Today, many cars already include several semi-autonomous characteristics, such as assisted parking. However, the next stage will be completely autonomous cars that can operate without human control, and they are quickly becoming a reality. In fact, Self-Driving Congress organizers say that autonomous driving cars are estimated to overtake conventional vehicles within the next decade.
Around the world, there are start-ups, automakers, and companies such as Google and Uber that are diligently working on generating and utilizing the technological advances that are necessary for the next generation of autonomous cars.
The technology required for autonomous cars can be divided into three technologies: sensors, connectivity, and software/control algorithms. To learn more, read on for the key technologies used in autonomous cars.
1. Sensors and Cameras
Located at the front and around the car, onboard cameras and sensors can accumulate enormous volumes of data processed in real time to ensure the vehicle travels in the appropriate lane and moves safely.
One of the benefits of autonomous cars is that the sensors are continually observing and, therefore, are not influenced by the condition of the driver (sleepy, angry, intoxicated). Additionally, they can conduct scans in multiple directions at the same time.
This is one of the main reasons that autonomous cars are set to transform safety on the road (94 percent of accidents are a result of human error). The effect of this technology will potentially be extensive, including decreased demand on emergency response systems and diminished auto insurance and healthcare costs.
At this point, the majority of sensors that are needed for autonomous cars are accessible today and are already used in many vehicles for features such as blind-spot monitoring, lane-keep assistance, and forward-collision warning. Additional sensors for features like radar, ultrasonics, and cameras render the information necessary to steer the car reliably and safely.
Moreover, ultimately, road signs, traffic lights, and lane markers will be able to interact with sensors in the vehicle.
Connectivity technology allows the car to stay up-to-date with the latest traffic, weather, maps, and nearby vehicles. When compiled together, this data monitors a car’s surrounding operating environment and can foretell the need to brake or to circumvent hazardous conditions.
The local data processors contain software that automatically produces real-time calculations, which facilitate rapid decision-making on the road, while the high-performance, satellite-based global positioning system (GPS) tracks the vehicle’s position and leads it to its final destination.
Furthermore, object detection systems utilize radio waves to ascertain the proximity, range, angle, and speed of surrounding objects.
Connectivity to the Internet of Things (IoT) is essential for autonomous cars as onboard systems facilitate machine-to-machine communications to learn from and communicate with other vehicles, while also adapting to weather developments and changing road conditions (like detours and in-path debris).
Cloud-based data processing and management tools aggregate and interpret real-time telemetric data (for example, vehicle speed and surrounding car proximity) and, therefore, can indicate the necessity for actions such as braking or lane-switching.
3. Software/Control Algorithms
It is the responsibility of the software and control algorithms to dependably take the data from the sensors and connectivity components and make judgments on the next actions. This is, of course, the most complicated element of autonomous cars, as the algorithms must be capable of commanding an abundance of uncomplicated and intricate driving conditions with no mistake.
Artificial intelligence (AI) continuously enhances vehicle performance without the need for reprogramming, supported by continuous software updates and the latest algorithms through the cloud. Connected to all the rest of the technologies, the advanced algorithms and deep learning systems of AI permit the vehicle to promptly and automatically adjust to shifting conditions.
Light detection and ranging technology (LIDAR) senses brake lights and changing road situations and uses light instead of radio waves. Industry giant, Google, is utilizing LIDAR in its development of autonomous cars.
These are the three main technological components of autonomous cars. Which technologies are the most interesting to you?
Are you excited about the continuing development of autonomous cars?
Ahmed Bahrozyan is the Chief Executive Officer of the Public Transport Agency - Roads and Transport Authority in the United Arab Emirates which is responsible for providing for the needs of public transport in the city. He is also Chairperson of the Dubai World Congress for Self-Driving Transport organizing committee.
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