Autonomous or self-driving cars can revolutionize and
transform transportation as the world knows it. These vehicles utilize
cutting-edge technologies to navigate and operate without human intervention,
opening new possibilities and raising intriguing questions about the future of
transportation.
Read below to know more about how autonomous vehicles came
to be and their future.
The Evolution of Autonomous Cars
Historical Perspective
1920s: The concept of an autonomous car first emerged in 1925
when an electrical engineer from New York City, Francis Houdina, implemented it
in his design. However, his prototype was still not autonomous since users
needed to control it remotely.
1980s: It wasn't until the 1980s that autonomous cars saw
significant progress. Ernst Dickmanns, a German scientist, incorporated cameras
and advanced computing systems into his Mercedes-Benz, turning it into the
first computer-controlled car. With this progress, he became the "father
of autonomous vehicles" for many.
2000s: In 2004,
the Defense Advanced Research Projects Agency (DARPA), a US Department of
Defense branch, held the first-ever "Grand Challenge" event. It aimed
to reward an individual or team that could complete its 150-mile course using
their autonomous vehicle. However, none of the participants finished the
challenging route.
The agency held another "Grand Challenge" event in
2005, modifying it and reducing the length to 132 miles. The Stanford Racing
Team won with their autonomous vehicle in this round, finishing the course
within 6 hours and 53 minutes. Thanks to these challenges, DARPA jumpstarted
research on advancing self-driving cars.
2010s: During this period, the autonomous vehicle sector saw
a surge of interest and investments from big companies like Google and Tesla.
In fact, Google started its self-driving cars project in 2009, now known as Waymo. In 2015,
Waymo released its first-ever fully autonomous vehicle for public roads,
showcasing the progress in sensor technology and AI algorithms.
Tesla also showed its capabilities of developing
self-driving cars with the introduction of their Autopilot feature, an
advanced assistance system that enhances safety and convenience for drivers.
This innovation marked a milestone in consumer-facing autonomous technology,
demonstrating the potential for incorporating self-driving features into
commercially available cars.
Present State of Autonomous Cars
The current state of autonomous cars exhibits a dynamic
landscape of technological advancements with ambitious research and development
efforts. Various companies and industry players actively shape the future of
self-driving technology.
Take Waymo, for instance. The company has accumulated
millions of miles of real-world testing and is now known for its focus on
developing advanced sensor technology and robust AI algorithms. Meanwhile,
Tesla has sensors and AI algorithms that enable lane-keeping, adaptive cruise
control, and self-parking features.
Aside from these tech giants, other companies like Cruise
and Mobileye have entered the self-driving car scene to enhance road safety. Cruise
is actively developing self-driving technology through pilot programs and
partnerships. On the other hand, Mobileye is developing advanced vision-based
driver assistance systems.
Autonomous cars have become prominent over the years. As
such, the industry has set standards for determining a vehicle's automation
level to ensure road safety. These standards can also help owners identify
their vehicle needs like required maintenance or car insurance policy
coverage.
Level 0 (No Automation): The vehicle operates without
autonomous capabilities at this level. Human drivers control all aspects of
driving, such as steering, acceleration, and braking.
Level 1 (Driver Assistance): Level 1 vehicles feature
systems that can assist the driver with specific functions, like adaptive
cruise control or lane-keeping. However, the driver still primarily controls
the car.
Level 2 (Partial Automation): These vehicles have advanced
driver assistance systems (ADAS) that simultaneously control steering,
acceleration, and braking under certain circumstances. However, the driver must
remain attentive and always ready to take control.
Level 3 (Conditional Automation): Vehicles in this level can
manage most driving tasks under specific conditions and environments. The
driver is not required to monitor the road constantly but must be ready to take
over when the system prompts their control.
Level 4 High Automation: Level 4 vehicles can perform all
driving tasks and functions within a defined operational design domain (ODD).
They can operate autonomously without driver intervention in certain conditions
or areas, like predetermined geographic spaces or specific road types. However,
they may still have limitations or require human control in complex situations.
Level 5 (Full Automation): This level represents the
pinnacle of autonomous driving. Level 5 vehicles can operate autonomously in
all conditions”eliminating human intervention. They can handle complex
environments, unexpected events, and diverse road conditions without drivers
controlling the car.
How Autonomous Cars Work
Autonomous cars have many advanced features that redefine
transportation and push the boundaries of technological innovation. Here are
some remarkable capabilities and cutting-edge functionalities that make
autonomous vehicles a fascinating glimpse into the future of mobility.
Sensors and Perception Systems
Autonomous cars rely on advanced sensors, such as cameras,
light detection and ranging (LiDAR) systems, and radars, to perceive and
understand their surroundings. Cameras capture visual data that allows the
vehicle's computer system to recognize and interpret objects, road signs, and
traffic signals.
