Torc’s autonomous trucks, like self-driving cars, are powered by a combination of algorithms, sensors, artificial intelligence, and so much more. Each individual piece plays a key role in operating our self-driving systems, but none are greater than the sum of their parts. These elements work in harmony to perform successful driving behaviors, especially where inclement weather is concerned.
How does weather affect self-driving vehicles?
Let’s think about our sensor suite as a “panel of experts” in their fields. Whether it’s research or execution, each expert is highly trained in their specialization. In any given scenario, they can problem solve and offer solutions with their years of knowledge behind them.
On this panel of autonomous trucking “experts”, we’d have a few different specialists: LiDAR, cameras, radar, and more. In an inclement weather situation, each would chime in with their unique perspective, but the decision would ultimately be made by the collective.
Let’s say our autonomous 18-wheeler is heading down a stretch of highway when a cloud of fog rolls in. As the fog overtakes the truck, the panel of self-driving sensors confers to figure out the vehicle’s next steps.
With high levels of fog, the visibility is low as the visual contrast isn’t significant enough for cameras to make a clear distinction between obstacle and air. Therefore, if the cameras on a self-driving vehicle were acting alone, they may decide that the best course of action is to slow down or pull over if the weather is significant enough.
At the same time, LiDAR, which works via bouncing laser beams off surrounding objects, might be sensing a wall of gray rather than a weather occurrence. This technology works so well at detecting its surroundings that it is thought of as a key piece in future lunar landings, but as with all technology, it can’t overcome physics and may draw some false positives and negatives from its surroundings. Acting alone, LiDAR may suggest slowing down so that it has an extended amount of time to deduce what’s happening around it.
However, radar has a different outlook altogether. Radar technology transmits radio waves, which aren’t affected by weather. Therefore, thick fog isn’t as much of a challenge. Radar’s drawback is that it only captures part of the image of the road around a self-driving 18-wheeler. As an expert panelist, radar may suggest that the truck is good to move forward slowly and with caution.
Before making a decision on what driving behaviors the truck should perform, the sensors work together to offer data on a given scenario. In our heavy fog scenario, each sensor said that visibility was low; radar tells us that it can confirm the fragments of images that LiDAR and cameras are able to provide, therefore giving us a complete picture. Each component plays off the other’s strengths and weaknesses, allowing the software to be the tie-breaker of our board of experts. When navigating significant weather, teamwork amongst these technologies is what moves self-driving vehicles from one stretch of highway to the next.
Self-driving vehicles are designed to be safe in a variety of weather conditions, but just like human drivers, their performance can be affected by bad weather such as rain, snow, fog, and extreme temperatures.
Can self-driving cars drive in snow?
Self-driving cars and automated semi-trucks can drive in snow, but their ability to do so depends on a number of factors, including the technology used, the amount and type of snow, and the driving conditions.
In general, snow can present challenges for driverless trucks and self-driving vehicles as a whole, as it can obscure lane markings, affect the performance of sensors, and make it difficult to detect and avoid obstacles. To address these challenges, automated trucking companies like Torc are developing more advanced algorithms that can better handle snowy conditions. In tandem, sensor manufacturers are also putting in the work to develop hardware that can handle the winter months.
For example, LiDAR sensors with higher power output and multiple wavelengths can help to better penetrate snow and ice and detect objects. Similarly, cameras with specialized lenses or coatings can help to reduce the impact of snowflakes or ice buildup.
In addition to technological advancements, automated vehicles may also rely on other strategies to navigate in snowy conditions. At Torc, our self-driving semi-trucks use map data and GPS to more accurately track their location and position on the road. Torc trucks also use radar, which allows us to further detect objects even in wintry weather.
Overall, while driving in snow can present challenges for autonomous trucks, the technology is rapidly evolving, and self-driving vehicles are becoming better equipped to handle a range of weather and driving conditions.
Will self-driving vehicles be safe in bad weather?
Yes. Self-driving vehicles are designed to be safe in a variety of weather conditions, but just like human drivers, their performance can be affected by bad weather such as rain, snow, fog, and extreme temperatures.
To ensure safety in bad weather conditions, self-driving truck companies are developing advanced sensors, algorithms, and safety protocols that can handle a range of weather conditions. For example, as mentioned, LiDAR sensors and cameras are being designed with specialized lenses or coatings that can better penetrate fog or rain, while radar sensors can be used to detect objects even in low-visibility conditions.
In addition, today’s consumer cars are being equipped with safety features such as adaptive cruise control, automatic emergency braking, and lane-departure warning systems that can help to prevent accidents in bad weather conditions.
However, it’s important to note that automated vehicles and driverless trucks may still have limitations in certain weather conditions, and in some cases, they may need to rely on human intervention or be programmed to avoid driving in certain conditions altogether. Just like human drivers may make the determination that roads aren’t safe to travel, the same will be determined by autonomous trucking technology. For example, in severe snowstorms, robotic trucks may need to autonomously pull to the side of the road, be re-routed, or even manually taken off the road if they are unable to navigate safely.
Overall, while automated semi-trucks and cars are being designed to be safe in a variety of weather conditions, their safety is still subject to ongoing testing, development, and regulatory oversight to ensure they can perform reliably in all conditions.
Can self-driving vehicles navigate weather?
Snow and rain are hot topics when it comes to automated cars and self-driving semi-trucks. Thankfully, sensor redundancy ensures that driverless vehicles can operate within a certain degree of extreme weather. In the same vein, the majority of shipping in the United States comes through places like Laredo, TX, making the sunny parts of the United States an ideal scenario for an initial launch of self-driving semi-trucks.
At Torc, we’re currently working towards an autonomous trucking solution that can overcome weather conditions on its long-haul journey across the country. Whether it’s rain, sleet, or snow, Torc’s software team is creating a product that will improve our shipping landscape.