Article·AI & Engineering·Jun 17, 2024
6 min read

The Hidden Truth Behind Self-Driving Cars: An Overview

6 min read
Tife Sanusi
By Tife Sanusi
PublishedJun 17, 2024
UpdatedJun 27, 2024

The concept of self-driving cars has been in existence for almost as long as technology has been in existence. Even before the invention of cars and all the way back to Leonardo da Vinci, people have always been fascinated with the idea of autonomous transportation machines. In the 16th century, da Vinci designed what is now regarded as the first self-driving machine and robot of any kind, a small self-propelled cart. This invention would go on to be a blueprint for early versions of self-driving cars. 

Technology has improved dramatically since the time of da Vinci the introduction of AI and computer vision into the mix, self-driving cars are now a reality with these autonomous vehicles being produced all around the world. However, even with all the ways that technology and AI has been used to make daily life easier and more efficient and the fact that self-driving cars are quite literally the stuff of science fiction, people still have reservations about autonomous cars specifically. During a 2024 survey by Forbes, 93% of Americans stated that they have concerns about some aspects of self-driving cars specifically with safety and malfunctions. 61% of people surveyed also said that they wouldn’t trust a self-driving car with their loved ones.

The skepticism of the general public towards self driving cars translates clearly in its sales. Mckinsey & Co predicts that just 12% of new vehicles with autonomous driving technology will be sold by 2030. To understand the current landscape of autonomous vehicles, we need to explore the evolution and challenges of self-driving cars, as well as what the future could look like.

The evolution of self-driving cars

The first record we have of an autonomous car is a newspaper clipping from 1925 that describes a radio-controlled car seen speeding through the streets of New York. According to reports, the car was operated using the telegraph key of the radio transmitter in a second car that followed the autonomous car. A receiving set on the radio controlled car picked up impulses from the second car which were then transmitted to the controls of the car.

In the following decades, several car manufacturers began to lay the groundwork for autonomous cars. In the Norman Bel Geddes’s Futurama exhibit sponsored by General Motors in 1939, radio-controlled cars were displayed. By 1960, Ohio State University had developed a project that would develop driverless cars which could be activated by electronic devices on the roads. In the 1980s and 90s, research on self-driving cars was mostly done under the Eureka PROMETHEUS Project, a scheme that brought together academics, universities, car manufacturers, and tech companies. The end product of the project was a self-driving Mercedes S-Class that went on a thousand mile journey through Munich, Germany to Copenhagen, Denmark without human intervention.

The US Department of Defense began to support research on self-driving cars in the 1980s including funding the Autonomous Land Vehicle (ALV) project and Carnegie Mellon University’s Navigation Laboratory that was researching and producing autonomous vehicles. In 2004, the Department of Defense through their Defense Advanced Research Projects Agency (DARPA) launched a Grand Challenge offering $1 million to any team that could build an autonomous car that could finish a 150-mile course in the Mojave Desert. By the 2010s, various major car manufacturers had started building and testing self-driving cars and in October 2014, Tesla Motors announced that their Model S cars would have autonomous steering and braking systems. In 2019, 29 US states passed laws permitting self-driving vehicles and right now, they are being used as public transportation all over the world. 

The current landscape of self-driving cars

Today, autonomous vehicles function using a combination of machine learning systems, sensors, actuators, complex algorithms, and powerful processors. With the help of sensors placed in various parts of the car, self-driving vehicles can monitor their surroundings, video cameras  detect traffic lights and road signs while keeping track of other vehicles and pedestrians, and light detection and ranging (LIDAR) sensors are able to gauge distances and detect road edges and lanes. All of this is processed through a complex software which then plots a path and sends instructions to the car’s actuators.

While self-driving cars have been around in some form for a couple of decades, public perception of them has not really changed. A large percentage of people have consistently maintained that they would be uncomfortable traveling in an autonomous vehicle. Simply put, people just don’t trust self-driving cars. Some of these concerns is related to recent troubles that Tesla, a brand almost synonymous with self-driving cars, has had with their autonomous vehicles. A National Highway Traffic Safety Administration (NHTSA) study found out that more than two thirds of all Advanced Driver Assistance Systems (ADAS) crashes are Teslas. The car brand also recently recalled almost all of its self-driving cars after a NHTSA probe revealed that nearly 1000 accidents occurred when autopilot was engaged.

The current public perception of self-driving cars is not the only challenge that autonomous vehicles face. Because self-driving cars are still a relatively new invention, at least to the public, there are not a lot of regulations or laws addressing their use. For example, the US currently uses state-by-state mandates for autonomous vehicles meaning that it might be difficult or even impossible to cross state lines with them. In the case of accidents, it is also difficult to determine who should be held liable for accidents caused by autonomous cars. A more existential issue is that the widespread adoption of self-driving cars will force us to reimagine how we develop roads, infrastructure, and even police and emergency response. 

The future of self-driving cars

Self-driving cars is one of those inventions that highlights how far technology has progressed. While we don’t have fully autonomous vehicles for sale yet, it is still very impressive that we are able to have, to an extent, cars that drive themselves. And with the rate at which technology is evolving, we might have fully autonomous cars soon. These cars could potentially help solve a lot of issues including decreasing traffic accidents, automating logistics such as delivery and moving systems, and even improving our quality of life because of less noise and pollution.

With experts predicting that fully autonomous vehicles will not be developed until 2035, we have a chance to think about how we want a future with self-driving cars to look like before it actually gets here. Looking at current research and trends, it is evident that research into autonomous vehicles is prioritizing sustainability and other climate conscious solutions. This is an example of the best approach to integrating autonomous vehicles into society, one that highlights the importance of taking public good into consideration.

Conclusion 

The technology behind self-driving cars has advanced significantly over the past few decades bringing the invention from a radio controlled car that could only move a block to autonomous vehicles that are able to travel across countries without human intervention. If we’re being optimistic, we might have fully autonomous cars in the next ten years which means that we will have to drastically reimagine our roads and transportation systems. With a lot of research going into vehicles that are sustainable and more durable, self-driving cars might provide a better alternative to more traditional driving systems.

Note: If you like this content and would like to learn more, click here! If you want to see a completely comprehensive AI Glossary, click here.

Unlock language AI at scale with an API call.

Get conversational intelligence with transcription and understanding on the world's best speech AI platform.