Author: sshao45

PI: James (Yichang) Tsai

Co-PI(s):  

Institution(s): Georgia Institute of Technology

---

Abstract

A disproportionally high number of fatal crashes (25%) occur on horizontal curves, even though curves represent only a fraction of the roadway network (5% of highway miles). MUTCD requires various horizontal alignment warning signs to ensure roadway safety on curves. However, current transportation agencies? practices for inventorying existing curve signs are typically a costly manual procedure. This report presents automatic curve sign detection (ACSD) using low-cost mobile devices such as smart phones, machine learning, and crowdsourcing to develop a live curve sign inventory. This inventory can be used to analyze MUTCD curve sign compliance for safety improvements. Phase II of this research project focuses on 1) validating the curve sign computation accuracy, 2) recommending data storage and management alternatives, and 3) recommending a methodology for MUTCD curve sign compliance analysis (MCSCA), and 4) presenting a roadmap for implementing the proposed methodology. Based on tests performed in Phase II, the proposed triangulation method, using the images and GPS data collected using smartphones, can achieve accuracy within 10 meters for most cases. However, some cases can have an error greater than 15 meters. Error cases typically occur when there is a significant change in vertical alignment or a rough roadway surface. Future refinement on the triangulation method that accounts for the vehicle?s pitch angle is recommended. Additionally, data storage and management alternatives and a methodology for MUTCD curve sign compliance analysis are recommended. Finally, a roadmap for implementing the proposed ACSD, live curve sign inventory, and MCSCA is presented.

---

Please comment below with any statements or questions you may have. Also let GTI if you would be interested webinars or presentations on similar topics.

PI: Karen Marie Johnson

Co-PI(s): John Marshall, jmarshall32@gsu.edu

Institution(s): Georgia State University

---

Abstract

The right-of-way acquisition process is time-consuming and complex, particularly when located over navigable waters. State constitutional provisions, state statutes, and case law establish public and private rights and ownership in waters and the submerged lands. Opportunities exist to improve the right-of-way acquisition process for highways crossing navigable waterways, reducing the possibility of oversight or confusion that could result in multiples agencies and private property owners appearing to have a legal right of ownership in potentially overlapping portions of the right-of-way area with no clear way to sort it out beyond a court proceeding. This project provides six recommendations to improve timely identification of projects crossing state navigable waters and prevent project delays.

---

Please comment below with any statements or questions you may have. Also let GTI if you would be interested webinars or presentations on similar topics.

PI: Jun Liu

Co-PI(s): Praveena Penmetsa, Ph.D. Timothy E. Barnett, P.E., PTOE Xiaobing Li, Ph.D. 

Institution(s): University of Alabama

---

Abstract

Non-traversable medians consistently yielded improved safety performance compared to other median types such as undivided, 4-feet flush medians, and two-way left-turn lane cross-sections. However, constructing non-traversable medians can be costly. The goal of this study is to 1) examine the safety performance of existing rural four-lane roadways with above-mentioned four median types in Georgia by using Safety Performance Functions (SPFs) and Crash Modification Factors (CMFs), and 2) develop criteria to determine under what conditions these four median types yield maximum safety benefits while considering construction costs. Data were refined and integrated from multiple sources such as from the Georgia Department of Transportation (GDOT), Federal Highway Administration (FHWA) and Google Maps. The Annual Average Daily Traffic (AADT), truck percentage, and access point density were considered as key independent variables in SPFs. The CMFs were estimated to show the effectiveness of a cross-section compared to the base- four-lane undivided roadway. Note, the SPFs and CMFs developed in this study did not consider the speed limit. The key results show that the estimated CMFs vary across different values of variables, indicating that the safety effectiveness of a treatment is likely to vary across different roadway and traffic conditions. Specifically, the segments with non-traversable medians outperformed the other three segment types across all AADTs, truck percentages, and access point densities, except at very low AADT under 5,000 where the 4-feet flush medians appear to have improved safety. The research team estimated average annual crash reductions (compared with undivided roadways), which were converted into monetary values using the average crash costs by severities. The safety benefits and project construction costs were used to estimate benefit-cost ratios (BCRs). Simulations were suggested in situations where safety solely did not help in the decision-making process of identifying cost-effective median type for rural four-lane roadways. It is highly recommended that decision-makers or practitioners use the estimated safety benefits from this study and the construction costs of a specific highway project to estimate BCRs for recommendations of the cross-section type.

---

Please comment below with any statements or questions you may have. Also let GTI if you would be interested webinars or presentations on similar topics.

