|Every day, we see news of car accidents across the world. The World Health Organization reported that nearly 1.25 million people die in road crashes annually, at an average of 3.287 deaths a day/ Photo by: Photo Spirit via Shutterstock|
Every day, we see news of car accidents across the world. The World Health Organization reported that nearly 1.25 million people die in road crashes annually, at an average of 3.287 deaths a day. Road crashes are the leading cause of death among young people ages 15 to 29, while it is the second leading cause of death among kids ages 5 to 14. If this continues, it is predicted that road traffic injuries will become the fifth leading cause of death by 2030.
Thus, road safety and driver’s education have become some of the governments’ priorities throughout the years. Car accidents can be predicted and prevented only if there are actions taken such as legislating and enforcing laws governing speed limits, formulating and implementing transport and land-use policies that promote safer and more efficient trips, and more. Fortunately, artificial intelligence can play a huge role not only in automating cars but also reducing road crashes and saving lives.
The Growth of AI in Automotive
Driverless cars have been hitting the headlines and dominating tech-talks, making sure that everyone knows the benefits they could provide.
Reports show that the automotive AI market was valued at $783 million in 2017, which is projected to increase by $11k million by 2025 – a CAGR of about 38.5%. Global information provider IHS Markit predicted that the installation rate of AI-based systems of new vehicles would increase from 8% in 2015 to 109% in 2025. Allied Market Research, a market research and advisory company, reported that the growth of the automotive AI market is driven by the rise in demand for autonomous vehicles as well as the increase in preference for enhanced user experience and convenience features.
Today, the automotive industry is among the major industries using AI to augment and mimic the action of humans. Automotive vendors are also encouraged to integrate AI due to its features such as adaptive cruise control (ACC), advanced driver assistance system (ADAS), blind-spot alert, and growth in demand for convenience features. In the next few years, it is projected that some of the factors that would influence the growth of the global automotive AI market include the increasing demand for premium vehicle segment, rising security and privacy concerns, rising trend of autonomous vehicles, and rise in demand for enhanced user experience and convenience features.
Among the features causing autonomous vehicles to gain popularity across the world are self-driving, automatic parking, autopilot, and others. All of these can minimize human effort when driving. At the same time, the biggest tech companies like Nvidia, Intel, and Tesla have also been active in developing autonomous vehicles. For instance, Tesla’s autopilot system has been considered one of the most advanced systems available in the automotive AI market due to its features, including self-parking, auto changing the lanes whenever required, and keeping the vehicle within a lane while driving.
How AI is Paving the Way for Self-Driving Cars
Today, tech companies are building autonomous vehicles that drive themselves but they are also working to make them drive as human drivers do. This means they need to provide these vehicles with cognitive functions (learning, decision-making, logical thinking, and memory), sensory functions, and executive capabilities that humans use to drive vehicles. According to Micron Technology, an American producer of computer memory and computer data storage, autonomous vehicles require safe, secure, and highly responsive solutions because they need to be able to make split-second decisions based on a detailed understanding of the driving environment.
For autonomous vehicles to understand their driving environment, they need to have a huge amount of data to be captured by myriad different sensors across the car. Also, AI networks need to undergo extensive training to understand how to see, understand what it’s seeing, and make the right decisions in any imaginable traffic situation. At the same time, a self-driving car’s AI system can only make real-time decisions based on complex data sets when they have a continuous, uninterrupted stream of data and instructions.
|Today, tech companies are building autonomous vehicles that drive themselves but they are also working to make them drive as human drivers do / Photo by: riopatuca via Shutterstock|
Also, it’s important to understand that there are different levels of self-driving cars. According to Forbes, a global media company focusing on business, investing, technology, entrepreneurship, leadership, and lifestyle, cars with AI driving them entirely on their own are considered Level 4 and Level 5 self-driving cars. Those that are at a Level 2 or Level 3 require a human driver to co-share the driving effort. They are considered semi-autonomous and usually have a variety of automated add-on’s that are referred to as ADAS (Advanced Driver-Assistance Systems).
Robert Bielby, the senior director responsible for automotive system architecture in the embedded business unit at Micron, stated that autonomous cars can drive better than human-driven cars due to AI’s deep neural network algorithms. “Combined with the extreme compute performance that today can be deployed in a car, and you have a situation where it is possible for cars to do a far better job of driving down the road with greater safety than we can,” Bielby said.
AI is a critical aspect to unleash the fullest potential of self-driving cars. Innovative memory and storage systems are needed for an autonomous vehicle to process and hold the vast amount of data necessary for a computer to make decisions like a human. This not only makes autonomous cars more advanced than ever but also ensures the drivers’ safety.