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DESCRIPTION:<p>Connected, Cooperative, and Automated Mobility (CCAM) is often discussed through the lens of vehicle automation—but its real power emerges when data, infrastructure, and AI work together at a system level.</p>
<p>In this session, experts explore real-world CCAM use cases from the United States, focusing on how AI enhances cooperation between vehicles, infrastructure, and transportation agencies, without being the autonomous driving AI itself.</p>
<p>The discussion will highlight:</p>
<ul>
<li>Connected vehicle data as a system-wide intelligence layer</li>
<li>AI-driven analytics for congestion mitigation, safety insights, and operational decision-making</li>
<li>Cooperative Congestion Management (CCM) pilots and lessons learned</li>
<li>How agencies can move from raw mobility data to actionable insights using AI-powered platforms</li>
</ul>
<p>This session bridges policy, operations, and technology, offering a practical roadmap for how CCAM can deliver measurable benefits today—improved safety, reduced congestion, and smarter investments—while laying the foundation for future automation.</p>
DTSTAMP;VALUE=DATE-TIME:20260214T140812
DTSTART;VALUE=DATE-TIME:20260310T114500
DTEND;VALUE=DATE-TIME:20260310T123000
LOCATION:3. SUMMIT THEATRE 3
SUMMARY;LANGUAGE=en_us:Beyond Autonomy: AI, Data, and the Future of Cooperative Mobility
TRANSP:TRANSPARENT
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