The District of Columbia Department of Transportation (DDOT) is accepting vendor proposals through July 16 for its Autonomous Vehicle or AV Observation Zone Challenge; a contest that seeks to develop a sensing technology package capable of detecting and identifying AVs operating within Washington, D.C., along with data that supports the observation and analysis of AV fleet operations. [Above image via DDOT] The project will allow DDOT and its academic partners to observe autonomous vehicle behavior and compare it with baseline data collected from human-driven vehicles. The findings will help inform future discussions regarding AV testing, deployment, and regulation in Washington, D.C. The selected vendor for this project – expected to be chosen by August – will receive $50,000 and will pilot its technology for three to six months at two intersections along the M Street SE/SW corridor within the nation’s capital. [Editor’s note: In April, DDOT issued a report reviewing how AVs are regulated across the United States as part of an effort to inform ongoing internal decision-making efforts concerning AV regulation for the area under its jurisdiction.] “The observation and analysis of autonomous vehicle behavior is an important part of understanding how these technologies fit into the District’s transportation system,” said Sharon Kershbaum, DDOT’s director, in a statement. “This initiative will help us better understand real-world autonomous vehicle operations while supporting thoughtful planning, public transparency, and informed decision-making.” The project is funded by the DDOT Research Program and is conducted in partnership with the Southwest Business Improvement District, US Ignite, George Washington University, and the University of Washington. Data gathered by the winning vendor will be analyzed by the academic faculty at the two universities that specialize in autonomous vehicles and urban traffic system modeling and operations. Other state departments of transportation have also participated in various AV testing