Monitoring the Speed, Configurations, and Weight of Vehicles Using an In-Situ Wireless Sensing Network

The Virginia Polytechnic Institute and State University is developing an integrated transportation monitoring system that will be capable of monitoring pavement and traffic simultaneously. As part of the system, a backcalculation method, which is presented in this paper, is used to estimate the speed, weight, and configuration of passing vehicles based on the pavement responses collected by in-situ pavement sensors. This method is still in its preliminary stage but could be very helpful in achieving real-time weigh-in-motion and traffic classification once completed in the future. A Gaussian model is used to describe the distribution of the horizontal strain induced by passing vehicles. The parameters of the Gaussian model are correlated with various loading conditions, including the weight and the configuration parameters of the passing vehicles, as proved by finite-element simulation and experimental measurements. The backcalculation process is efficient and valuable, considering the accuracy of the estimation with a low computational cost. The whole method is simple and straightforward and can be conveniently used in real-time monitoring.

[1]  H Jianming,et al.  Traffic congestion identification based on image processing , 2012 .

[2]  Jinhui Lan,et al.  Vehicle detection and classification by measuring and processing magnetic signal , 2011 .

[3]  Rahim F Benekohal,et al.  Technologies for Truck Classification and Methodologies for Estimating Truck Vehicle Miles Traveled , 2003 .

[4]  George Yannis,et al.  Integration of Weigh-in-Motion Technologies in Road Infrastructure Management , 2005 .

[5]  Paul J Cosentino,et al.  Analysis of Fiber Optic Traffic Sensors in Flexible Pavements , 2003 .

[6]  Imad L. Al-Qadi,et al.  The Virginia smart road: The impact of pavement instrumentation on understanding pavement performance , 2004 .

[7]  B G Grossman,et al.  OPTIMIZATION AND IMPLEMENTATION OF FIBER OPTIC SENSORS FOR TRAFFIC CLASSIFICATION AND WEIGH-IN-MOTION SYSTEMS (PHASE 3) , 2000 .

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

[9]  Imad L. Al-Qadi,et al.  Difference between In Situ Flexible Pavement Measured and Calculated Stresses and Strains , 2006 .

[10]  Piotr Piwowar,et al.  Measurements of Road Traffic Parameters Using Inductive Loops and Piezoelectric Sensors , 2007 .

[11]  Imad L. Al-Qadi,et al.  Pavement Response to Dual Tires and New Wide-Base Tires at Same Tire Pressure , 2002 .

[12]  Wenbin Zhang,et al.  A Novel Vehicle Classification Using Embedded Strain Gauge Sensors , 2008, Sensors.

[13]  Benjamin Coifman,et al.  Speed Estimation and Length Based Vehicle Classification from Freeway Single Loop Detectors , 2009 .

[14]  Erland O Lukanen Load Testing of Instrumented Pavement Sections , 2005 .

[15]  Philip J Tarnoff,et al.  Data Collection of Freeway Travel Time Ground Truth with Bluetooth Sensors , 2010 .

[16]  R. Sroka,et al.  Accuracy analysis of WIM systems calibrated using pre-weighed vehicles method , 2007 .

[17]  Nicholas J Garber,et al.  CONTROL OF VEHICLE SPEEDS IN TEMPORARY TRAFFIC CONTROL ZONES (WORK ZONES) USING CHANGEABLE MESSAGE SIGNS WITH RADAR , 1995 .

[18]  P. Varaiya,et al.  Sensor Networks for Monitoring Traffic , 2004 .

[19]  Imad L. Al-Qadi,et al.  Simulation of tyre–pavement interaction for predicting contact stresses at static and various rolling conditions , 2012 .

[20]  I. Magrini,et al.  A Distributed Sensor Network for Real-Time Acoustic Traffic Monitoring and Early Queue Detection , 2010, 2010 Fourth International Conference on Sensor Technologies and Applications.

[21]  O K Norman,et al.  Weighing vehicles in motion , 1952 .

[22]  Imad L. Al-Qadi,et al.  Impact Quantification of Wide-Base Tire Loading on Secondary Road Flexible Pavements , 2011 .

[23]  Imad L. Al-Qadi,et al.  Quantification of Pavement Damage Caused by Dual and Wide-Base Tires , 2005 .

[24]  Brian Daku,et al.  Continuous primary dynamic pavement response system using piezoelectric axle sensors , 2005 .

[25]  Peter Wagner,et al.  A TRAFFIC INFORMATION SYSTEM BY MEANS OF REAL-TIME FLOATING-CAR DATA , 2002 .

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

[27]  Tarek Saadawi,et al.  Overhead infrared vehicle sensor for traffic control , 1993, IEEE 43rd Vehicular Technology Conference.

[28]  Eric Udd,et al.  Traffic monitoring using fiber optic grating sensors on the I-84 freeway and future uses in WIM , 2003, Pacific Northwest Fiber Optic Sensor Workshop.

[29]  Rafael Palacios Hielscher,et al.  Speed estimation of vehicles approaching an intersection, a digital image processing method , 2011 .