Abbott approached Thaler about using the AI as the basis of the case and with a team of lawyers, all working pro bono, they filed patent applications in more than a dozen countries listing DABUS as the inventor of a beverage container it created. New Zealand's Assistant Commissioner of Patents rejected the initial application in January, ruling that the term "inventor" intrinsically refers to a natural person. Abbott said the test case was not about any sort of legal rights for machines, rather it was about trying to get a patent for "the inventive output from an AI" that lacks a traditional human inventor. Some firms were already using AI programmes to discover new drugs or to find ways to repurpose materials but the companies that many of the lawyers on the case represent wanted greater clarity on patent ownership before investing further, he said. The application was declined in Australia but later overturned by the Federal Court in 2021 which said the country's patent act had no specific provision excluding AI systems as inventors.

In this paper, we describe a pilot implementation and field test of a recently developed approach to real-time adaptive traffic signal control. The pilot system, called SURTRAC (Scalable Urban Traffic Control), follows the perspective of recent work in multi-agent planning and implements a decentralized, schedule-driven approach to traffic signal control. Under this approach, each intersection independently (and asynchronously) computes a schedule that optimizes the flow of currently approaching traffic through that intersection, and uses this schedule to decide when to switch green phases. The traffic outflows projected by this schedule are then communicated to the intersection's downstream neighbors, to increase visibility of vehicles entering their respective planning horizons. This process is repeated as frequently as once per second in rolling horizon fashion, to provide real-time responsiveness to changing traffic conditions and coordinated signal network behavior. After summarizing this basic approach to adaptive traffic signal control and the domain challenges it is intended to address, we describe the pilot implementation of SURTRAC and its application to a nine-intersection road network in Pittsburgh, Pennsylvania. Both the SURTRAC architecture for interfacing with the detection equipment, hardware controller and communication network at a given intersection and the extensions required to account for unreliable sensor data are discussed. Finally, we present the results of a pilot test of the system, where SURTRAC is seen to achieve major reductions in travel times and vehicle emissions over pre-existing signal timings.