Autonomous cars, often referred to as self-driving vehicles, utilize a combination of sensors, cameras, and artificial intelligence to navigate and operate without human intervention. These vehicles are equipped with advanced technologies such as LIDAR (Light Detection and Ranging), radar, and GPS for real-time environmental mapping. The data collected from these sensors is processed through complex algorithms that allow the car to make decisions on the road, such as stopping at traffic signals, changing lanes, and avoiding obstacles. This intricate system is designed to enhance safety and efficiency, making driving more intuitive and less reliant on manual control.

At the core of autonomous driving technology lies machine learning, which enables the car to improve its performance by analyzing data from previous journeys. The artificial intelligence systems are trained using millions of miles of driving data, enabling the vehicle to recognize patterns and adapt to various driving conditions. Moreover, vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication further augment the car's awareness, allowing it to interact with other vehicles and surrounding infrastructure for enhanced safety and traffic management. As these technologies continue to evolve, the dream of fully autonomous transport appears increasingly within reach.

The landscape of transportation is rapidly evolving, and at the forefront of this change are autonomous vehicles. As technology advances, the prospect of self-driving cars transitioning from concept to reality is becoming increasingly achievable. This shift could revolutionize the way we commute, significantly reduce traffic accidents caused by human error, and enhance the efficiency of transportation systems. However, the question remains: are we truly ready for this leap into a future dominated by autonomous vehicles? It entails not only technological readiness but also societal acceptance and regulatory frameworks to govern their use.

To assess our readiness, we must consider several key factors:

1. Public Perception: How do consumers feel about sharing the road with self-driving cars?
2. Legal Frameworks: Are current laws capable of addressing the complexities introduced by autonomous driving?
3. Infrastructure Requirements: Do our roads and systems support the technological needs of autonomous vehicles?

The advent of autonomous cars is poised to revolutionize city planning and infrastructure in profound ways. As these self-driving vehicles become more prevalent, urban planners will need to reassess the design and functionality of roadways, parking structures, and public transportation systems. Traditional parking lots may become obsolete, allowing for the redevelopment of valuable urban land into green spaces or mixed-use facilities. By minimizing the need for extensive parking areas, cities can enhance their livability, promote sustainability, and create more pedestrian-friendly environments.

Moreover, autonomous vehicles could lead to a significant reduction in traffic congestion and accidents, impacting the overall layout of cities. With improved traffic flow and efficiency, planners may shift their focus towards developing smart infrastructure equipped with advanced technologies. For instance, integrated traffic management systems could be implemented to optimize transportation networks, reducing travel times and improving air quality. In conclusion, the rise of autonomous vehicles represents a paradigm shift in urban development, necessitating innovative approaches to adapt our cities for the future.