All of us have heard of the term Auto Pilot, But have we ever thought of the idea of an Auto Driver?
Ya, we may have technically come across this term, but here I will not say about a driver who operates the 3-wheeler vehicle on Indian roads as one of the cheapest forms of public transport, but a technology that can operate all transport vehicles without a so-called driver.
Google Transport System, or Apple Transport System? Sounds Creepy right?
Sounds crazy? I too thought that at first, like 20 year ago no one imagined about an Android device on our palms, that will change our day to day life today. Can you imagine a life in this lockdown, without your smartphone? How much life would have been different? Similarly, these driverless Transport Systems can also bring in revolution in the coming 20 years.
Without wasting any further time, giving an introduction, and increasing the suspense, lets directly come to the point of topic about which I am bragging all these times.
An automated-driving Transport System is a vehicle that uses a combination of sensor, camera, radar and artificial intelligence (AI) to travel between destinations without a human operator. To qualify as fully autonomous, a vehicle must be able to navigate without human intervention to a predetermined destination over roads that have not been adapted for its use.
How automated-driving Transport Systems work
AI technologies power automated-driving Transport System systems. Developers of automated-driving Transport Systems use vast amounts of data from image recognition systems, along with machine learning and neural networks, to build systems that can drive autonomously.
The neural networks identify patterns in the data, which is fed to the machine learning algorithms. That data includes images from camera on automated-driving Transport Systems from which the neural network learns to identify traffic lights, trees, curbs, pedestrians, street signs and other parts of any given driving environment.
For example, Google's automated-driving Transport System project, called Waymo, uses a mix of sensor, Lidar (light detection and ranging -- a technology similar to radar) and camera and combines all of the data those systems generate to identify everything around the vehicle and predict what those objects might do next. This happens in fractions of a second. Maturity is important for these systems.
The following outlines how Google Waymo vehicles work:
The driver (or passenger) sets a destination. The Transport System's software calculates a route.
A rotating, roof-mounted Lidar sensor monitors a 60-meter range around the car and creates a dynamic three-dimensional (3D) map of the car's current environment.
A sensor on the left rear wheel monitors sideways movement to detect the Transport System's position relative to the 3D map.
Radar systems in the front and rear bumpers calculate distances to obstacles.
AI software in the Transport System is connected to all the sensor and collects input from Google Street View and video camera inside the Transport System.
The AI simulates human perceptual and decision-making processes using deep learning and controls actions in driver control systems, such as steering and brakes.
The Transport System's software consults Google Maps for advance notice of things like landmarks, traffic signs and lights.
An override function is available to enable a human to take control of the vehicle.
Transport Systems with automated-driving features
Google's Waymo project is an example of a automated-driving Transport System that is almost entirely autonomous. It still requires a human driver to be present but only to override the system when necessary. It is not automated-driving in the purest sense, but it can drive itself in ideal conditions. It has a high level of autonomy. Many of the Transport Systems available to consumers today have a lower level of autonomy but still have some automated-driving features. The automated-driving features that are available in many productions Transport Systems as of 2019 include the following:
Hands-free steering centers the Transport System without the driver's hands on the wheel. The driver is still required to pay attention.
Adaptive cruise control (ACC) down to a stop automatically maintains a selectable distance between the driver's Transport System and the Transport System in front.
Lane-centering steering intervenes when the driver crosses lane markings by automatically nudging the vehicle toward the opposite lane marking.
Levels of autonomy in automated-driving Transport Systems
Level 1: An advanced driver assistance system (ADAS) aid the human driver with steering, braking or accelerating, though not simultaneously. An ADAS includes rearview camera and features like a vibrating seat warning to alert drivers when they drift out of the traveling lane.
Level 2: An ADAS that can steer and either brake or accelerate simultaneously while the driver remains fully aware behind the wheel and continues to act as the driver.
Level 3: An automated driving system (ADS) can perform all driving tasks under certain circumstances, such as parking the Transport System. In these circumstances, the human driver must be ready to retake control and is still required to be the main driver of the vehicle./p>
Level 4: An ADS can perform all driving tasks and monitor the driving environment in certain circumstances. In those circumstances, the ADS is reliable enough that the human driver needn't pay attention.
Level 5: The vehicle's ADS acts as a virtual chauffeur and does all the driving in all circumstances. The human occupants are passengers and are never expected to drive the vehicle.
Uses
As of 2019, Transport System makers have reached Level 4. Manufacturers must clear a variety of technological milestones, and several important issues must be addressed before fully autonomous vehicles can be purchased and used on public roads in the United States. Even though Transport Systems with Level 4 autonomy aren't available for public consumption, they are in used in other ways.
For example, Google's Waymo partnered with Lyft to offer a fully autonomous commercial ride-sharing service called Waymo One. Riders can hail an automated-driving Transport System to bring them to their destination and provide feedback to Waymo. The Transport Systems still include a safety driver in case the ADS need to be overridden. The service is only available in the Metro Phoenix area as of late 2019 but is looking to expand to cities in Florida and California.
Autonomous street-sweeping vehicles are also being produced in China's Hunan province, meeting the Level 4 requirements for independently navigating a familiar environment with limited novel situations.
Projections from manufacturers vary on when Level 4 and 5 vehicles will be widely available. Ford and Volvo both project a 2021 release of a Level 4 vehicle for public consumption. Tesla CEO Elon Musk, being a pioneer of both automated-driving and electric Transport Systems, has claimed that his company will have Level 5 vehicles ready as early as 2020. A successful Level 5 Transport System must be able to react to novel driving situations as well or better than a human can.
Source/reference(if any):internet