In-Pavement Fiber Bragg Grating Sensor for Vehicle Counting

Traffic volume studies are conducted to determine the number, movements, and classifications of roadway vehicles at a given location and period. Typically, there are two methods for conducting traffic volume studies: manual and automatic counting. When manual counting is used, a person records the traffic volume on the site or alternatively from video recordings and this estimate can have a large margin of error. Automatic counting is based on measurement technologies, including pneumatic road tubes, inductive loops, infrared, microwave Doppler/radar, passive acoustic, video image detection, and Bluetooth devices. However, they are costly to install and have various limitations, such as high maintenance cost, availability of power source, and dependence on surrounding environment. Currently, weigh-in-motion (WIM) technology has become popular for automatic vehicle counting. In this paper, a three-dimensional glass fiber-reinforced polymer packaged fiber Bragg grating sensor (3-D GFRP-FBG) is introduced for in-pavement vehicle counting. The 3D GFRP-FBG sensor was installed on I-94 freeway, at MnROAD facility, Minnesota. When a vehicle passes over the road, the pavement produces strain signals that are picked up by wavelength changes. These strain peaks can be tracked to achieve vehicle counting. The sensors were laid out 9 feet from the road centerline with 16 feet distance between them to detect all the vehicles travelling on the right side of the road. The feasibility tests show the ability of the sensors to detect vehicles from small cars to semi tractor-trailer. For a 250-second period, the sensor detected 23 vehicles, with a total of 69 axles.

[1]  Ying Huang,et al.  In-pavement fiber Bragg grating sensors for high-speed weigh-in-motion measurements , 2017, Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring.

[2]  Dick T. Apronti,et al.  Estimating Traffic Volume on Wyoming Low Volume Roads Using Linear and Logistic Regression Methods , 2016 .

[3]  Lei Gao,et al.  Using Custom Fiber Bragg Grating-Based Sensors to Monitor Artificial Landslides , 2016, Sensors.

[4]  Ying Huang,et al.  Glass fiber-reinforced polymer packaged fiber Bragg grating sensors for low-speed weigh-in-motion measurements , 2016 .

[5]  Zhi Zhou,et al.  Optical fiber Bragg grating sensor assembly for 3D strain monitoring and its case study in highway pavement , 2012 .

[6]  Pengjun Zheng,et al.  An Investigation on the Manual Traffic Count Accuracy , 2012 .

[7]  T. K. Gangopadhyay,et al.  Fibre Bragg gratings in structural health monitoring—Present status and applications , 2008 .

[8]  Norman W. Garrick,et al.  A Special Fiber Optic Sensor for Measuring Wheel Loads of Vehicles on Highways , 2008, Sensors.

[9]  L Zhang,et al.  Evaluating Weigh-In-Motion Sensing Technology for Traffic Data Collection , 2007 .

[10]  Jongsung Sim,et al.  Interface debonding failure in beams strengthened with externally bonded GFRP , 2004 .

[11]  Alexander Skabardonis,et al.  Estimation of Truck Traffic Volume from Single Loop Detectors with Lane-to-Lane Speed Correlation , 2003 .

[12]  Byoungho Lee,et al.  Review of the present status of optical fiber sensors , 2003 .

[13]  Lawrence A Klein,et al.  SUMMARY OF VEHICLE DETECTION AND SURVEILLANCE TECHNOLOGIES USED IN INTELLIGENT TRANSPORTATION SYSTEMS , 2000 .