Effective Coordination with Towing Companies for Incident Response and Clearance

Tow truck operators are directly exposed to traffic when responding to incidents. In addition, stalled vehicles on the highway can hinder safety and operations on the highway and can create a risk of secondary incidents. Fast and effective removal of stalled vehicles on the highway can improve traffic operations and safety for tow truck operators and all users of the transportation system. The objectives of this research study are to synthesize existing department of transportation (DOT) practices regarding coordination with towing companies and to identify potential collaboration and training opportunities that will improve towing worker safety as well as traffic safety by improving incident response and clearance. The research methodology to meet this objective includes a literature review, survey, and coordination with the tow trucking industry, specifically the Missouri Tow Trucking Association (MTTA). Results indicate that training programs (26 responding DOTs) and coordination with the state towing association (23 responding DOTs) are the strategies most used by responding DOTs for partnering with the towing industry. Eight responding DOTs have implemented a Towing Recovery Incentive Program (TRIP) that provides incentive payments for towing companies to clear incidents within a specified timeframe. DOTs have found TRIPs to be beneficial in clearing incidents sooner. During an informal focus group as part of their monthly meeting, MTTA provided feedback on various topics, such as communication needs, interest in training, and the need for regulations that improve the quality of tow operators. The research identified potential opportunities for MoDOT and the State of Missouri to enhance its coordination practices with MTTA, such as including the towing industry in the planning process for major projects, implementation of regulations for requirements of tow operators, and partnering to strategize on how to best manage incidents involving electric vehicle fires.

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Report number: cmr 25-014
Published: September 2025

Project number: TR202514

Authors: Henry Brown, Carlos Sun, and Zhu Qing  

Performing organization: University of Missouri-Columbia

Assessment and Repair of Prestressed Bridge Girders Subjected to Over-height Truck Impacts

This research investigates the impact of over-height vehicle collisions on prestressed concrete bridge girders and explores effective repair strategies to restore their structural integrity. The study addresses a critical concern in bridge resilience, as vehicle impacts can cause varying degrees of damage and severe prestressing strands which compromise girder flexural strength and overall safety. A comprehensive approach was employed, integrating numerical modeling and experimental testing to assess damage mechanisms and evaluate the effectiveness of different repair techniques. Key findings include the determination of equivalent static force for semi-tractor trailers and rigid objects. Shear failure was identified as the dominant failure mode of prestressed concrete girders under impact loading. Additionally, accidental lateral eccentricity was found to reduce flexural resistance, necessitating a 15% reduction factor in AASHTO LRFD guidelines. A practical technique for measuring residual prestress forces was developed and validated with an experimental test and found to be conservative by 9.4%. Repair methods using mechanical strand splicing successfully restored up to 95% of the original strength for strand losses ranging from 17% to 33% using innovative confinement techniques. Moreover, externally bonded carbon fiber-reinforced polymer (CFRP) repairs fully restored flexural strength for up to 33% strand loss, with an additional strength reserve of 15%–23%.

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Report number: cmr 25-013
Published: September 2025

Project number: TR202011

Authors: Haitham AbdelMalek, Francis Ashun, Mohamed Elshazli, Mohanad Abdulazeez, Ahmed Gheni, Ahmed Ibrahim, and Mohamed ElGawady

Performing organization: Missouri University of Science and Technology

AI-Enabled Vision System for Intersection Analytics

This project developed and demonstrated an AI-enabled vision system for intersection analytics capable of automatically generating Turning Movement Counts (TMCs) and integrating them with Signal Phase and Timing (SPaT) data to evaluate traffic signal performance. Using existing Missouri Department of Transportation (MoDOT) CCTV (Closed Circuit Television) infrastructure, the system eliminated the need for manually placed detection zones and significantly reduced the labor traditionally required for data collection.

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Report number: cmr 25-012
Published: September 2025

Project number: TR202506

Authors: Yaw Adu-Gyamfi and Muturi Turner

Performing organization: University of Missouri-Columbia

Traffic Disruption-free Bridge Inspection Initiative with Robotic Systems

The current practice of bridge inspection requires the use of snooper trucks and, when parked on bridges, the control of passing traffic, thus causing an operation safety concern for both passengers and inspectors. It also leads to inherently subjective and qualitative results. This pooled-fund study aims to develop case studies on the deployment and performance of Bridge Inspection Robot Deployment Systems (BIRDS) developed in the INSPIRE University Transportation Center for faster, safer, cheaper, and more quantitative bridge inspection with minimum impact on traffic flow. To this endeavor, an automated bridge preservation framework was envisioned to integrate advanced robotics, remote sensing, and nondestructive testing into the practice of visual inspection and associated maintenance. By evaluating the advanced technologies at 59 bridges in diverse types, age groups, and geographical locations, the best practices of the technologies were summarized in inspection protocols and guidelines using commercial drones, structural crawlers, and custom-built hybrid uncrewed vehicles. Vision-based instance segmentation via machine learning efficiently and effectively detected, located, and quantified weld defects in steel bridges, including cracks, debonding, and cavity, in real time. Topside and underside deck inspections were compared to ensure the reliability of traffic disruption-free bridge inspection from the underside of the bridge deck. By combining flying, traversing, and crawling capabilities, the award-winning invention - BIRDS offered a versatile robotic solution that addressed the limitations of commercial drone technologies. Its ability to seamlessly transition between aerial and ground-based inspection modes ensured a comprehensive coverage of bridge structures. This innovation enabled both global visual monitoring and local detailed inspection using remote sensing (e.g., microscope imager and laser scanner) and nondestructive testing (e.g., ultrasonic metal thickness gauge) for the detection and quantification of bridge surface and substrate defects. Since a limited type and number of defects were observed from the selected bridges, more bridges should be inspected to collect big data required in machine learning to develop decision-making support tools toward data-driven bridge asset management.

