The following is a sample of current and recent projects conducted at VT-Scores 

UTC Region 3, Integrated Transportation Infrastructure Management

The Center for Integrated Asset Management for Multi-Modal Transportation Infrastructure Systems (CIAMTIS) will take advantage of world-class researchers and facilities to improve the ability of agencies to deliver safe and cost-effective transportation infrastructure by targeting high-return aspects of infrastructure asset management. Enhanced infrastructure asset management has the capability to extend the life of existing infrastructure, provide improved performance while controlling the costs to both agencies and users, and provide targeted data for enabling the fruition of long-life designs. The Center's activities will span and benefit multiple modes of transportation, with particular emphasis on highways and railways.

Infrastructure Condition Assessment and Prediction under Variable Traffic Demand and Management Scenarios

While there have been several research efforts on infrastructure condition assessments, and other research efforts on traffic demand and management strategies, there is a wide gap in the nexus of the two fields. As more data, technology, and advancements in computer modeling and simulation are becoming available, it is important to understand the impact of changes in traffic demand, shift in intermodal travel, and control/management strategies on infrastructure health. This project will develop a system that will enable understanding, predicting, and evaluating the impact of traffic changes on infrastructure condition assessment. Models and tools will be developed to assist VDOT in its decision-making as it allocates funds to construct and maintain its infrastructure over a given time-horizon in response to traffic-related changes.

Enabled Analysis, Modeling, and Simulation (AMS) for Cooperative Automated Vehicle

The objective of this task order is to develop guidance on how AMS tools can be enabled to evaluate Cooperative Automated Vehicles (CAV) applications. This will allow the transportation professionals in using AMS to assess the safety, mobility, environmental and energy benefits of CAVs. It will also assist transportation agencies in developing guidance on the safe deployment and operation of these vehicles, and to make informed decisions for infrastructure investments.

Evaluating Performance-Based Objectives: An Analytical Framework

This project aims to investigate a wide range of examples from all types of investment decisions, not only example cases in road transportation, but also example cases from other modes of transportation and other fields of study. This approach will also enable the development of a framework that covers the full set of investment decision-making processes, enabling agencies to properly evaluate performance-based objectives. The overall goal is to provide guidance and develop a practical framework that agencies can easily understand and apply in their routine decision-making process to maximize their benefits.

Leveraging Connected Vehicles to Enhance Traffic Responsive Traffic Signal Control

The goal of this research project is to leverage connected vehicle technology and radar sensor information to improve traffic signal efficiency, which will thereby reduce emissions and fuel consumption. This will be accomplished with the following objectives. 1. Design and implement a central system-in-the-loop simulation platform that can collect vehicle trajectory data in real-time to emulate data from Connected Vehicles (CV) and radar detection. 2. Design, test, and implement an algorithm to estimate queue lengths in real-time based on the CV and radar data with varying market penetration rates and sensor accuracies. 3. Design and implement real-time state estimation logic that will make Traffic Responsive Plan Selections (TRPS) via existing controller protocols based on different combinations of volume, occupancy, queue length, and speed. 4. Quantify the benefits of the advanced TRPS logic compared to existing logic across a range of volume scenarios for the study corridor. 

Enhancing Traffic Control Systems to Reduce Emissions and Fuel Consumption

This project will develop a system for monitoring travel time delays on interstates and arterials utilizing existing high resolution data to reduce emissions and fuel consumption. This research stands at the forefront of application-based traffic signal research. Often, products of research are published in a report that sits on a shelf and never get implemented. The ability to deploy these advanced algorithms to control traffic provides benefits to the state Departments of Transportation and the traveling public.

