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Project

#386 Deterioration Digital Twins of Commercial Trucks and Trailers for Targeted Inspection and Maintenance


Principal Investigator
Pingbo Tang
Status
Active
Start Date
July 1, 2022
End Date
June 30, 2023
Research Type
Applied
Grant Type
Research
Grant Program
FAST Act - Mobility National (2016 - 2022)
Grant Cycle
2022 Mobility21 UTC
Visibility
Public

Abstract

The proposed project intends to enhance the safety of fleets of commercial trucks and trailers without compromising mobility and operating costs. Various agencies inspected safety components, such as tires, brakes, and lights through planned or roadside inspections. Targeting these inspections toward safety-critical vehicles and components can ensure safety without losing mobility. We partner with two Pennsylvania firms to create vehicle deterioration digital twins that use inspection histories to guide effective telematics for predictive operations of truck fleets.    
Description
The proposed project aims to enable targeted inspection and maintenance of commercial tractors and trailers fleets by a vehicle deterioration digital twin that integrates historical inspection records and real-time sensor data for predicting high-risk vehicles and components. Such a vehicle deterioration digital twin should support the prioritization of vehicles and vehicle components for inspection and maintenance to balance fleets’ safety, mobility, and maintenance costs. Around the world, periodic and unannounced inspections of commercial trucks and trailers ensure vehicle safety and acceptable emissions. These programs have inspectors manually check vehicle safety components, such as brakes, tires, and lights. However, only 13 out of 50 states have mandatory safety inspection programs. State legislatures have been eliminating these programs or making them less frequent due to the perception that they waste resources. Unfortunately, our study found that 15% of vehicles would fail inspections if they did not have maintenance done at the inspection time.
The low efficiency of vehicle safety inspection programs is due to the lack of methods that help prioritize millions of commercial vehicles. In practice, planned and unannounced roadside inspections lack real-time guidance for spotting high-risk vehicles from many. As a result, limited enforcement personnel could hardly target their efforts towards critical vehicles. Increasing the frequencies of inspections without targeted efforts would result in more checks of vehicles with lower risks, wasting the limited resources and reducing mobility. 
Effective use of historical data and real-time sensor technologies can address these challenges by predicting high-priority vehicles based on inspection and operation histories. Fleet owners claim to have centrally managed inspection regimes that proactively identify and fix problems. In past work, we leveraged inspection records for vehicle miles traveled estimates to analyze Pennsylvania’s milage-based user fees [1]. We developed methods that automatically reconstruct deterioration models of mechanical systems (e.g., nuclear plants) to help predict components that need inspection or maintenance [2]–[4]. These “Deterioration Digital Twins”  reconstructed from multiple data sources can support targeted inspections and maintenances of engineered systems.  
Aiming at reconstructing deterioration digital twins of commercial trucks and trailers, we are building a data analytics architecture to hold commercial vehicle tractor and trailer inspection data. We are using this architecture to assess the effectiveness of state safety inspection programs for commercial trucks and trailers. The integrated data sources include 1) inspection records accumulated by industry partner (CompuSpections), PennDOT, and Federal Motor Carrier Safety Administration (FMCSA) [5], and 2) telematics data contributed by an industry partner (Truck-Lite). The results indicate that vehicle safety inspection programs have significant variations in the number of inspections needed for identifying one problematic vehicle. 
This project proposes to continue the ongoing collaboration between industry, state, and federal inspectors to reduce less informative inspections for improved mobility. We will extend our ongoing inspection and telematics data analytics efforts to build deterioration digital twins of commercial trucks and trailers. Another focus is to use deterioration digital twins to generate inspection and maintenance plans that target high-risk vehicles and vehicle components (e.g., brakes as identified in the ongoing work).    
Timeline
November 2021 – This proposal submitted
December 2021 – Complementary PITA proposal submitted
July 2022 – Joint Mobility21/PITA Project Starts
Task 1 (Generating Deterioration Digital Twins): July – December 2021
Task 2 (Generating Inspection and Maintenance Plans): August 2022-May 2023
Task 3 (Discussions with Agencies): has already begun - June 2023
June 2023 – Mobility21 Project Ends
December 2023 – PITA Project Ends
    
