# An Overview of Autonomous Vehicles Sensors and Their Vulnerability to Weather Conditions
## 5 Conclusions and Future Work  
Despite the ongoing advancements in automobile technology, one major challenge that has to be overcome is driving safely in severe weather. Driving under less-than-ideal circumstances reduces on-road visibility and impairs the functioning of AV sensors, rendering them vulnerable to possible accidents. Based on the findings, RADAR sensors seem to align with today's technology since they can operate beyond adverse weather conditions. The main drawback is that they still need the assistance of a perception system in order to improve decision robustness. LiDAR can be offset to perform in bad weather and, thus, it is still viable. Similarly to RADAR, it requires a perception companion. Cameras can lose their ability to decipher what it observes when lighting changes, weather is severe, or visibility is low. Lightning is a major problem and even obstructions such as dirt-caked signs and cameras will not always be reliable. On the other hand, LiDAR sensors appear to be more efficient for spacecraft missions, including location and docking, but not for autonomous vehicles. If there are intentions for acquiring active photon generators for automotive purposes, visible wavelength sensors will be useless, since the photon generator covers down to the optical wavelength, while low-cost radars can easily penetrate at incursion situations such as rain, fog, or snow. Numerical studies of a LiDAR sensor simulation tool show that new sensor models can simulate raw data provided by a laser scanner through the pulse laser propagation and energy losses under the weather condition. These attributions will contribute in reducing the cost and time to develop LiDAR applications and to increase performance of such systems. Self-driving vehicles can rely heavily on cameras to perceive the surrounding environment. Therefore, cameras are mostly used due to their low cost, high resolution, and their capability to differentiate between colors. Connecting two visible (VIS) cameras with a predetermined focal distance allows computer stereo vision to be performed; hence, a 3D representation of the scene around the vehicle is produced. However, even in a stereoscopic vision camera system, the estimated depth accuracy is lower than the one obtained from active range finders such as radars and lidars. Adverse weather conditions can impose challenges and create potential failures to AV sensors. However, with the assistance of satellite for monitoring, the existing infrastructure (e.g., traffic lights) and control centers via mobile devices will be essential for collision avoidance. As a result, prominent semiconductor firms are developing chips that will transform autonomous vehicles into mobile data centers, allowing driverless cars to make crucial decisions in real time. The paper's scope is an effort to summarize the weather effects on AV sensors, specifically on RADAR, LiDAR, and camera systems, but the discussion could be expanded. In addition to strategies for minimizing attenuation, the environmental impacts on AV technology, geography, sensor network topology, natural catastrophes, and interferences may be accounted for. What would be even more intriguing is the topic expansion of AV technology effects relative to the environment. Studies on these more expansive dialogues would then contribute to overall sensor information in AV. Although outdoor test environments are the most relevant schemes with high levels of sensor attenuation due to their unpredictable natures, there are additional applications. Scenarios with topology variation, natural disasters, emergencies, physical/internal interference, or lack of human aspects can also contribute to sensor attenuation. Conceptualization, J.V. and S.A.; methodology, J.V. and S.A.; investigation, J.V., S.A., O.T., and J.S. ; writing--original draft preparation, J.V., J.S., and S.A.; writing--review and editing, J.V., S.A., O.T., and R.R. ; supervision, J.V. and S.A. All authors have read and agreed to the published version of the manuscript.