Systematic Evaluation and Selection of Statewide Central Signal System for VDOT

The Signal and Arterial Systems Program area of the VDOT Traffic Engineering Division (TED) is seeking to prepare Systems Engineering documentation to select and procure a statewide Central Signal System for VDOT. This documentation should identify the vision, goals, objectives, and strategies for operating a statewide central signal system. The objective of this technical assistance effort is to prepare Systems Engineering documentation to select and procure a statewide Central Signal System for VDOT. The project builds on the success of the Next Generation Control (NGC) research project to complete the tasks in a timely fashion. 

Optimal Control and Assessment of Area-wide Emergency Vehicle Priority Systems

Emergency vehicles (EVs) are provided priority at traffic signals via emergency vehicle preemption (EVP) mechanisms. In order to guarantee timely passing of EVs, EVP has to interrupt the normal operation of traffic signals along the EV path, one at a time, causing each intersection to fall out of coordination. This procedure can cause major increase in overall traffic delay. New GPS-based priority mechanisms are currently emerging and being piloted at several locations in the US. Both systems have advantages and disadvantages and need to be evaluated to determine: (1) the conditions under which one system should be used and (2) the optimal configuration of the selected system. This project will investigate each system and provide tools and guidelines to provide prioritized right of way to EVs through signalized intersections while optimizing the overall system performance.

Game-Aided Pedagogy to Improve Students' Learning Outcomes and Engagement in Transportation Engineering

The goal of this proposal is to go beyond the development or use of games in the classroom. The objective is to investigate and design a game-aided pedagogy to improve students' learning outcomes and engagement in transportation engineering. We propose a cyclic approach to design and implement games into the curriculum of several transportation courses, and assess their values. The results of our analysis will be used to enhance the games and increase their effectiveness. The focus of this project is not only the development of the tools, but also to increase our understanding as educators about the students' learning outcomes and effective game teaching methods. At the end of this project, we will produce web games with an effective set of exercises that can be used by faculty members at other universities.

MADONNA's Workshop and Professional development for VDOT Districts

The objective of this project is to develop and deliver workshops to VDOT on using the MADONNA system. MADONNA (stands for the Multi Attribute Decision-making Optimizer for Next-generation Network-upgrade and Assessment) was developed and used on a VCTIR funded project to select the next generation of traffic control signal system for VDOT.

Modeling the Dynamics of Driver's Dilemma Zone Perception using Machine Learning Methods for Safer Intersection Control

This joint proposed research between Virginia Tech, Morgan State University, and Penn State will investigate the dynamic nature of driver's perception of dilemma zone, and whether that perception changes as a function of their experience driving through safe or unsafe intersections. A matching project funded by Virginia Center for Transportation Innovation and Research (VCTIR) is investigating different control methods to minimize dilemma zone related crashes, ranging from traditional advance detector and actuated control optimal configuration to the use of advanced technologies such as Wavetronix, Detection-control systems, etc. These two efforts can lead to better modeling of driver perception, better control algorithms, and ultimately safer intersections.

Addressing Dilemma Zone Issues with Control Solutions

Rural, high-speed signalized intersections are associated with vehicle crashes due to dilemma zone problems. Dilemma zones (DZ) are defined in either time or space, as zones where some drivers may decide to proceed, and some may decide to stop at the onset of yellow. This disagreement among drivers can lead to rear-end crashes (when a driver decides to stop while their follower decides to proceed) and/or right-angle crashes (when drivers end up violating the red light and crash with side street traffic). A recent survey conducted by the National Safety Council reports that the crashes associated with signalized intersections constitutes up to 45 percent of all crashes. Besides driver errors, indecisiveness in DZ is another leading cause, especially at high-speed signalized intersections. A control system that minimizes the number of vehicles caught in DZ will result in reduction of the number and severity of crashes at intersections. This research will evaluate and provide guidance related to control solutions that address safety issues related to DZ problems. The solutions will include optimal and proper design of advanced detectors, use of advanced controller features, advanced controller algorithms (Detection-Control System [D-CS], Platoon Identification and Accommodation [PIA], etc.), and other potential advanced solutions. Potential benefits of this research include better safety at high-speed isolated intersections. Guidelines from the research could change signal design and operation practice in Virginia.

