Snow, fog and blizzards practically make driving impossible in the US. Winters are getting worse with every year, thanks to the Climate Change. Driving in snow and fog is full of danger. According to a report, over 1300 people hundreds of thousands are wounded every year due to crashes and accidents caused by snow. Snow depletes friction on roads, and make it impossible for the cars to immediately halt on icy streets. There is already much skepticism on the level of trust that could be put in self-driving cars. How, then, will self-driving cars will handle snow?
3D Mapping on self driving cars
Mapping is the best defense of self-driving cars when it comes to hostile terrains. Autonomous cars use precise mapping techniques to pre-load the maps and terrains. They load the minute details like position of trees, weather, lines, curbs and curves. 3D Maps help the car’s sensors in detecting real-time obstacles like other cars, buildings and pedestrians. Many car companies are using LiDAR technology, which provides a great obstacle detection mechanism when combined with 3D maps. When an autonomous car has all the data and information of objects on and nearby road, it will adjust speeds and maneuvers accordingly.
Self-driving cars can detect snowflakes, ice on the roads, trees, signs and other obstacles by using the LIDAR technology, which is based on precise light emission. LiDAR technology takes data from 3D maps and compares the terrain and environment of a clear day with the current data. LiDAR technology can detect the real shapes and curves of roads even when all the surfaces are covered with snow. How? It uses the light emission detection mechanism, and it has all the data of roads preloaded in the maps. The problem in this technology, however, is that the car may take a snow flake or ice piece as an obstacle, which could result in the vehicle stopping. But there is a variable called “obstacle persistence”. If a small obstacle is too persistent, the car can be programmed to overlook it and pass over it, which should happen on snowy roads. Here is a video summing up Ford’s LiDAR technology to make driverless cars smart enough to drive in snow.
Some experts say that LiDAR technology can sometimes halt in snow because it works on light, and there are chances that LED reflection will not work in fog and snow. In case of LiDAR failure, self-driving cars have basic radar technology which works on electromagnetic waves. A radar can always detect moving objects, vehicles, buildings, pedestrians and snow. But in order for the autonomous cars to work well, they would have to be placed inside the car’s body or behind the windshield so that ice and rain may not block the wave production.
Cameras are quintessential in making an autonomous car vigilant and aware of its surroundings. Companies are putting cameras behind the vipers and windscreens so that they could get a clear view even in the times of rain and snow. Cameras work with LiDAR technology and radars to make the mapping stronger. It’s all about adding more equipment to decrease the risk factor. For example, one of Mercedes Benz’s car has over 23 sensors that detect guardrails, oncoming traffic and trees so that the vehicle can travel without lane lines.
Conventional Technology and Room for Improvement
Despite of all the technology-laden features in driverless cars, it is imperative that companies work on the strong tires and all-wheel drives, which are the traditional ways to tackle skids, spinouts and rear-end collisions which are caused by snow and ice on roads. There is a great room for improvement and research in this area, and giants working on driverless cars such as Tesla, Google, Ford and Fiat have a great responsibility in this realm to solve this critical problem.