Abstract Manager

Managing large-scale pavement surveys across Texas requires efficient data collection strategies to meet delivery schedules while maintaining quality standards. ARRB Systems America deployed two iPAVe vehicles simultaneously for TxDOT pavement condition surveys across multiple districts, creating unique coordination challenges that required planning approaches beyond standard single-vehicle workflows.Running two survey vehicles at the same time meant figuring out how to keep data quality consistent between vehicles, manage multiple processors working on different county deliverables simultaneously, handle spatial remapping validation for both datasets, and coordinate field operations to avoid conflicts. The standard single-vehicle workflow wasn't scalable to this complexity without sacrificing TxDOT's strict QC requirements. This presentation outlines the practical planning framework developed to coordinate dual-vehicle pavement surveys while maintaining data consistency, meeting delivery timelines, and ensuring quality control procedures work effectively across multiple data streams.The implementation involved developing coordinated survey schedules that maximized coverage while preventing vehicle route conflicts. A critical component was establishing weekly validation and calibration procedures where both vehicles were tested against ground truth sections and compared against each other before being cleared for collection. This cross-vehicle validation ensured data consistency throughout the project and caught any equipment drift early. Data processing workflows were standardized so different processors could handle TxDOT database deliverables consistently, including deflection QC procedures, pavement type assignments, and spatial remapping validation. Real-time communication protocols kept field and office teams synchronized throughout the project. The approach required careful database management.The dual-vehicle strategy cut project timelines significantly while maintaining TxDOT quality standards. Success came from establishing clear processing procedures upfront, implementing systematic QC checks that worked across both vehicles, maintaining rigorous weekly calibration protocols, and ensuring effective communication between processors. The framework proved effective for managing complex multi-vehicle operations and should transfer well to other large state networks facing similar delivery pressures.