Synthesis on Flashing Beacons for Red Signal Ahead Signs

Driver-decision' in dilemma zones (decision zones) during a traffic signal change interval plays a significant role in increasing the road safety at signalized intersections. Hence, providing dilemma zone protection becomes necessary to prevent improper decisions to brake hard in response to a yellow signal indication, leading to rear-end crashes or to proceed into the intersection without being able to clear it before the beginning of red, leading to red-light running incidents and possibly right-angle crashes. The need for dilemma zone protection is more pronounced in cases of high-speed isolated rural or suburban intersections, or intersections with reduced sight distance. Other factors like the type of approaching vehicle (e.g., car or truck) and the grade of the roadway, near the intersection make it increasingly difficult for the vehicles to stop safely at an intersection when the signal changes to red. Availability of traffic signal status information in advance of the intersection would help the motorists in making a better stop/go decision and as a result, Advanced Warning Flasher (AWF) systems have been gaining importance over the past few years. Various types of AWFs have been successfully evaluated for different factors such as dilemma-zone protection and intersection delay and stop reduction in many parts of The United States and Canada. The purpose of this study was to conduct a synthesis on flashing beacons for red signal ahead signs. From a review of the literature and related practices by other state DOTs, best practices for the use of flashing beacons for red signal ahead signs were identified. VDOT's experience with these signs was reviewed and recommendations were made to revise VDOT's guidelines

Field Implementation and Evaluation of Traffic Responsive Control in Reston Parkway

Traffic responsive plan selection (TRPS) control mode has the potential to significantly improve the overall system performance of coordinated traffic networks. TRPS has the advantage of switching timing plans in response to changes in traffic patterns and can reduce the need for signal retiming. Simulation analysis conducted as a part of a completed VTRC project revealed that implementation of TRPS control mode in the Reston Parkway network can achieve an average delay reduction of up to 27 percent and an average stops reduction of up to 21 percent. There is therefore a need to implement the TRPS control mode in the field to evaluate its performance and transfer the research results into practice. The objective of this research was to conduct field implementation and evaluation of TRPS control in Reston Parkway, including actual implementation of TRPS, update of timing plans, determination of optimal TRPS implementation schedule, and documentation of field evaluation.

Exploratory and Advanced Research Program: Driver Behavior in Traffic

Existing traffic analysis and management tools do not model the ability of drivers to recognize their environment and respond to it with behaviors that vary according to the encountered driving situation. The small body of literature on characterizing drivers' behavior is typically limited to specific locations (i.e., by collecting data on specific intersections or freeway sections) and is very narrow in scope. This report documented the research performed to model driver behavior in traffic under naturalistic driving data. The research resulted in the development of hybrid car-following model. In addition, a neuro-fuzzy reinforcement learning, an agent-based artificial intelligence machine-learning technique, was used to model driving behavior. The naturalistic driving database was used to train and validate driver agents. The proposed methodology simulated events from different drivers and proved behavior heterogeneities. Robust agent activation techniques were also developed using discriminant analysis. The developed agents were implemented in VISSIM simulation platform and were evaluated by comparing the behavior of vehicles with and without agent activation. The results showed very close resemblance of the behavior of agents and driver data. Prototype agents prototype (spreadsheets and codes) were developed. Future research recommendations include training agents using more data to cover a wider region in the Wiedemann regime space, and sensitivity analysis of agent training parameters.