Meanwhile, LiDAR sensors use laser beams to create detailed
3D maps of the environment, providing depth perception for safe navigation.
Lastly, radar sensors detect objects and obstacles even in adverse weather
conditions, complementing other autonomous vehicle technologies. Integrating
data from these sensors help autonomous cars understand their environment
comprehensively.
Artificial Intelligence and Machine Learning
These two technologies enable autonomous cars to operate intelligently
and make real-time decisions. For instance, AI algorithms process and analyze
the data that the vehicle's sensors collect. They also leverage machine
learning techniques to let the car learn from past experiences and adapt to
various driving scenarios.
Simply put, they can improve the performance of self-driving
cars through deep neural networks and reinforcement learning. In turn, these
vehicles can navigate complex road conditions, anticipate potential hazards,
and respond accordingly.
Connectivity and Communication
Through communication technologies, autonomous cars can
exchange information with each other and with infrastructure. As a result,
drivers can expect enhanced safety and efficiency. For instance,
vehicle-to-vehicle (V2V) communication enables real-time data sharing, such as
speed, position, and intent, letting cars coordinate and make informed
decisions.
On the other hand, vehicle-to-infrastructure (V2I)
communication lets autonomous cars interact with traffic signals, road signs,
and other elements of the transportation ecosystem. This interconnectedness
paves the way for smarter transportation systems and enhanced road safety.
The Future of Autonomous Cars
As we stand on the cusp of a transportation revolution, the
future of autonomous cars holds immense promise and intrigue. Let's delve into
the possibilities that self-driving vehicles bring.
Industry Projections
The future of autonomous cars holds immense potential, as
industry projections show. According to Business Wire, the global market size for self-driving cars can expect a CAGR of
13.3%, from 20.3 million units in 2021 to 62.4 million units by 2030.
Additionally, Mckinsey
projects that self-driving vehicles can generate a revenue of $300 billion to
$400 billion in 2035.
In the same Mckinsey report, projections show that by 2030,
new passenger cars of level 3 automation will have an adoption rate of 12%-20%
and 27%-57% for vehicles with advanced autonomous driving technologies.
Impact on Society
With projections showing a widespread adoption of autonomous
cars, the world can expect a transformative effect on various aspects of
society. Moreover, advancements in self-driving technology can change how the
world operates.
1. Transportation Infrastructure
Enhanced road infrastructure
Autonomous cars rely on well-maintained roadways with clear
markings and signage. Infrastructure upgrades are necessary to ensure
compatibility with autonomous driving systems. For example, governments may
need to improve road markings and communication infrastructure to enhance road
safety for autonomous cars.
Increased development of smart cities
Smart cities may become more prominent as their transport
systems become more suited for autonomous vehicles. It'll consist of smart
traffic management systems, connected infrastructure, and real-time data
analytics that can make traffic flow and urban mobility more efficient.
2. Urban Planning
Reduced parking requirements
Autonomous vehicles can drop off passengers and proceed to
the next destination or find parking in remote locations without driver
assistance. As such, the need for extensive parking spaces in urban areas may
decrease.
This decrease opens opportunities for redesigning urban
landscapes and reclaiming parking lots for green spaces or mixed-use
developments.
Changes in commuting patterns
Since passengers won't need to control the vehicle, they can
work, relax or engage in leisure activities in transit. In effect, they may
become more accepting of longer travel times.
More than that, autonomous vehicles can change commuting
patterns. People may opt to live in the suburbs or rural residences while still
going to work or accessing urban centers conveniently.
3. Employment
Makes professional driver roles obsolete
As autonomous technology advances, there may be a shift
towards autonomous delivery vehicles and self-driving taxis. These sectors may see a decrease in demand
for labor, requiring workforce transitions and retraining programs.
Creates new job opportunities
Developing, deploying, and maintaining autonomous vehicles
can create new positions and help decrease unemployment. The industry will
require engineers, technicians, data analysts, cybersecurity experts, and AI
specialists to design, operate, and support autonomous systems.
4. Environmental Impact
Provides energy efficiency
Autonomous vehicles are programmable to optimize energy
usage and reduce fuel consumption. With AI algorithms, these cars can optimize
routes, acceleration, and braking patterns and contribute to improved fuel
efficiency and reduced carbon emissions.
Aligns with electric and shared mobility trends
Many autonomous vehicles are electric, reducing fossil fuel
dependence. Self-driving technology also enables efficient ride-sharing and
pooling, decreasing the overall number of cars on the road.
Navigating Future Roads with Self-Driving Cars
Autonomous cars represent a remarkable technological
evolution that can revolutionize transportation and reshape society. Through
advancements in self-driving technology and AI, these vehicles are becoming
more of a tangible reality.
Autonomous vehicles have certainly come a long way. However,
further research and development are still needed to unlock their
transformative potential and ensure the safety of all those traversing the open
road.
