Piloting an AI-Enabled Immersive Multi-Agency Traffic Incident Management (TIM) Training Platform
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2026-09-01
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Edition:Final Report
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Description:Traffic Incident Management (TIM) depends on coordinated actions among transportation agencies, law enforcement, fire and rescue, emergency medical services, towing and recovery, dispatch, and other partners. This pilot project developed and demonstrated a modular immersive TIM training platform intended to supplement classroom, tabletop, online, and field-based training. The platform was implemented on Meta Quest 3 standalone virtual reality headsets and organized around reusable Virtual Operational Environments (VOEs) that separated persistent roadway settings from scenario-specific incident content. Two VOEs were developed: an Interstate VOE representing multilane, high-speed operations and a Rural Highway VOE representing a two-lane, two-way roadway with opposing traffic and constrained response space. The platform incorporated first-person navigation, selected object interactions, in-application voice communication, rule-based simulated roadway traffic, shared sessions supporting up to four participants, and an initial Unity-Open AI application programming interface connection that presented model-generated text within the VR application. Three pilot demonstrations were conducted with Missouri Department of Transportation personnel and TIM partners. Demonstration feedback led to further refinement of the Rural Highway VOE and implementation of an injured-driver avatar and related animation. Additional updates involving towing and recovery, participant orientation, scenario content, structured data capture, after-action review, and AI-enabled virtual responders were also implemented. The demonstrations supported the technical feasibility and operational relevance of the platform but did not constitute a formal evaluation of training effectiveness. A focused second phase is recommended to expand scenarios, develop validated role-specific virtual responders, implement controlled scenario actions and instructor oversight, and conduct technical, usability, operational-validity, and training-effectiveness evaluations.
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Main Document Checksum:urn:sha-512:7fe6f35091400ab956ab63ca5675f6f5b27ccd57335a86b362f816538492dafca0c2244a144a744485a97390e4daf2abd80d739ce69936fadaccbba56fa3e49f