Integration and Operation of an Advanced Weigh-in-Motion (A-WIM) System for Autonomous Enforcement of Overweight Trucks

Overview

Roadways in New York City handle substantial daily traffic throughout different boroughs. Trucks have been an integral part of the freight movement network in distributing goods and services to various communities; however, a percentage of these trucks are often overloaded beyond legal load limits. The Brooklyn-Queens Expressway (BQE) that connects two boroughs suffers from significant deterioration because of the existing environmental conditions exacerbated by a substantial number of OW trucks.

The New York City Department of Transportation (NYCDOT) has been planning to rehabilitate the bridge to accommodate future traffic volume and weight demands. Accordingly, the team closely worked with the NYCDOT and collected truck traffic and weight data to provide recommendations for future design or rehabilitation work on BQE bridges. The team learned that the average daily number of OW trucks is significantly higher, and the extent of the OW (or OW tonnage) is substantially heavier than the national average.

Our team also found that current OW enforcement practices at the weighing stations and by the weight enforcement officers using portable scales would capture only a small fraction of the OW trucks.  For example, the number of vehicles screened by four weighing stations in NJ was 1,006,749 in 2009, and only 0.142% (1,430 trucks) of screened trucks were overweighted and ticketed.  However, the actual OW percentage along the corridors near four weighing stations in NJ was 6.4%, based on the WIM data.  This confirms that the current OW enforcement practices would only capture less than 3% of total OW trucks. Therefore, a more practical and efficient OW enforcement scheme would be needed to discourage the trucking industry from overloading their fleets.

Research Objectives & Deliverables

The ultimate objective of this project is to assist and support the NYCDOT in establishing the legislation to operate the autonomous OW enforcement system and extend the service life of the BQE corridor. The team will utilize two testbeds on both sides of the BQE corridor to develop the guidelines and specifications for the operation of the OW enforcement system in an urban area.  The deliverables will include, but not be limited to, an updated NYCDOT in-house calibration procedure and methodology to assure weight accuracy, the attainable accuracy target under current roadway conditions, and updates of service life predictions for BQE bridges.  

The scope of work will include the following tasks:

Task 1 – Establishment of a new smart roadway testbed at the south part of the BQE corridor 

Task 2 – Implementation of automated license plate recognition (ALPR) system and other available technologies

Task 3 – Practice of autonomous enforcement

Task 4 – Evaluation of the impact of OW truck enforcement on load rating and reliability assessment of BQE structure

Task 5 – Technical support to establish the legislation for the operation of the autonomous enforcement at BQE

Deliverables include the final report and technical memorandum(s) for the new smart roadway testbed on BQE, deployment of SW-based ALPR system, etc.

Personnel

Hani Nassif

Hani Nassif

PRINCIPAL INVESTIGATOR

Peng Lou

Peng Lou

CO-PRINCIPAL INVESTIGATOR

Chaekuk Na

Chaekuk Na

CO-PRINCIPAL INVESTIGATOR

Kaan Ozbay

Headshot of Kaan Ozbay

COLLABORATOR

Thales Couto Braguim

Thales Couto Braguim

STUDENT RESEARCHER

Principal InvestigatorHani Nassif
Funding SourceNYCDOT In-Kind Matching (up to $1,000,000)
Total Project Cost$125,000
USDOT Award #69A3551747124 
Implementation of Research OutcomesThe team will implement an in-house calibration procedure and methodology and help implement legislation to operate an automated enforcement system at NYCDOT.
Impacts/Benefits of Implementation

This implementation will help to extend the service life of infrastructure (good to owner/agency), provide safe infrastructure to the taxpayer (good to user), and promote resiliency of infrastructure (good to society).

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