Automated and Connected Driving: Core Challenges and Functions

The transition to fully autonomous and connected vehicles is reshaping modern transportation, but it requires solving complex engineering hurdles. Understanding how vehicles perceive their surroundings, communicate with infrastructure, and make decisions is essential for any aspiring automotive specialist. This text-based course guides you through the core concepts, architectures, and design challenges of automated driving. You will gain a solid foundation in how vehicles process sensor data, coordinate with other road users, and maintain safety in complex environments. What you'll learn: Understand the key levels of vehicle automation and the fundamental architecture of connected driving systems; Analyze sensor technologies including radar, lidar, and cameras, along with modern sensor fusion concepts; Explore vehicle-to-everything (V2X) communication protocols and how they improve cooperative driving strategies; Study safety-critical design principles, incorporating standards like ISO 26262 and SOTIF (Safety of the Intended Functionality); Examine path planning and decision-making algorithms used by vehicles to navigate real-world scenarios. The course starts with essential terminology and structural overviews of automated vehicles before moving on to sensor integration, V2X networking, and path-planning logic. You will progress through written case studies and conceptual design exercises that reinforce practical safety and testing methodologies. This course is designed for beginners, engineering students, and technology enthusiasts who want to enter the autonomous vehicle space, with no prior background in automotive hardware required. Start reading today to build your foundational knowledge of autonomous vehicle technology.