Operations Research

Holiday Travel Trends

STL has created an application for the Virginia Holiday Travel Trends website. STL will enhance the current methodology for establishing congestion levels, experiment with new visualization techniques and will create the Travel Trends application and website for the 2014 Labor Day Weekend and 2014 Thanksgiving Holiday Period.

Evaluation of Operational Decisions and Impacts Using Travel Time Data

This project is a pilot study that uses travel data to evaluate the operational impacts of incidents, work zones, and weather events. For each of the event types, a set of performance measures and event evaluation tools (visual aids) has been identified and has been applied to one incident, one workzone, and one weather event. After receiving feedback from VDOT, the performance measures and visual aids are being applied to a second incident, workzone, and weather event.  Travel time and volume data are the two main data sources used in this project; in addition, incident, workzone, weather data, local media reports, and others are also used. Along the way, challenges, lessons learned and steps needed for automating of the research work will be documented. Recommendations for enhancing the use of travel time data in operational decisions will be made.

Investigation of Different Methodologies to Calculate Freight Performance Measures

The goal of this project is to see if it is possible to compute the Annual Hours of Truck Delay performance measure using only the general-purpose travel time data (that VDOT is using for other needs in the agency) and internal data sources. This will save VDOT money by eliminating the need to purchase additional specialized data from truck profile data. STL will use a one-time truck profile data purchase to calculate the Annual Hours of Truck Delay performance measure. STL will also compute the Annual Hours of Truck Delay performance measure using the regular data combined with the VDOT continuous count volume and classification data and, if necessary other data sources.

Comprehensive Regional Congestion Analysis

In collaboration with VDOT, STL will select an operational region, district, or metro region to act as first test case for developing a methodology for comprehensive data analysis for a larger geographical area. The traffic engineering analyses and performance measures planned are: list of bottlenecks, heat map of the peak period (or peak hour) of congestion, list of travel time indices for key commuter routes, list of buffer indices for key commuter routes. The work on this task will help VDOT get a comprehensive picture of traffic and congestion trends and will establish a methodology for calculating performance measures over a large geographical area.

Connected Vehicles Research

Connected Vehicle Enabled Freeway Merge Management – Field Test

Working under a grant from the FHWA’s Exploratory Advanced Research Program, UVA CTS has spent two years developing and simulation testing a set of advanced algorithms to improve freeway merging using connected vehicle technology. The objective of the algorithms is to increase utilization of merging capacity in freeways, and also to reduce merging related incidents. The specific algorithms proposed for field testing at the UTC Virginia test beds are: Variable Speed Limit (VSL), Lane Changing Advisory (LCA), and Merging Control Algorithms (MCA). This project will test and validate the benefits of the developed algorithms using the UTC Virginia test bed in Blacksburg.

Infrastructure Safety Assessment Using Connected Vehicle Data

Transportation agencies devote significant resources to analyzing crash data to identify “hot spots” – locations which experience larger than normal number of accidents. The premise behind this project is that for every actual crash, there are numerous “near misses” where drivers’ take last second, extreme evasive action (such as swerving or skidding) to avoid a crash. This project will analyze data archived from the connected vehicle test bed to extract “near miss” maneuvers. This data will then be analyzed to identify hot spots that will be examined in terms of traditional crash data to determine if there is a correlation – thus pointing to the potential of this approach.

Infrastructure Pavement Assessment and Management Applications Enabled by the Connected Vehicles Environment Research Program – Phase I: Proof-of-Concept

An important requirement in the pavement management activity is to collect data to assess the condition of the pavement. Currently, agencies use specialized sensors and equipment for this activity, but they impose a significant cost burden on agencies and this method of data collection scales poorly. A potential advantage offered by connected vehicles is that this program promises to closely tie the infrastructure to the vast vehicle fleet using the infrastructure, with in-vehicle sensors being used to assess pavement conditions. The work will address two specific pavement applications: roughness measurement and friction assessment during snow and rain.

Next Generation Transit Signal Priority with Connected Vehicle Technology

For years, Transit Signal Priority (TSP) has been proposed and studied as an efficient way of improving transit operations. This research utilizes the connected vehicle technology allowing two-way communications among multiple transit buses and traffic signals, and among transit buses and other vehicles to develop next generation Transit Signal Priority (TSP) that does not have to rely on conventional TSP sensors. A coordination method accounting for adjacent intersections where transit buses are bounded to travel is also studied. The TSP logic will be evaluated by performing a smart road operational test and a field operational test to quantify the benefit of the proposed TSP logic.

Prototyping and Evaluating a Smartphone Dynamic Message Sign (DMS) Application in the CVI-UTC Testbed

This proposed project is prototyping and evaluating a smart phone application that provides the functionality of a DMS. When a traveler is in range of a physical DMS, the information from the sign will be presented to the traveler via an audible message. The app will not require “active” driver participation. Initially ranges will simply correspond to existing DMS locations, and the audible messages will be the same as the current DMS message, but the application will be readily scalable to other “virtual” DMS locations and messages. This project will conduct a field test using the UTC Northern Virginia testbed and collect and analyze user satisfaction survey data.

Other Research Areas

Identifying and Prototyping Integrated Corridor Management (ICM) Strategies for Application in Virginia

Integrated Corridor Management (ICM) strategies have gained considerable interest in the United States due to their ability to improve service in high demand corridors. ICM seeks to use all systems and resources in a corridor in an integrated fashion to optimize the movement of people and goods. Experience has shown that ICM must be tailored for the specific characteristics of a region and corridor. Therefore, this project aims to identify the ICM strategies that are specifically applicable to corridors in the Commonwealth of Virginia, and to demonstrate their potential benefits through prototype application in a simulation environment.

Multimodal Enhancements to Public-Private Partnership (PPP) Projects

Public-Private Partnership (PPP) projects are attractive because they bring private equity, but sometimes they are not financially self-sustaining for the private sector. A promising new perspective for multimodal projects has emerged: measuring their worth by accounting for their societal benefits (needed to justify the public sector investment) and making such projects multimodal rather than unimodal. Because previous PPP guidelines focused only on financial viability and a single mode, new guidelines are needed. These guidelines will be developed for Virginia by defining multimodal cataloging practices and quantifying societal benefits.

Integration of Travel Demand Models with Operational Analysis Tools

This research aims to develop a framework to link the results from regional travel demand models with operational analysis tools. The framework’s major components are selection of an appropriate operational tool, disaggregation of daily volumes to peak period volumes, and alignment of modeling elements such as link capacity. The framework is demonstrated with a HOT lane deployment in the Hampton Roads (Virginia) region. The results can potentially provide a powerful tool for use by VDOT and the state’s MPOs to compare ITS operational improvements alongside physical capacity expansions that will make it feasible to bring alternative operational strategies into the long range planning process.