POSTER 19-01: IMPROVED DISASTER MANAGEMENT THROUGH AUTOMATED DAMAGE ASSESSMENT USING UNMANNED AERIAL VEHICLES (UAVS)

IMPROVED DISASTER MANAGEMENT THROUGH AUTOMATED DAMAGE ASSESSMENT USING UNMANNED AERIAL VEHICLES (UAVS)


PI: Rami J. Haddad

Co-PI(s): 

Institution(s): Georgia Southern University


Abstract

Natural disasters cause devastating effects on transportation networks by causing significant damage and obstruction on frequently traveled roads. This report describes the design and implementation of an automated Unmanned Aerial Vehicle (UAV) based damage management using convolutional neural networks (CNNs). This system utilizes image processing and deep learning techniques to assess damages to the state’s transportation system. The assessed damages are automatically geo-tagged to an ArcGIS map compatible with the Georgia Department of Transportation (GDOT) GIS standards. This UAV-based intelligent disaster management system enables the GDOT to optimize its disaster management and recovery efforts. Additionally, this system provided live streaming of the UAV’s video feed to an RTMP server, enabling the first responders to assess damages. The system is composed of hardware and software components. In addition to the UAV platform, a customized application was developed using Python and MATLAB software to automate and centralize the operation of this system. The application included managing, sampling, classifying, and ArcGIS map tagging of the UAV-generated video streams. The simulation results of this system, using a library of images, have shown that the system could classify clear vs. damaged roads with an accuracy of over 99%. However, when the classification categories increased to six, damaged roads, clear roads, blocked roads, boat in roads, fallen power lines, and flooded roads, the average classification accuracy dropped to 74.1%. This was mainly due to the relatively small size of the library of disaster-related images.


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POSTER 19-11: SAFETY AND ILLUMINATION OF RURAL AND SUBURBAN ROUNDABOUTS PHASE II

PI: Michael Rodgers

Co-PI(s): 

Institution(s): Georgia Institute of Technology


Abstract

This project focused on establishing the relationship between the presence/absence or levels of illumination and other geometric and traffic characteristics on nighttime safety at rural and suburban roundabouts. Eighty roundabouts from 37 counties across Georgia were selected to provide a wide range of conditions in terms of illumination layout, illumination levels, number of legs, number of circulating lanes, daily entering volumes, approach speeds, etc. for field measurements of illumination levels. Urban roundabouts with significant pedestrian activity were specifically excluded. Field data collection at each site included both direct measurements of illumination levels as well as a civil site survey to verify the geometric characteristics of the roundabout and were conducted by measurement teams from Georgia Institute of Technology and Georgia Southern University. The resulting data were processed, joined, and aggregated to the individual site level and used to establish statistical relationships between observed nighttime crash rates, severity, and crash types (e.g. single vs. multiple vehicles, impaired drivers, etc.) and underlying geometric factors and measured illuminance levels. The variation in observed crash rates were modeled against known parameters of the roundabouts to develop a predictive model as to how single vehicle nighttime crash rates were impacted by illumination and other factors. As expected, multiple vehicle crashes showed no statistically significant dependence on illumination levels as the vehicles themselves, through their head- and taillights, are important contributors to nighttime visibility at the roundabout. This was not the case for single vehicle crashes. Single vehicle crashes were shown to increase for 3-leg roundabouts for illumination values less than 5 lux. No such trend was observed in either 4 or 5-leg roundabouts and these sites showed no statistically significant variation in nighttime single vehicle crash rates at any level of illumination. An overarching conclusion of the study is that there was no observed evidence of illumination values in excess of 5 lux resulting in a statistically significant reduction in nighttime crash rates for rural and suburban roundabouts. These results suggest that for rural and suburban roundabouts with no significant pedestrian volumes, illumination values significantly lower than current standards may still prove effective as a safety treatment and that, in the absence of a need to protect pedestrians or cyclists at nighttime at a particular location, a reduction in lighting levels or the use of passive retroreflective safety treatments may be a cost-effective treatment.


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POSTER 19-14: EXTRACT HORIZONTAL AND VERTICAL ALIGNMENT INFORMATION FROM PUBLIC DATA AND OPEN API

EXTRACT HORIZONTAL AND VERTICAL ALIGNMENT INFORMATION FROM PUBLIC DATA AND OPEN API


PI: Xiaoming Yang

Co-PI(s): Russell Krenek, and David Scott

Institution(s): Georgia Southern University


Abstract

An open-source program was developed for extracting horizontal and vertical alignment information of roadways using public data and open APIs (application programming interface). The program employs unsupervised analysis to detect, segment, classify, and measure curves and tangents along a given route, based on the coordinates of the beginning and ending points. Erratic vertical grade data points at bridges were detected. A validation case is provided based on a 23.4-km Interstate highway route in Georgia. A visual inspection of the result showed that the program was able to detect and measure all horizontal circular curves along the sample route. Moreover, the program correctly identified the vertical curves and vertical tangents for more than 90% of the length of the route. Occasional inaccuracies in the vertical alignment analysis were observed, mainly at short segments near bridges. The program was developed in the R language. The complete source code of the program is publicly accessible via a dedicated GitHub repository.