MAUTC IntelliDrive

Traffic signal systems are currently operated using a very archaic traffic detection simple binary logic (vehicle presence/non presence information). The logic was originally developed to provide input for old electro-mechanical controllers that were developed in the early 1920's, and was sufficient for that purpose only. Many decades later, both the controller and detection technology have evolved significantly. Vehicle infrastructure integration (VII, currently known as IntelliDrive) promises to bridge the gap between the infrastructure and individual drivers. VII can offer significant benefits to traffic operations and control. Nevertheless, basic research in this area is still lacking, and does not provide enough guidance on how to use the existing system to its fullest potential. There is a wide range of underutilized control capabilities, including advanced traffic signal timing, the use of second-by-second vehicle location data to estimate approach delays and queue size information. Currently, only vehicle presence is provided to and used by the existing controllers. There is therefore a need to investigate the potential of using VII data to enhance traffic signal control capabilities. Furthermore, in conjunction with traffic signal control there is a need to reduce the traffic demand on a network. One of these approaches includes the use of roadway tolling. VII again can assist in the charging of roadway usage given that the location of vehicles will be known to the second-by-second level. The objectives of the proposed research effort are: (a) Research and investigate the potential to utilize VII data to characterize system operation and estimate system-wide measures of performance, and (b) Develop advanced signal timing procedures that can capitalize on VII data and enhance the operations of traffic signal system operations.

Evaluation of Merits and Requirements of Next Generation Traffic Control Systems for Northern Regions Existing Infrastructure

The objective of this project is to understand the limits of the existing system under the growing traffic demands and needs, and to determine when/if the existing system should be replaced or re-used and retro-fitted to a certain extent. This project will start by solving challenges related to Northern Region Operations (NRO) systems (focus on NRO hardware and software needs in relation to the existing levels of traffic demands), and then transfer the insights and lessons learned to the rest of the state. Phase I of the project focuses on the determination of the functional requirements of the control system in VDOT, existing capabilities and desired feature matrix, hardware and communication infrastructure issues, and an overview of the national as well as the European traffic signal system management techniques. Phase II focuses on studying different controllers and software features, retrofitting feasibilities, potential benefits of next-generation control system, macroscopic level analysis of demands in the NRO and a detailed microscopic level analysis for specific networks, and identification of any adaptations to VDOT's communication master plan that will be required to accommodate near-future development.

Feasibility of Using In-Vehicle Video Data to Explore How to Modify Driver Behavior that Causes Non-Recurring Congestion

The objective of this project was to determine the feasibility of using existing in-vehicle video to make inferences about driver behavior that would allow the investigation of the relationship of observable driver behavior to non-recurring congestion in order to improve travel time reliability. The use of other data sources, such as infrastructure-based video and traffic data for example, was also evaluated for the potential to identify ways to modify driver behavior to improve travel time reliability.

NCHRP 3-90: Traffic Control Strategies for Oversaturated conditions

Traffic congestion continues to grow significantly in the United States and throughout the world. Agencies tasked with managing traffic control systems are more and more frequently challenged with moving traffic in congested conditions and situations where the traffic demand exceeds the capacity of the system. Under this condition of oversaturation, typical traffic control strategies do not work as efficiently as necessary, particularly since the objectives are decidedly different when mobility is restricted. As indicated by the results of the 2005 and 2007 Traffic Signal Operation Self-Assessment surveys, the majority of agencies involved in the operation and maintenance of traffic signal systems are already stretched thin and challenged to provide adequate service to drivers in their jurisdictions. Oversaturated conditions present an additional burden for practitioners that do not have adequate tools for addressing such situations. In this project, Kimley-Horn & Associates (KHA), the University of Minnesota, and Virginia Tech performed research on the mitigation of oversaturated traffic conditions on arterials and networks. This research was divided into four components: (1) Diagnosis of the type and causes of the oversaturated conditions, (2) Identification of appropriate operational objective(s) based on the observed condition(s), (3) Identification of appropriate strategies to address specific scenarios, and (4) Development of tools to relate diagnosis of conditions with action strategies In addition to these four areas of emphasis, the research also resulted in a rational guide for practitioners to identify oversaturated scenarios and apply appropriate strategies. The research focused on identifying traffic control strategies that can be implemented by traffic signal systems to handle certain types of oversaturated conditions on surface streets.