Deployment Plan
For this project, we will collaborate with the following organizations:
CompuSpections, LLC – Compuspections, based in Valenica, PA, is a small business that provides web-based inspection record management and reporting software for inspection stations (ranging from small garages to large dealerships).  Funded by an ongoing Mobility 21 project, we have worked with them for 1 year on our current safety inspection studies of commercial trucks and trailers and know their data architecture well. Their system records all PA safety inspection criteria, regardless of pass or fail status, and data for some fields are comprehensive, including information such as all actual tire tread measurements (in units of 1/32 of an inch) at the time of inspection, all maintenance work done to meet state inspection program requirements, final pass/fail status, etc. We expect to collect state-mandated safety inspection data for a significant number of trucks and trailers in the state. CompuSpections has provided us with a large amount of in-kind data and expertise to frame this proposed study.  Given their role in the industry, they have also helped us build relationships with other interested parties such as PennDOT, various state senators, and representatives, the Pennsylvania Automotive Association (PAA), the annual IM Solutions conference, CITA (a global alliance of companies in the safety and emission inspection industry), etc.  CompuSpections will be providing in-kind support in the form of all of their historical data related to truck and trailer inspections, as well as substantial staff time in extracting, providing, and supporting our work with the data (see support letter).
Truck-Lite Co., LLC – Truck-Lite is a subsidiary of Clarience Technologies LLC, a truck safety component and system company having a global R&D center located in Pittsburgh. Truck-lite has been making lights for medium and heavy-duty trucks for over 60 years and has recently entered the telematics space for commercial trucking through its Road Ready system.  The Road Ready system (https://www.roadreadysystem.com) is a new hardware and services platform that collects data from various onboard sensor components (including all safety components, not just lights) on trucks and trailers. This platform communicates the data and status information to the driver and centrally to fleet managers. For example, a typical trailer has about 20 lights, and any one of them being inoperable results in a failed inspection. Clarience Technologies, LLC is co-owned by a company that owns and manages a national fleet of 50,000 trucks subject to the patchwork of DOT and state inspections mentioned above. Truck-Lite intends to leverage its connections with company partners to obtain access to several years’ worth of fleet inspection data to be used in this analysis. Truck-lite will be providing in-kind support in terms of staff support time, access to the Road Ready platform, etc. (see support letter).
PA Department of Transportation (PennDOT) – We have negotiated a data usage agreement with PennDOT that allows us to purchase a complete list of all registered vehicles (including commercial trucks and trailers) currently in the state as of the time of the request. The information available includes the vehicle identification number, zip code, county, type of vehicle, etc. We will also attempt to work with them and the Pennsylvania State Policy to identify interested parties for our system’s pilot “fleet dashboard” (ongoing at the time of proposal submission).
CITA - CITA is the international association of public and private sector organizations actively involved in mandatory road vehicle compliance. While much of their members’ activities are focused on passenger vehicle programs, there is a significant cross-section of members whose operations span commercial vehicles and are interested in the results of this work. We are also hopeful of getting a cash donation from CITA in support of this work.    
Expected Accomplishments and Metrics
In this one year project, we will:
•	Reconstruct deterioration models of commercial trucks and trailers based on historical data on the components most likely to lead to a tractor-trailer safety inspection failure from state and eventually internal corporate records, with an integrated analysis of some real-time sensor logs from a telematics system of Truck-Lite
•	Help improve the telematics effectiveness of cutting-edge sensing and communications technologies to monitor safety component status in trucks continuously. 
•	Help prioritize trucks, trailers, and safety-critical components for inspection and maintenance based on the deterioration digital twins generated from historical inspection records and sensor logs of telematics systems
•	Begin necessary discussions with agencies about regulatory relief for fleets incorporating advanced telematics to improve freight mobility by targeting inspection efforts to vehicles and components predicted by the digital twins as high-risk items.
We believe the combination of parties and technologies can lead to a new paradigm for tracking commercial vehicle safety, and more importantly, save time and money for fleet owners. 
We envision the metrics of this project to be:
•	Number of inspection records available and processed
•	Percentage of inspections that find trucks and trailers that are posing high operating risks
•	Number of safety-critical components able to be effectively monitored by the system
•	Number of external presentations given
•	Number of state agencies in discussions about using a telematics system
•	Number of papers published
    

Individuals Involved

Email Name Affiliation Role Position
bethannh@andrew.cmu.edu Hockenberry, Beth Carnegie Mellon University Other Staff - Business Manager
ptang@andrew.cmu.edu Tang, Pingbo Carnegie Mellon University PI Faculty - Untenured, Tenure Track
chenyuyu@andrew.cmu.edu Yuan, Chenyu Carnegie Mellon University Other Student - PhD

Budget

Amount of UTC Funds Awarded
$100000.00
Total Project Budget (from all funding sources)
$200000.00

Documents

Type Name Uploaded
Data Management Plan Data_management_Plan_for_Mobility21_Truck_lite_2022_PF7piM8.docx Nov. 19, 2021, 5:21 a.m.
Project Brief Project_PowerPoint_Summary_2022.pptx March 2, 2022, 11:28 a.m.

Match Sources

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Partners

Name Type
CompuSpections, LLC Deployment Partner Deployment Partner
Truck-Lite Deployment Partner Deployment Partner