one stretch of road or throughout one day

alfanita (18)in #news • 4 years ago

On top of atmospheric challenges, winter also provides road-level ones. Snow comes in many forms — it can be fresh and loose or hard and compact. It can appear harmless to the eye but be hiding treacherous ice beneath it. Snow conditions can change along one stretch of road or throughout one day. To guarantee a safe driving experience, our self-driving system must be able to adapt to these different road conditions.

The key to this is the friction coefficient between the road and the car’s tires. This coefficient is automatically determined by our self-driving system and impacts all of the car’s decision-making. For example, it allows the system to determine how quickly it can accelerate based on road conditions, and thus it can make a proper decision regarding changing lanes — whether to switch right away or wait until a better time. It also has a role to play in braking, constantly determining the safe distance from the car in front and also evaluating the right time to start braking before traffic lights.

Other important decisions, such as maneuver trajectories or maximum safe speed, also depend on weather conditions. Getting all of these details right not only ensures a safe journey in tricky weather conditions but also guarantees a more pleasant and comfortable experience for passengers and other drivers around our cars. This is particularly important when driving in dense urban traffic. Below, we have shared a video showing one of our many autonomous trips along Moscow’s snow-covered roads.

We apologize for the irritating windscreen wipers, but the snow was so heavy that our test driver couldn’t see without them.

Localization

Heavy snowfall can change the landscape beyond recognition. It obscures road markings, and sometimes even the boundaries of the road. On some streets, particularly those used to store snow cleared from the roads, snowdrifts can be the size of buildings. This winter, our localisation technology has proven its robustness and reliability.

Our automated, self-updating maps system enabled us to adapt in real-time to changes in the city. Even before our maps are updated, our driverless cars continue to localize themselves and navigate seamlessly through the streets. Thanks to our sensor fusion technology’s ability to combine data from lidars, inertial measurement units, and odometry, our vehicles are able to localize themselves even in situations where the car slips or skids. The pictures below show a snow storage street both before and after heavy snowfall.

There are a large number of hazards that also don’t just disappear in the winter. In fact, they sometimes become more complicated during winter weather conditions. For example, there is usually a significant increase during the winter months in the use of road maintenance equipment. In addition, snowdrifts narrow the streets, resulting in fewer available parking spaces. This increases the number of illegally double-parked cars, which makes it very difficult to keep normal traffic flowing. This increases traffic jams and incidents of dangerous driving as impatient drivers try to avoid them by moving into the oncoming lane. We can’t forget about pedestrians either. On particularly cold days, they love to take shortcuts to get home or to the office quicker. These shortcuts usually involve crossing in the middle of the road, rather than using designated crosswalks. Take a look at a typical city center journey after a heavy snowfall.

Our aim is to create a universal self-driving technology that can be safely used in different cities and countries around the world. We cannot achieve this without testing this technology in varying and challenging weather conditions. Moscow has a harsh seasonal climate and experiences a range of difficult weather conditions throughout the year. By testing our system here, we are giving it the tools to work in regions across the world, regardless of the climate.

4 years ago in #news by alfanita (18)

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