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Report number: cmr 25-011
Published: September 2025

Project number: TR202004

Authors: Genda Chen, Zhenhua Shi, Son Nguyen, Mohammad Hossein Afsharmovahed, Peter Damilola Ogunjinmi, Ying Zhuo

Performing organization: Missouri University of Science & Technology

GFRP Reinforced Bridge Barriers: Experiment Testing

The reported work includes the experiment testing of glass fiber reinforced polymer (GFRP) and steel reinforced concrete bridge barriers. A total of four reinforced concrete barriers were prepared, including three GFRP reinforced barriers and one mild steel reinforced barrier, and cast on two concrete slabs. Impact testing was conducted using a cart with weight and a long straight sled system. The force, displacement, and strain data were measured. The results demonstrated that GFRP is fully capable of withstanding impact loads that could occur in real-world scenarios.

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Report number: cmr 25-010
Published: July 2025

Project number: TR202319

Authors: Congjie Wie, Manish Kumar Gadhe, John J. Myers, and Chenglin Wu

Performing organization: Missouri University of Science & Technology

Shear Wave Velocity Measurements

The Missouri Department of Transportation (MoDOT) commissioned SCI Engineering, Inc. to investigate cost-effective, non-intrusive geophysical methods for determining time-averaged shear wave velocity (Vs) profiles to a depth of 100 feet, based on anticipated updates to AASHTO seismic site classification specifications. Following a comprehensive literature review, eight candidate methods were identified. Of these, four methods—Active Multichannel Analysis of Surface Waves (Active MASW), Passive Multichannel Analysis of Surface Waves (Passive MASW), Active Refraction Microtremor (Active ReMi), and Passive Refraction Microtremor (Passive ReMi)—were selected for field testing based on their practicality and effectiveness.

Field evaluations were conducted at three sites: the SCI Office in O’Fallon, Illinois; the I-270 Chain of Rocks Bridge; and the MLK Connector in Illinois. The sites were selected based on access, availability of existing groundtruth subsurface soil information, as well as representing a variety of subsurface profiles.  Various geophone spacings and array configurations were tested. Performance metrics included depth of investigation, ease of deployment, data quality, and interpretability. Results demonstrated that combining Active and Passive MASW methods offered the most reliable and practical solution, providing consistent results, minimal operational complexity, and shared equipment and software requirements.

SCI Engineering developed a comprehensive User Manual and conducted field demonstrations to train MoDOT personnel in the acquisition, processing, and interpretation of MASW data. Adoption of these methods will streamline MoDOT’s seismic site classification processes, align practices with forthcoming AASHTO requirements, and enhance MoDOT’s internal technical capacity.

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Report number: cmr 25-009
Published: June 2025

Project number: TR202403

Authors: Evgeniy "Eugene" Torgashov, Neil Anderson, and Thomas J. Casey

Performing organization: SCI Engineering, Inc.

Testing Survey Methods for Detecting Bats Roosting in Bridges

Bats are a critical component of our natural world, and many species are at risk. Protecting roosting habitat is one way we can help conserve a variety of species. Although many bats use natural roosts, a growing number are adapting to anthropogenic structures due to habitat encroachment. In this study, we tested methods for detecting bats using bridges as roosts. We visited 20 bridges four times each to test six daytime methods (human visual and hearing, use of an acoustic detector, use of an agitator to induce bat vocalization, visual search with a spotlight, use of a thermal camera, and a borescope) and three evening emergence methods (human visual, thermal camera, and acoustic detector). Occupancy modeling revealed that the most effective way to document bat use at bridges is with an acoustic detector during evening emergence. This was followed by the use of thermal cameras during evening emergence, and the third best model was use of thermal cameras during the day. Surveying longer did not increase detectability in any of the top models. Based on our findings and suggestions in guidance documents for detecting bats in bridges, the first step is to survey a bridge with a spotlight, listening for bat vocalizations, and noting smell. If bats are not detected during the day, using acoustic detectors and thermal cameras during emergence will determine if bats are using bridges and can provide additional data if they are documented using them during the day.

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Report number: cmr 25-008
Published: June 2025

Project number: TR202420

Authors: Piper L. Roby, Crystal Birdsall, and Timothy Divoll

Performing organization: Copperhead Environmental Consulting, Inc.