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POSTER 19-17: CHARACTERIZING ALKALI-SILICA REACTION MITIGATION OF RECLAIMED ASH USING MICRO-X-RAY FLUORESCENCE

CHARACTERIZING ALKALI-SILICA REACTION MITIGATION OF RECLAIMED ASH USING MICRO-X-RAY FLUORESCENCE


PI: Kimberly Kurtis

Co-PI(s): 

Institution(s): Georgia Institute of Technology


Abstract

Over the past 80 years, concrete mixtures have become reliant on the use of fly ash to improve performance. The closure of coal power plants in the US has raised concerns about the supply of traditional fly ash. Fortunately, there are billions of tons of fly ash stored in solid waste disposal sites that can be easily accessed. However, current classification procedures are not suited to handle this variety of available ash and new specifications are needed on the usage of reclaimed fly ash to produce concrete mixtures with long-lasting performance. This study addresses this knowledge gap through experiments on samples made incorporating reclaimed fly ashes. Mortar bar samples were subjected to an aggressive and accelerated test to assess the alkali-silica reaction (ASR) mitigation potential of the reclaimed ashes. At the end of the test duration, Micro-X-Ray Fluorescence (MicroXRF) analysis was conducted to better understand transport of alkali into the microstructure and how it may lead to deleterious expansion due to ASR. The results showed that the length expansions of the reclaimed ash mortar bars were significantly lower compared to the reference OPC and inert filler samples. From the MicroXRF analysis, there was a range of magnitudes for surface concentrations and diffusivity coefficients in the reclaimed ash samples. This showed that it is not enough to look at diffusivity coefficient in isolation as surface concentration is also important factor in the resulting expansion. Overall, the results of this study suggest the potential of using reclaimed fly ashes for alkali silica reaction mitigation in concrete.


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POSTER 20-03: ADEQUACY OF DSRC IN 5.9 GHZ BAND FOR GDOT’S CONNECTED VEHICLE INFRASTRUCTURE

ADEQUACY OF DSRC IN 5.9 GHZ BAND FOR GDOT’S CONNECTED VEHICLE INFRASTRUCTURE


PI: Seungmo Kim

Co-PI(s): 

Institution(s): Georgia Southern University


Abstract

Vehicle-to-everything (V2X) communications are expected to take a critical role in a variety of transportation safety applications in connected and autonomous vehicle environment. However, Dedicated Short-Range Communications (DSRC), one of the representative technologies implementing the V2X communications, is encountering challenges due to the re-allocation of the 5.9 GHz spectrum by the Federal Communications Commission (FCC). The state of Georgia is leading the nation in the deployment of connected vehicle infrastructure with thousands of infrastructure units connecting vehicles based on DSRC. This project aimed at measuring the impact of the spectrum re-allocation on the performance of the Georgia’s connected vehicle infrastructure. The project’s particular technical focuses were to (i) model the performance of a DSRC system and (ii) design a protocol to improve the DSRC performance, under the FCC’s reform of the 5.9 GHz band.


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POSTER 20-22 ENHANCING AND GENERATING GDOT’S MUTCD CURVE SIGN PLACEMENT DESIGN WITH CURVE FINDER AND CURVE SIGN DETERMINATION

ENHANCING AND GENERATING GDOT’S MUTCD CURVE SIGN PLACEMENT DESIGN WITH CURVE FINDER AND CURVE SIGN DETERMINATION


PI: James (Yichang) Tsai

Co-PI(s): 

Institution(s): Georgia Institute of Technology


Abstract

Though curves represent only 5% of highway miles, they account for 25% of fatal roadway crashes. Thus, the MUTCD requires various warning signs to ensure safety on curves. GDOT?s current MUTCD-compliant curve sign design practice is labor-intensive and time-consuming, especially the determination of detailed curve geometry and the validation of the sign placement which must be done for only one curve at a time. Therefore, there is an urgent need to enhance this practice. The objectives of this project are to enhance the GDOT curve sign design practice by automatically batch processing multiple curves at once to extract sensor data including curve geometry, BBI, speed limit, and GPS location. This information will then be used compute the necessary advisory speed for the curve, generate MUTCD-compliant curve signs in a tabular format, and visualize these signs for streamlined implementation by GDOT. This processing will be done using an application previously developed by Georgia Tech for high friction surface treatment location. This project can save time, money, and effort for GDOT as well as increase confidence in the accuracy of the curve sign placement design on a network level.


