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Autonomous vehicles: How does they work?

Autonomous vehicles promise to revolutionize the way humans and goods move around, in a future that is getting closer. When AI takes the wheel and Data serves as the engine: discover everything you need to know about this technology that will change the world!

Artificial Intelligence is making its way into all areas, including on the roads. Among all the innovations based on this revolutionary technology, one of the most pivotal is undoubtedly autonomous vehicles.

Once a figment of the overflowing imagination of science fiction authors, the driverless car is now nearly a reality, driven forward by the rapid advancements in AI and Data Science.

We hear every day about these vehicles of a new kind, capable of launching themselves onto the asphalt alone, and their manufacturers like Tesla, Waymo with its autonomous taxis, or Chinese behemoths like Baidu.

However, do you genuinely understand how this technology functions? It epitomizes a complex and intriguing fusion between engineering, computing, and cognitive sciences with the sole aim of enabling vehicles to perceive, analyze, and react to their environment.

Through this article, you’ll uncover the true secret behind this road revolution, and grasp the crucial role of AI and Big Data!

What are autonomous vehicles?

The term autonomous vehicle refers to a vehicle capable of perceiving its environment and operating without any human intervention.

Truth be told, there is even no need for a passenger to be on board. However, like a conventional vehicle, it can navigate from point A to point B using the same roads.

This technology is far from trivial, as it will eventually permanently replace manual driving. Over time, artificial intelligence will commit fewer errors than humans and will thus be safer.

That’s why numerous manufacturers are already developing or testing autonomous vehicles, such as Audi, BMW, Ford, General Motors, Tesla, Volkswagen, and Volvo.

The NHTSA, the agency in charge of road safety in the United States, has established six levels of autonomy. Level 0 corresponds to human driving, while level 6 denotes a fully autonomous vehicle…

So, how does it operate? What’s concealed under the hood of these vehicles to enable them to move independently?

Replacing the human driver

While the concept of an autonomous vehicle is easy to comprehend, its operation relies on several highly complex cutting-edge technologies.

Each of these machines is outfitted with a system composed of sensors, algorithms, and software, empowering it to navigate safely on its own.

Radars monitor the positioning of surrounding vehicles, cameras detect traffic lights, signs, and pedestrians, while Lidar gauges distances and detects road edges through pulses of light.

All data collected by these sensors is then consolidated and interpreted by sophisticated algorithms, creating a visual representation of the vehicle’s surroundings.

Once the vehicle has a distinct perception of its surroundings, it must be capable of making intelligent real-time decisions.

This achievement is enabled by AI and Machine Learning algorithms, which scrutinize the current driving scenario and historical data to forecast the movements of other road users, anticipate risks, and chart safe paths.

Thus, various sensors substitute the eyes and ears of the human driver, while algorithms act as the brain to process the information.

To translate its decisions into concrete actions, the vehicle employs control systems and actuation ensuring it follows its trajectory accurately, by adjusting its speed, direction, and braking according to the prevailing conditions.

Perception, decision, and action: it is through combining these three components that vehicles become competent at navigating autonomously in a broad array of environments.

A world without accidents or traffic jams?

If autonomous driving technology generates so much buzz, it’s because it harbors many promises.

In terms of road safety, vehicles steered by AI are likely to significantly diminish the number of accidents. Most often, road catastrophes ensue due to human errors such as distraction, fatigue, or recklessness.

However, even if autonomous cars are not yet 100% dependable, they could ultimately eradicate these negative behaviors entirely. Furthermore, AI can react much quicker than a human being.

Moreover, such a vehicle can allow older or disabled individuals to regain independence. If you forget something when departing on vacation, your car could return autonomously to collect it (with the assistance of a neighbor). You could even send your pet to the vet unaccompanied!

These vehicles can also enhance energy efficiency and traffic flow. Thanks to their ability to communicate amongst themselves and cooperate in a coordinated manner, they can optimize routes, diminish traffic jams, and minimize fuel consumption.

This may therefore lead to massive savings in terms of time and travel expenses for users.

According to a study by ITDP, by 2050, autonomous and electric vehicles could reduce the number of cars on the roads by 30%, lower expenses by 40%, liberate numerous parking spaces, and decrease CO2 emissions by 80% globally.

