While discussing the effects of whether in autonomous vehicle functioning it is considerable that even with the ongoing breakthroughs in the automotive sector, a significant obstacle to overcome is driving safely in bad weather. On-road visibility reduces by moving in less than ideal conditions, leaving your fleet vulnerable to potential accidents. We explore the question of autonomous vehicle safety and weather in this article. Although many promises and possibilities come with the future of autonomous technology. A lot of work still needs for self-driving cars to maneuver safely under harsh weather conditions.
Challenge as of The effects of Whether in Autonomous Vehicle Functioning
Using sensors such as cameras, light detection and ranging (LiDAR), millimeter-wave radar (MWR), and the global navigation satellite system, decisions must be taken during automatonomous driving in urban areas while recognizing the surrounding environment (GNSS).
An essential issue for automated driving on any road is the capacity to drive under different environmental conditions. The ability to assess the other traffic conditions and to navigate safely presents severe challenges to bring automated vehicles to market. The development of a robust recognition system that can account for adverse weather conditions is another crucial challenge. Adverse weather conditions in the driving environment include sun glare, rain, fog, and snow.
The Top four Challenges as The effects of Whether in Autonomous Vehicle Functioning
Here we are going to present the top four challenges as the effects of whether in autonomous vehicle functioning.
Water Buildup-The car must feel the puddle ahead, or better yet, measure how deep it is before or around it before driving. Alternatively, it also needs to consider the best route for reaching its destination during rainy conditions.
- Sensors- The primary sensory device in each vehicle is often LIDAR, a survey method. It does not always accurately feel that it is raining, which can interfere with the vehicle’s sensors.
- Slippery road conditions-According to the slippery conditions, the vehicle needs to change its “driving” capabilities. It is essential to take more care, including leaving enough space between cars, accelerating, and braking well in advance.
Hydroplaning-The vehicle needs to make a quick judgment call on the correct course of action, along with spatial awareness, before attempting to acquire or regain control.
While the future seems exciting, in conditions that frequently undergo a dramatic shift in temperature, the idea of autonomous cars cannot still be fully functioning. This is because early autonomous vehicles gets usually tests in places like California or Arizona that are sunny and dry.
Whether the effect on the future of Autonomous Vehicles
The new challenge for autonomous vehicles shortly, when autonomous vehicles and human drivers share the lane, will be to respond appropriately to pedestrians and drivers who alter their driving behavior during severe weather conditions.
Although this is not one of the the direct effects of whether in autonomous vehicle functioning but still considerable.
The demand for autonomous vehicles designed to drive in stricter weather conditions has increased. Enterprises are searching for ways to fill the gap. For example, one semiconductor maker chose Ontario as a testing area to test the efficiency of vehicles in colder weather.
The visible light camera of AV
The visible light camera is prone to poor weather such as fog and can hardly be seen at night without a light source. However, infrared cameras have a feature that allows them to penetrate through the fog and, since they can measure temperature, can observe pedestrians at night. Yet, because of an image sensor that can detect infrared rays, the infrared camera has a lower resolution than the visible light camera. The resolution of the onboard sensor’s infrared camera is around 1.3 megapixels. Visible light cameras are therefore primarily used, and the current use of infrared cameras is limited.
Importance of Sensors in all conditions
Therefore, it is necessary to consider the configuration of the sensor so that objects can be observed in all directions to avoid effects of whether in autonomous vehicle functioning. A robust device can be required to cover the observation area with several sensors to inspect critical areas. Furthermore, to make the right situational decisions, the automated driving device needs to process a vast amount of sensor information in real-time.
Since the automated vehicle uses onboard sensors to recognize its ambient environment and makes situational decisions based on the effects of the recognition, knowing the ground around the car and predicting how the conditions will change is critical. Furthermore, for the vehicle to behave smoothly in different traffic conditions, road features such as traffic lights need to be remembered.
Map Matching Technology as on The effects of Whether in Autonomous Vehicle Functioning
To estimate the vehicle’s location, map matching technology is used. Many studies have implemented a map matching technique between the reference digital map and sensor observations in self-localization to avoid the effects of whether in autonomous vehicle functioning. The reference map provides details on sensor features along roads with precise positions. Generally, three kinds of map structure are used as predefined maps (3D point cloud map, 2D image map, and vector structured map).
A cloud map of 3D points contains details about 3D objects around the road. Although the maintenance cost does not considers for this form of plan, the data size is enormous. By extracting road surface features from a 3D dot cloud, a 2D image map is created. As a consequence, in contrast with the 3D map, the data size is reduces. The vector map includes road and lane boundaries with polynomial curves, such as white lines and curbs. This is called a light guide in terms of data size. But it has a high maintenance cost. As infrared reflectance characteristics become unstable comparing it to non-rainfall, the effect on output during self-localization must also consider. Due to variations in the reflectance features obtained between the map and real-time observation. These false estimations occur in the map matching phase and make the effects of whether in autonomous vehicle functioning worse.
A travel strategy that complies with traffic laws is the second technology to overcome the effects of whether in autonomous vehicle functioning. When driving along the road, it is essential to obey the traffic rules. In particular, it is necessary to ensure a safe procedure, taking into account the traffic light status’s recognition results and the stop line location when making an entry decision at the intersection. On the zebra crossing, the positional relationship between the oncoming vehicle and pedestrians. When driving through a meeting, it is necessary to remember the priority connection between the current road and the destination road.