PI: Samuel Coogan

Co-PI(s): Makhin Thitsa

Institution(s): Georgia Institute of Technology, Mercer University

---

Abstract

Diverging Diamond Interchanges (DDI) are a relatively new interchange design that moves traffic to the opposite side of the road at a freeway overpass. This allows vehicles to enter and exit the freeway via unimpeded left-hand turns. This project aims to develop traffic prediction and control algorithms to optimize traffic flows at Georgia?s DDIs and their adjacent intersections. Through robust data-driven methods, our team was able to develop traffic prediction algorithms for the coordinated control of the traffic flow networks around the DDIs. The algorithm?s predictions are especially valuable for signal timing optimization purposes on the days of unusual traffic trends where nominal parameters will fail to predict the future traffic flows. Our study shows that the use of the algorithm can save approximately 70 to 350 hours of delay, amounting to approximately $1,000 to $5,000 per day in travel time savings at the four intersections of the DDI in the network when flow is atypical.

Project Video

---

Please comment below with any statements or questions you may have. Also let GTI if you would be interested webinars or presentations on similar topics.

PI: Junan Shen

Co-PI(s): Yunfeng Chen, Purdue University Weinan Gao, Florida Institute of Technology 

Institution(s): Georgia Southern University

---

Abstract

This poster presented the research project of RP 19-12 which was supported by GDOT: Cognitive attention and its application in countermeasures on a curve section of rural road. The effectiveness of the common countermeasures on reduction of crashes was examined based on the information of the number of crashes, the eye movement indexes collected during simulation. Results indicated that the eye movement indexes from eye tracker can help understanding the effectiveness of those countermeasures.

---

Please comment below with any statements or questions you may have. Also let GTI if you would be interested webinars or presentations on similar topics.

PI: Javier Irizarry

Co-PI(s): Yong Kwon Cho 

Institution(s): Georgia Institute of Technology

---

Abstract

Vegetation control and roadside mowing on highway is a repetitive task conducted several times per year. Especially, verification of mowing work is labor-intensive, time-consuming and presents safety issues. This study focuses on a development of UAV-based automatic mowing inspection framework using computer vision and Artificial Intelligence. This work also presents a workflow analysis to optimize for the right-of-way mowing activities. The goal of this project is to develop an automated performance verification framework for highway grass condition monitoring tasks. The proposed method uses real highway image data captured by the UAV to process the grass classification and height estimation algorithms. The results from the proposed approaches are evaluated in terms of accuracy of detected grass regions and heights by comparing ground truth data. The outcome of this research will enhance and automate the roadway mowing inspection and monitoring process.

---

Please comment below with any statements or questions you may have. Also let GTI if you would be interested webinars or presentations on similar topics.

PI: Jon Calabria

Co-PI(s): Clark Alexander Kevin Haas 

Institution(s): The University of Georgia

---

Abstract

The shoreline of an anthropogenically altered island is changing and threatens cultural and natural resources on the property that GDOT owns and intends to use for saltwater marsh mitigation. The first phase of the Bird-Long Island investigated shoreline movement over time, deployed spat sticks, documented vegetative alliances and quantified channel velocities (Phase 1A: Alexander, C. and Calabria, J. and Phase 1B: Haas, K.)[1]. Results from the first phase informed the second phase of design interventions that balance cultural and natural resources in light of environmental changes. Design interventions are proposed with unranked strengths and weaknesses that explain their efficacy. Several conceptual plans with passive and active strategies to enhance natural and cultural resources on this property are proposed.

---

Please comment below with any statements or questions you may have. Also let GTI if you would be interested webinars or presentations on similar topics.

PI: Baabak Ashuri

Co-PI(s): 

Institution(s): Georgia Institute of Technology

---

Abstract

Prepared in cooperation with the Georgia Department of Transportation, Office Right of Way (ROW), this research found the current state of the practice in right of way acquisition among state DOTs to identify best practices with the greatest potential to improve ROW acquisition, including: (a) the organizational structures of the office of ROW, (b) the process of using consultants and performance measurements, and (c) the best practices and strategies used to expedite ROW acquisition. The research utilized the following tasks to evaluate opportunities to estimate the ROW acquisition timeline, considering unique project features and important external factors surrounding the project environment: (a) identify important factors in setting the ROW acquisition timeline, (b) collect required data, (c) conduct data mining to evaluate opportunities to estimate the ROW acquisition timeline.

Project Video

---

Please comment below with any statements or questions you may have. Also let GTI if you would be interested webinars or presentations on similar topics.