Sehr interessanter Artikel über die wachsende Bedeutung von Videodaten für Verkehrslösungen.
One of the areas where video technology has the potential to drive significant impact is on safety behind the wheel. Video monitoring is already helping drivers track information about the exact time, speeds and position of vehicles during collisions to prevent future crashes. Additionally, the data garnered from AI-assisted monitoring can help to identify habits to improve driver behavior. And video will also play an increasingly important role in ensuring the safety of our roads as we start to see the rise of more intelligent transportation infrastructure.
The number of vehicles on the world’s roads is expected to double to over 2 billion in the next 20 years. Even with new roads, the increase in traffic will quickly exceed the ability of the world’s network of highways to cope in many urban areas. To reduce the environmental and congestion challenges this presents, both electric and autonomous vehicles (and electric autonomous vehicles) are expected to see significant growth in the coming decades.
New data suggests that by 2025, 25% of cars sold will have electric engines and there will be more than 11 million driverless vehicles operating on the roads globally by 2030. Twenty-nine states have already enacted legislation related to self-driving vehicles on state roads, according to the National Conference of State Legislatures, with other states set to follow.
Video data will be one of the most critical enablers of this new future of AI-driven autonomous vehicles. When it comes to autonomous driving, safety will be more important than ever. Video data from onboard cameras will act as the “eyes” of an autonomous vehicle. A combination of video, LIDAR and radar can analyze surroundings for situational awareness of pedestrians, bikes and of course other vehicles. Video data will also be important for the ongoing training and improvement of vehicle autonomy as AI-powered cars and trucks learn to react to different conditions and situations.