Intellectual Property Protection for Intangible Technologies in Autonomous Vehicles in Iran, US, and EU: A Comparative Study with the Focus on Algorithms

The underlying technologies embodied in autonomous vehicles (AVs) underpin the transportation industry to experience remarkable advancement. Technologies enabling vehicles to function autonomously encompass tangible and intangible components, many of which have already been advanced. The legislature should grant intellectual property (IP) protection to the owner of the said technologies to balance the interests of both individuals and society, encouraging development and responsibility. The Iranian IP regulations might pose challenges when protecting intangible components of AV technologies (such as artificial intelligence and software in sensors) and particularly algorithms; the challenges might lead to increased reliance on trade secret regulations and confidentiality contracts, neglecting benefits for society in the disclosure of algorithms. Exploring IP protection for algorithms, facing challenges, and suggesting solutions inspired by the US and EU practices, this research studies current Iranian IP-related regulations, legal literature, and a newly reviewed bill on industrial properties, which has been passed back to the Iranian Parliament for amendments. Following are the findings (1) The wording of the Iranian patent laws with pro-innovation interpretation supports the argument that algorithms are patent-eligible and patentable in principle; (2) considering that the idea of an algorithm is protectable, not merely the expressed form of it, and the originality criterion of a subject matter is a presumption, algorithms might fall within the ambit of the Iranian copyright laws; (3) algorithms attract more protection under trade secret provisions of the new bill than previous regulations in Iran. Lastly, after reflecting on the protection costs and individual-society conflict of interests in the three IP systems, the research concludes by proposing legislation on copyright laws in preference to open source. Document Type: Research Paper.