystems of ADAS. It discusses its limitations when individual sensors deteriorate with weather and highlights
the operational problems encountered by a real-world ADAS. Some of the extant strategies to overcome these
problems will also be discussed in detail, including sensor fusion techniques and adaptation of algorithms with
regard to changes in weather. Relevant research gaps to be outlined by this paper include inadequate all-round
weather testing of the existing body of knowledge, the need for stronger techniques of sensor calibration, and the
role of artificial intelligence in enhancing real-time adaptability. With these research gaps as its objectives, this
paper aims to shed light on the improvement of the reliability of ADAS, with an assurance of safe and steady
performance in any weather condition. These results will add to the continued development of stronger
autonomous driving systems, and ultimately push vehicle safety and automation to the limits