ADVANCED SENSOR TECHNOLOGIES

We have exclusive knowledge and project experience on the cutting-edge Inductive Loop Signature (ILS) technologies and the next-generation traffic performance measurement system.

The conventional traffic sensors typically provide volume, occupancy, vehicle presence and speed data. ILS is an emerging advanced sensor technology that aims to provide more data for travel information, travel time estimation, vehicle classification, emission, and origin-destination (OD) estimation applications.

WIM has been employed as a major technology to collect heavy vehicles’ data on the freeways. Because WIM is one of the most costly and sophisticated data collection system, how to effectively utilize the valuable WIM data, monitor WIM stations’ performance, and identify out of calibration stations are especially important. In this project, CLR proposed an innovative and yet practical approach to develop an Inductive Loop Signature-WIM based real-time heavy vehicle monitoring system that combines the use of both WIM data and the inductive loop signature data. The integration of inductive loop signature technology offers a low-cost solution to monitor the performance of the WIM stations, identify out-of-calibration stations, and provide ground-truth truck movement data to be used for calibration.

Continued population growth and expanded commercial development have already push the daily traffic on National Park Service (NPS) Parkways exceeds design capacity especially around the urban area. The Parkways around urban areas usually serve as commuting routes for commuters and as scenic routes for visitors. Heavy traffic in rush hours, high travel speeds during non-peak periods, and condition of the road surface in bad weather have made the Parkways more vulnerable to traffic accidents. It is important to collect and utilize the traffic data to fulfill the needs of improving safety and mobility of the Parkways.

Inductive loop detection systems are currently the most invested technology for obtaining traffic data in the United States and are widely deployed on most major freeway networks. With continuing emphasis on transportation sustainability, there is an increasing need to obtain more accurate and comprehensive traffic system performance measures such as section travel time, origin-destination, and vehicle classification.

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