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Reimagining Sensor Deployment

Abstract

The California Department of Transportation (Caltrans) collects megabytes of data every day using a dedicated traffic sensing infrastructure. The collected data provide support for traffic management and system performance monitoring activities that are crucial for supporting the agency’s mission, vision, and strategic goals to strengthen stewardship and drive efficiency. Operating this vast detection system requires extensive resources in the form of engineering and maintenance support, along with millions in capital funds to keep the system running. Within the above context, alternate hybrid data collection models utilizing purchased or third-party data to augment existing data collection system capabilities may enable a reduction in the number of physical detection stations required while maintaining suitable accuracy for Caltrans’ purposes. In addition to the potential for cost savings, the reliance on fewer physical sensors also offers the potential to reduce the exposure of Caltrans employees to the occupational hazard of maintaining roadside detection stations, in alignment with the agency’s “safety first” strategic goal.

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