AI and computer vision enthusiast Melanie Leah Johnson shares the most compelling secrets behind self-driving cars for Women Love Tech.
Ever since their invention, vehicles have had an immense impact on human lives. The arrival of autonomous vehicles arguably has the most significant technological advance in the 21st century. As self-driving cars continue to progress, the number of automated vehicles increases. Recent advancements in computer science, mechanical engineering, and software programming are swiftly facilitating self-driving cars to become a reality. Computer vision is one of the main contributing factors, in that context.
How autonomous vehicles change the world
With the potential to significantly impact our daily routine, autonomous vehicles hold countless possibilities. Advanced Driver-Assistance Systems (ADAS) contribute essential safety functions such as automatic braking, steering assistance, pre-collision warnings, eliminating the need for a driver.
Chances of accidents are lower with competent technology sensors. It heavily influences transport-related sectors such as automobile repair centres and insurance industries, impacting employability.
The development of autonomous vehicles and robotics share numerous technologies including image recognition, AI, remote advanced sensing, GPS. The same infrastructure could be a strong base for service centres, recharging stations, and communication network protocols. On top of transforming the autonomous vehicle industry, its growth has a profound value on social, economic, and environmental aspects.
5 secrets behind self-driving cars
Let’s take a look at some of the key components in autonomous vehicles:
Network infrastructure is the first and foremost factor that keeps different vehicles connected with each other. High-speed and stable communication connectivity between self-driving cars and cloud infrastructure safeguards signals to and from the vehicles more accurately and rapidly. Moreover, advanced technologies such as fibre and sensor networks, IoT devices, Wi-Fi, 5G connections make self-driving cars easy to navigate safely on roads.
The ability to sense and see other cars, obstacles, road signs, pedestrians, and animals is mandatory in the autonomous vehicle development cycle. This is made possible via various sensors and cameras. The most commonly known sensor technologies are cameras, ultrasound, radar, and radio antennas.
For a precise comprehension of where a particular car is in relation to objects, a position estimator collects sensory data. To process the data and make accurate decisions, a central processing unit (CPU) is required.
Levels of Autonomy
Adopted by the U.S. Department of Transportation, the Society of Automotive Engineers distinguishes 6 levels of driving automation, ranging from completely manual to completely autonomous.
|Level 0: No Driving Automation
|Complete manual control. Steering, acceleration, braking, etc. performed by the driver.
|Level 1: Driver Assistance
|The vehicle features a single automated system (for instance, it monitors speed through cruise control).
|Level 2: Partial Driving Automation
|Includes advanced driver assistance systems (ADAS). Steering and acceleration are performed by the vehicle. The driver can take command any time as well as monitor all tasks.
|Level 3: Conditional Driving Automation
|Environmental detection capabilities. The vehicle can perform most driving tasks, but driver override is needed.
|Level 4: High Driving Automation
|Under particular circumstances, the vehicle executes all driving tasks. Geofencing is required. Driver override is still an option.
|Level 5: Full Driving Automation
|Under all conditions, the vehicle carries out all driving tasks. Driver’s observation is not required.
While this adds up to the secret of self-driving cars, the promising future for autonomous vehicles is still at Level 2 because of security issues.
The transportation sector contributes heavily to all greenhouse gas emissions. Electric, solar-powered self-driving cars have major effects on these emissions.
However, self-driving itself improves the travelling experience, which may inspire commuters to move away from work, acknowledging they could be spending their time on something more important than driving.
For routine commutes, electric bus lines are non-polluting and silent. With technological advancements, their electric charging and solar-powered solutions are undergoing lots of upgrades in recent times. So, autonomous vehicles have tremendous prospects for transforming future mobility, especially towards better sustainability.
Improved Parking Issues
Self-driving cars now can execute numerous driving tasks in a particular structure, including automatic parking and highway pilot. This is all possible with computer vision in autonomous vehicles, which includes analyzing, processing, and understanding objects and at the end of it, producing accurate decisions based on them. The combination of algorithm-based software programming development and microprocessor advancement gives immense computing power at a better price for consumers.
Pros & Cons of Autonomous Vehicles
|Decrease human error — With the help of computer vision, self-driving vehicles significantly enhance road safety by decreasing human error.
|Security issue — Communicating protocols in vehicles are relatively more vulnerable to the threats and potential of hacking.
|Prevention of accidents — Approximately, 90% of self-driving cars can prevent accidents.
|Initial costs — While autonomous vehicles help to achieve long-term goals, their initial costs are quite expensive. Of course, as technology progresses, costs should come down.
|The better mode of transportation — For people who cannot or choose not to drive, self-driving public transportation could be a better option.
|Machine error — These cars still have a flawed ability to make decisions between various unfavourable outcomes.
|Disabled friendly — Autonomous vehicles stand for comfort, freedom, and less dependence on others.
|Accidents — At times, machine malfunctions put customers’ lives at risk.
|Traffic efficiency — With the technological ability to communicate in real-time, self-driving cars improve travel to optimized distances from each other, reducing traffic jams.
|Weather dependent — Harsh weather interferes with self-driving cars’ effectiveness. For instance, cameras and parking sensors are hard to navigate and are less effective in the snow.
The road to fully autonomous vehicles leads to a bright future ahead. It is already becoming part of our daily routine.
Most of the impacts are driven by the acceptance factor of autonomous vehicle technology. As customers’ trust in the system improves along with the security and reliability of the system, a collaboration between various disciplines becomes essential to lead this new technology.