When all the vehicles on the roads are autonomous, traffic could become perfectly fluid. Unfortunately, numerous obstacles still stand in the way…

A road still strewn with hurdles

Despite the many advantages presented by this technology, several significant challenges must be surmounted before autonomous vehicles becomes an ubiquitous reality on our roads.

Its widespread adoption has suffered a great deal of delay compared to initial predictions, and this is attributable to several reasons.

Firstly, the challenge of developing AI and sensors sophisticated enough to foresee every potential hazard on a road as unpredictable as ours has proven more daunting than anticipated.

Moreover, even if accidents are infrequent, they sow doubt and provoke hesitancy among the public and governments regarding the reliability and safety of this new mode of transport.

And in the event of a collision, who is held responsible? The manufacturer, the owner, the software developer, or a combination of these stakeholders? It is difficult to pinpoint an exact answer.

Another barrier to enthusiasm for this innovation is the significant impact it could have on employment, by replacing human drivers in various sectors such as freight transport and taxi services.

There is also the dilemma of safeguarding the sensitive data about users’ movements and behaviors, which are generated and processed in vast quantities by autonomous vehicles.

Before we can aspire to see the driverless car proliferate on the roads, it will be necessary to guarantee their absolute safety, to protect the data against hacking and leaks, and to unambiguously define standards of responsibility.

Freight transport, urban mobility... what are the use cases?

As autonomous vehicle technology develops, its applications are rapidly diversifying and reaching various sectors by offering solutions to contemporary mobility challenges.

In the realm of freight transport, these vehicles are utilized to cut logistical costs and optimize delivery routes. Autonomous truck fleets can operate continuously, without needing breaks for drivers.

This accelerates deliveries and reduces waiting times. Similarly, driverless cars provide innovative solutions for carpooling and public transport services.

Autonomous shuttles can circulate in densely populated urban areas, presenting a convenient and eco-friendly way to navigate. They can also be meshed into existing public transport systems, for example as a last-mile solution for travelers.

In San Francisco, California, Waymo autonomous taxis are already traversing the streets widely and are gaining popularity despite some early obstacles.

Across the automotive industry, manufacturers are progressively incorporating autonomous technologies into their production vehicles. Features such as lane-keeping assist, adaptive cruise control, and automatic parking have become widespread.

However, few manufacturers offer an autopilot system as advanced as Tesla’s Full Self-Driving

The pivotal role of AI and Data Science

The ascendancy of autonomous vehicles is intimately linked to the rapid progress in AI and Data Science. These disciplines play an essential role in the evolution of autonomous systems capable of perceiving, understanding, and acting within complex environments.

The gathering and analysis of extensive data are crucial to enhance their performance, by enabling them to learn from past experiences and to adapt to varying road conditions.

For a deeper understanding of the road environment, Deep Learning plays a particularly critical role.

It is deep neural networks that enable vehicles to extract complex patterns from raw sensory data to effectively detect and identify objects, obstacles, and driving situations.

But it is this capacity to learn from data that truly sets autonomous vehicles apart from traditional automated control systems.

Moreover, predictive modeling is essential to foresee the behaviors of other road users and to plan both safe and efficient paths.

Utilizing techniques such as probabilistic models and recurrent neural networks, autonomous cars can anticipate the movements of pedestrians, cyclists, and other vehicles to make proactive decisions and avoid collisions or other risky situations.

Indeed, it is the advancements in AI and Data Science that will pave the way to a new era of intelligent and sustainable mobility!

Conclusion

In the years ahead, AI and other foundational technologies of autonomous vehicles will continue to evolve and enable us to surmount the obstacles currently hindering its widespread adoption.

Eventually, we will be able to move about safely without even needing to pay attention to the road. As a result, our entire way of life will transform, as daily commutes can become moments of leisure.

We can also look forward to integration with the infrastructures of smart, connected cities, with transport systems coordinated with traffic lights and road sensors.

Autonomous vehicles will facilitate the transition to a world that is safer, greener, and above all, more liberated. If you wish to play a part in this revolution, you can train with DataScientest!

Our distance learning programs will enable you to acquire expertise in Data Science and artificial intelligence, which you can then apply to the development of autonomous vehicles or other tech companies related to this sector.

All our certification courses are available in bootcamp, continuous training, or apprenticeship formats, and our organization qualifies for CPF funding. Discover DataScientest promptly!

You now know everything about autonomous vehicles. For more information on this topic, explore our comprehensive file on Deep Learning and our general dossier on artificial intelligence

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