Autonomous vehicles were designed with the purpose of minimizing accidents on urban roads and providing more safety and comfort, assisting or performing independently some tasks that are the driver’s responsibility.
The Society of Automotive Engineers (SAE) has developed a classification of autonomous vehicles, creating six categories for autonomous driving. Level zero refers to conventional cars without any technology of this type, while at the other extreme, at level five, the driver becomes a passenger, needing only to activate the vehicle and indicate the destination. In such case, it is up to the vehicle control system to carry out in a fully autonomous way the driving of the vehicle throughout the route and to carry out any emergency decision-making. The intermediate levels of autonomous driving include systems already found on the market, such as parking assistance, emergency braking and lane change assistance, among others.
In general, to perform actions autonomously, a vehicle depends on various types of sensors that allow the reading of external parameters of the environment in which it travels (such as the presence of pedestrians, other vehicles, traffic signs and any obstacle that may arise on a road, for example) and the information collected by these sensors must be treated and processed to enable the sending of commands to electronic actuators subject to which the vehicle performs a certain action, such as emergency braking or making a detour.
To achieve higher levels of autonomous driving, it is essential to develop technologies with greater capacity to obtain and process data, starting from sensors and other hardware components that are more robust, agile and with lower manufacturing costs, as well as the development of more efficient software and control methods with lower error rates. The use of artificial intelligence and deep learning become important allies in this mission.
Deep learning consists of an artificial intelligence technology which conducts information even faster and makes decisions in a fraction of a second, constantly improving itself and becoming more accurate and assertive than a human driver. Therefore, with the advent of deep learning, it is expected that a vehicle will be able to visualize and interpret the real world and recognize obstacles early enough to make any kind of decision in driving the vehicle.
Because it is a new technology, another important ally in the development and expansion of autonomous vehicles in the market are the tools for the protection of intellectual property.
Getting Around the Ban on Software Patents
Regarding the protection of software in autonomous vehicles, it is important to note that the Brazilian Industrial Property Law (Law No. 9,279/1996) provides for a prohibition on the protection of “software per se” through patents. Specifically, according to Article 10, item V, a software is not considered an invention or utility model, per se. As per this understanding the source code of the software is understood as “software per se“, being an expression or method by means of a language that can be understood by a computer.
However, the method itself, represented by a sequence of logical steps that is capable of solving a certain technical problem, might be patentable and, in parallel, the referred source code can be protected as a computer program, based on the so-called “Brazilian Software Law” (Law No. 9.609/1998), which follows a legal regime related to copyright, and gives the author a period of 50 years of exclusivity for commercial exploitation of the protected computer program.
Stay Ahead of the Competition with IP
Statista recently published a DossierPlus on autonomous vehicles, indicating that annual production of self-driving cars is expected to reach 800,000 units worldwide between 2023 and 2030. The analysis indicates that autonomous vehicles are a trend of the near future and, therefore, those that hold intellectual property rights (and, consequently, exclusive rights of commercial exploitation) over the main technologies that enable these vehicles, at accessible costs to the public, will have the greatest commercial advantage over their competitors.
Therefore, developers of technologies in the field of autonomous vehicles that use artificial intelligence and adopt policies to protect intellectual property will be able to reap the fruits of their investments. Getting IP protection will allow them to stand out in the market as technology in this burgeoning sector evolves.
Article published on the IPWatchdog.