A Novel Low-Cost Weigh in Motion (WIM) System Tested in Virginia Suggested the Cost to Monitor Vehicle Weights and Axle Layouts in Live Traffic Could be Reduced by 73 Percent Compared to a Traditional WIM System.

Virginia Study Used Accelerometer Sensors to Measure Pavement Deflection and Automatically Assess Characteristics of Moving Traffic.

Date Posted
05/30/2023
Identifier
2023-B01749
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Development of Low-Cost Weigh-In-Motion (WIM) and Response Spectra Techniques

Summary Information

Weigh-in-Motion (WIM) systems effectively record vehicle weight and axle layouts, supplying vital information for evaluating the performance of transportation infrastructure. A low-cost, long-life WIM system named Roadway Infrastructure and Vehicle Information System (RIVIS) was developed using surface-mounted accelerometers placed at the edge of the roadway to measure pavement movement in response to different vehicle types in a traffic stream. Data acquisition and power systems were installed at the roadside.  Two test efforts including laboratory and field deployment were undertaken to evaluate the performance of RIVIS. The laboratory test spanned 40 days from September to October 2021 and the field deployment was conducted using seven vehicles including passenger cars and pickup trucks on a 0.6 km long and 7.5 m wide research road at Virginia Tech in Blacksburg, Virginia.

METHODOLOGY

The developed RIVIS V1.0 included: sensors (SEN); a data acquisition unit (DAQ); a power supply (PSP); a power source (PSO); and data storage media (DSM). RIVIS V1.0 underwent laboratory testing using a third-party pavement testing apparatus designed to replicate the successive loads of a chain of moving axles. A complete field deployment trial encompassed six passes per sensor for each vehicle. Data was collected at a 1 kHz sampling frequency during each vehicle trial and processed using frequency domain analysis and regression analysis employing linear regression. The frequency domain analysis and regression analysis evaluated the performance of RIVIS in pavement response as well as the sensitivity to various vehicle types.

FINDINGS

  • The estimated capital and installation cost of RIVIS V1.0 was $4,487 per-node (as the simplest functional configuration) indicating an approximate 73 percent saving as compared to the existing WIM system with reported per-node costs of $15,000 and $15,250.
  • The system requires no special equipment or infrastructure changes and can be installed by a single person in about an hour, which decreases both monetary and opportunity costs.
  • Frequency domain analysis revealed that the bandwidth of region of interest (ROI), which is a relevant measurement range, was directly related to the bandwidth of pavement response frequencies generated by the vehicles, which could be useful for vehicle identification.
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