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POSTER 20-28: DYNAMIC DIFFUSION GRAPH CONVOLUTIONAL NETWORKS FOR NETWORK TRAFFIC ESTIMATION

DYNAMIC DIFFUSION GRAPH CONVOLUTIONAL NETWORKS FOR NETWORK TRAFFIC ESTIMATION


PI: Jidong J Yang

Co-PI(s): Sonny Kim, Stephan Durham, and Mi Geum Chorzepa

Institution(s): University of Georgia


Abstract

Network traffic estimation and forecasting is fundamental to transportation systems analysis and decision making in planning, design, and operation of such systems. The rapid development of intelligent transportation systems (ITS) and emerging avant-garde monitoring technologies have made traffic data collection more convenient and efficient in support of decision making at various levels. In practice, permanently located continuous count stations, complemented with portable traffic counters, are typically used for traffic data collection. However, due to budget and personnel constraints, only a limited number of segments in the road network are equipped with sensors. In other words, the network traffic flows are only partially observable, which may lead to unexpected consequences due to uncertainty and associated biases. In this study, we introduces a novel graph-based approach for estimating network-wide traffic volumes from limited sensor locations.


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POSTER 21-08: STUDY ON SPECTRUM OPTIONS FOR GDOT’S CONNECTED VEHICLE INFRASTRUCTURE

STUDY ON SPECTRUM OPTIONS FOR GDOT’S CONNECTED VEHICLE INFRASTRUCTURE


PI: Seungmo Kim

Co-PI(s): 

Institution(s): Georgia Southern University


Abstract

To investigate the feasibility of operating the existing DSRC devices in unlicensed bands, e.g., industrial, scientific and medical (ISM) bands and to analyze the technical impacts of the transition from DSRC to C-V2X in the spectrum of 5.895-5.925 GHz, compliant with the recent regulatory change by the FCC.


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POSTER 22-19: REMOTE BRIDGE HEALTH MONITORING FOR SCOURING USING COST-EFFICIENT SENSING TECHNOLOGY

REMOTE BRIDGE HEALTH MONITORING FOR SCOURING USING COST-EFFICIENT SENSING TECHNOLOGY


PI: Tien Yee

Co-PI(s): Jidong Yang, Metin Oguzmert, and Mahyar Amirgholy

Institution(s): Kennesaw State University & University of Georgia


Abstract

Scouring is a major concern for highway bridges and is known to be a common cause of road bridge failures in the United States. Bridges are often inspected for scouring periodically and after large storm events to determine the health and safe operation of bridges. The general practice of manual measurements is employed by GDOT personnel after the storm events to determine the extent of scouring on bridge piers. While manual measurements are good for assessment after storm events, however, there are two disadvantages to this practice. Firstly, manual measurements require that the GDOT inspection crew be on standby for deployment immediately after a storm event and depending on the number of personnel that is available, may not be able to quickly perform the inspection on the majority of the bridges. Secondly, without prior knowledge of the extent of scour depths during floods, the post-flood inspection may be a safety concern for GDOT engineers and inspection crews. Commercial instrumentations are often expensive and may not be easily customizable to fit the needs of GDOT. There is a need for a less expensive and safe alternative near real-time bridge health assessment due to scouring. The goal of this project is to firstly produce a cost-efficient system for remote bridge health monitoring using existing technology and secondly make use of the data collected from the system to optimize operations within GDOT bridge monitoring units. Currently, the research has produced a lab-tested system shown in the poster. This system is poised to be deployed in the field for data collection.


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POSTER 22-28: 5.9GHZ INTERFERENCE RESILIENCY FOR CONNECTED VEHICLE INFRASTRUCTURE

5.9GHZ INTERFERENCE RESILIENCY FOR CONNECTED VEHICLE INFRASTRUCTURE


PI: Billy Kihei

Co-PI(s): 

Institution(s): Kennesaw State University


Abstract

Currently, there are not enough Wi-Fi devices operating around U-NII-4 Channels 180 to 184 to understand the impact to Connected Vehicle (CV) applications. Therefore, further research is needed to deploy a density of real-world devices in the field to understand the impact of: Co-channel interference (within the 5.9GHz Safety Band), Adjacent channel interference (above and below the 5.9GHz Safety Band). Studies to date do not consider a saturation of real-world interference devices in the unlicensed Wi-Fi bands below and above the 5.9GHz Intelligent Transportation Systems (ITS) safety band. This is due to an unavailability of consumer Wi-Fi devices in the lower 40MHz of the previous 5.9GHz Dedicated Short Range Communications (DSRC) spectrum, and a low penetration of consumer Wi-Fi devices in the new Wi-Fi 6E spectrum. The objective of this project is to assess the resiliency of CV applications to interference by reporting real-world CV performance and develop methods for detecting and mitigating interference with GDOT deployed CV devices.


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