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Washington DC names winner of autonomous vehicle challenge
AIWaysion will deploy its Mobile Unit for Sensing Traffic to help DDoT independently observe and analyse AV operations in real-world, mixed urban traffic.
At a glance
Who: US Ignite; District Department of Transportation (DDoT); Southwest Business Improvement District (SWBID); AIWaysion; Parsons Corporation; George Washington University; University of Washington.
What: AIWaysion has been announced as the winner of the Autonomous Vehicle Observation (AVO) Zone Challenge.
Why: The pilot will provide valuable data to help DDoT understand how autonomous vehicles interact with pedestrians, cyclists, transit users, and motorists in a complex urban environment.
When: The pilot is scheduled to begin in January 2027.
AIWaysion has been named the winner of the Washington DC Autonomous Vehicle Observation (Avo) Zone Challenge.
The Avo Zone Challenge was designed to identify and pilot innovative solutions that enable the District Department of Transportation (DDoT) to detect, monitor, and analyse the impact of autonomous vehicle (AV) operations in DC.
Mobile sensing
The District Department of Transportation (DDoT), partnered with Southwest Business Improvement District (SWBID), and US Ignite to launch the Avo Zone Challenge.
AIWaysion, in partnership with Parsons Corporation, will deploy its Mobile Unit for Sensing Traffic (Must) to help DDoT independently observe and analyse autonomous vehicle operations in real-world, mixed urban traffic.
The Edge AI roadside sensing system uses computer vision to detect and track autonomous vehicles, generate high-resolution trajectory data, and produce configurable traffic behaviour analytics. Scheduled to begin in January 2027, the pilot will be part of one of the nation’s first municipal efforts to build an independent, data-driven understanding of how AVs operate on public streets.
“The decisions we make today will help shape the streets of tomorrow, and our goal is to ensure innovation moves forward with safety at the forefront”
Supported by academic partners, the George Washington University and the University of Washington, the initiative will help equip DDOT with tools and data insights to better understand how AVs interact within a bustling multimodal transportation environment as emerging transportation technologies continue to evolve.
“Emerging technology gives us an opportunity not only to better understand how our transportation system is changing, but to make it safer for everyone who uses it,” said DDoT director Sharon Kershbaum.
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Kershbaum continued: “This pilot will provide valuable data to help us understand how autonomous vehicles interact with pedestrians, cyclists, transit users, and motorists in a complex urban environment. The decisions we make today will help shape the streets of tomorrow, and our goal is to ensure innovation moves forward with safety at the forefront.”
“AIWaysion is helping the DC Mobility Innovation District take an important step in co-creating safe streets for our residents,” said Zachary Baldwin, director of mobility, data, and research at SWBID. “The AVO Zone Challenge is a great example of how SWBID can support the district’s efforts to ensure AVs drive responsibly so DC’s roads are safe for all road users.”
AI smart infrastructure
AIWaysion is a transportation technology company pioneering edge AI smart infrastructure with a view to making transportation systems safer and more efficient. It reports its technology has been deployed at more than 150 locations across 15 states, supporting state, local, and tribal transportation agencies in multimodal traffic monitoring and data collection.
US Ignite works closely with communities, startups, and researchers to solve, what it reckons is their toughest economic development and technology innovation challenges. Operating like a high-tech startup, the nonprofit organisation aims to deliver customised results through stakeholder engagement, technical expertise, and targeted tools.
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Who won Washington DC’s Autonomous Vehicle Observation Zone Challenge?When is AIWaysion’s autonomous vehicle observation pilot scheduled to begin?What will AIWaysion’s Mobile Unit for Sensing Traffic measure?Which road users will DDoT study alongside autonomous vehicles?How will Edge AI help DDoT monitor AVs in mixed traffic?AI and Machine LearningAnalyticsCAVsCloud and edge computingconnected and autonomous vehiclesDatamobilityRoadWashington DC
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