Research in robotics technology started in early 60s, and the first self-sufficient and autonomous cars appeared in the 1980s at Carnegie Mellon University. Automation and Robotics Technology have gone through a lot of evolution in the last few decades. In recent years, digital technology has enabled the trial testing of autonomous vehicles. This led to the development of autonomous vehicles that were researched by Defense Advanced Research Projects Agency (DARPA).
The Five Different Levels of Autonomous Technology
Autonomous vehicle technology conducted tests on a range of prototype vehicles.
Level 0 (No Automation)
The driver is in complete control of braking, steering, throttle and power at all times.
Level 1 (Function-Specific Automation)
One or more specific control functions, such as electronic stability control or vehicle-assisted braking, operate automatically.
Level 2 (Combined-Function Automation)
At least two primary control operations, designed to work in unison to relieve the driver of control of those functions, operate autonomously. These combined functions might include adaptive cruise control in combination with lane centering.
Level 3 (Limited Self-Driving Automation)
Vehicles at this level enable the driver to cede full control of all safety-critical functions under certain traffic or environmental conditions. The vehicle monitors changes in those conditions requiring transition back to driver control. The driver is expected to be available for occasional control, but with sufficiently comfortable transition time.
Level 4 (Full Self-Driving Automation)
The vehicle is designed to perform all safety-critical driving functions and monitor roadway conditions for an entire trip. Such a design anticipates that the driver will provide destination or navigation input, but is not expected to be available for control at any time during the trip. This includes both occupied and unoccupied vehicles.
Driven by Technology
Autonomous vehicles use varieties of techniques to detect their surroundings, such as radar, laser light, GPS, odometry, and computer vision. Advanced control systems interpret sensory information to identify appropriate navigation paths, as well as obstacles and relevant signage.
Autonomous vehicles have control systems that are capable to analysing sensory data to distinguish between different cars on the road, which is very useful in planning a path to the desired destination.
1. The “driver” sets a destination. The vehicles’ software calculates a route and starts the car on its way.
2. A rotating, roof-mounted LIDAR (Light Detection and Ranging)- sensor monitors a 60-meter range around the car and creates a dynamic 3-D map of the car’s current environment.
3. A sensor on the left rear wheel monitors sideways movement to detect the car’s position relative to the 3-D map.
4. Radar systems in the front and rear bumpers calculate distances to obstacles.
5. Artificial intelligence (AI) software in the car is connected to all the sensors and has input from Google Street View and video cameras inside the car.
6. The AI simulates human perceptual and decision-making processes and controls actions in driver-control systems such as steering and brakes.
7. The car’s software consults Mapping System for advance notice of things like landmarks and traffic signs and lights.
8. An override function is available to allow a human to take control of the vehicle.
Robot cars are also known as autonomous cars, self-driving cars, robot cars, or driverless cars. It is a type of autonomous driving vehicle that can perform the function of a human-operated vehicle on its own. Likewise, it has the capacity to sense its environment and navigate on its own. All that a human need to do is simply choose the destination of the vehicle and perform mechanical operations and repairs.
Impact on Autonomous Trucking in Logistics Transportation
Perhaps the best way to understand the technologies that are already being implemented in the trucking industry, and how they will transform the industry’s stakeholders, are to break them down into two primary areas: Truck itself and the Logistics Chain.
Autonomous vehicles may have not yet achieved the mass-market appeal, they have presented several advantages that have been noted for their efficiency and desirability:
1. Fewer crashes. Robot trucks have autonomous systems that have better reliability than human drivers.
2. Better roadway capacity and reduced traffic congestion. Autonomous trucks have a reduced need for safety gaps, such as platooning while they have the capacity to manage better traffic flow.
3. Optimized road experience. Robot trucks could detect how to reach a destination the fastest way, taking into consideration the traffic congestion.
4. Lower fuel consumption and gas emission. Robot trucks are eco-friendly and they are better in managing traffic flow by removing safety features.
5. Convenience. Because robot trucks are autonomous, they do not require occupants to endure the inconvenience of driving and navigation. Thus, occupants are relieved from the constraints associated with driving. Also, issues regarding age, suitability and disabilities are eliminated with robot cars.
6. Elimination for parking scarcity. Robot trucks could, park anywhere space is available, and return when the need for the vehicle is needed. This also means reduced space needed for parking as well as the costs and inconvenience of hiring drivers.
7. Reduced need for road signage. Robot trucks could receive important communications electronically, thus minimizing the need for physical signs and line markings.
8. State-of-the-art facilities like no other. Robot trucks are equipped with the most state-of-the-art equipment and facilities that most traditional vehicles don’t have including laser, radar, LIDAR, GPS and computer vision. Robot trucks have the most modern control systems that interpret the information to determine the necessary navigation paths, obstacles and relevant signage. Robot trucks also update their maps depending on the sensory input, allowing them to navigate even in the most unknown environments.
The radical transformation of autonomous trucking coming to logistics industries over the next 10 or 15 years presents many risks but also opportunities for all the players in the business. For some, the risks will be so great that they will likely not survive. For others, success will depend on their ability to understand the opportunities available to them, and to build or buy the capabilities needed to aggressively pursue them. The real risk lies in failing to move forward in technology changes.