AI-generated summary
AI applications in mobility hold great promise, though they remain in early stages, particularly in the implementation of autonomous vehicles in urban settings. According to expert Raúl Rojas, the future of transportation is closely tied to mobile phones, which will play a central role. Before fully autonomous cars become widespread, technological advancements such as highway curve stability programs—referred to as “technological copilots”—will emerge as important transitional tools to enhance driver safety and vehicle performance.
Designers and manufacturers of autonomous vehicles face complex challenges, especially when integrating numerous sensors, cameras, and radars. These challenges intensify when autonomous vehicles must interact with human-driven cars, requiring systems to adopt “swarm behavior.” This approach involves not only processing environmental data from maps and sensors but also anticipating and adapting to the behavior of surrounding drivers. Beyond land mobility, AI is increasingly critical in sea and air transport. The rise of drones with diverse applications—from rescue missions to goods delivery—is driven by AI and big data technologies. While many AI-powered mobility applications are already operational, their widespread deployment and integration into everyday life will require additional years of development and refinement.
The role of AI in mobility is still emerging, but it already collaborates in its implementation in automatic cars and drones.
AI applications to mobility are truly promising, even though they are still emerging, barely taking their first steps into the implementation of autonomous vehicles across cities.
Our expert Raúl Rojas believes that the future–already present–of transportation will be mobile phones. But before the deployment of the autonomous car we will see the development of the technological copilot, such as curve stability programs on highways.
Autonomous vehicle designers and manufacturers have complex challenges ahead of them, particularly in the development of autonomous vehicles that have all sorts of sensors, cameras and radars. the situation changes when AI is used in a context in which the autonomous car is surrounded by other cars with human drivers. That is why they’ve started to develop what they call “swarm behavior”, which entails not only checking the map and the sensors, but also the behavior of the rest of the drivers in order to adapt to it.
These problems are ground-related, but there are different challenges for sea and air mobility. We see an increasing number of drones, different types with different functions, ranging from rescue to the transportation of goods and all kinds of products. All these applications are already here, and they would not be possible without AI and big data. Notwithstanding, its large-scale implementation and deployment will still take a few more years.
Professor of AI at Freie Universität
