Advanced technology vehicles (ATV) including connected vehicles (CV), non-connected automated vehicles (AV), and connected and automated vehicle (CAV) technologies and applications promise transformative changes in transportation system performance. Agencies need the capability to assess the planning, design, operations, and management implications of the presence of such vehicles with different levels of connectivity and automation on system performance. In addition, agencies need to assess the impacts of these technologies as part of their decision-making processes to plan, design, operate, and manage the transportation system.

The purpose of this research is to assist the NCDOT Traffic Management Unit (TMU) and the Value Management Office (VMO) in assessing issues regarding the construction of Diverse, Modern, and Unconventional Intersections and Interchanges (DMUII). Assessing the constructability of these emerging DMUII is a new area of study that has not yet been previously explored. Therefore, this research will identify factors affecting construction projects prior to construction and develop a schedule and cost payout model (based on prior NCDOT projects) that identifies problems related to expenditure, schedule, and obstruction of traffic during construction.

The NCDOT is launching a bold and forward-looking effort to establish multi-university transportation centers of excellence to provide broad-based, multidisciplinary research into the applications and impacts of cutting edge technologies and emergent, disruptive trends. The projects included in our center proposal were custom-built to address the research areas spelled out in the request for proposals for the desired Mobility and Congestion center. The three themes are as follows: ��������������� Theme #1: Big Data and Data-Driven Transportation Management and Decision Support ��������������� Theme #2: Active Transportation Management/Integrated Corridor Management ��������������� Theme #3: Transit and Mobility as a Service

This proposal describes Phase II of Project K2, titled Assessing and Addressing Deficiencies in the HCM Weaving Segment Analyses. Phase I of this project was limited to the analysis of simple, ramp weaves. It included new data collection at 15 sites in the Southeast and Western US, and a new speed predictive model that avoids much of the complexities in the HCM6 method. The model was found to yield more accurate speed predictions than the current HCM6 methodology. Phase II will extend the work to major weaves. As part of the original Phase I data collection, the research team had already collected volume and geometry data for 14 Type B sites which were not used in that phase. In addition, the team has access to the original NCHRP 03-75 database, which included another 10 Type B weaves. As a result, there will be no new data collection for this weaving configuration in Phase II. . The team proposes to collect a limited set of new data in North Carolina (5-6 sites) for Type C weaving configuration, in order to cover all weaving configurations and enabling the development of new HCM material that is comprehensive across all weaving types.

This project will identify, develop, and implement a suite of simulation models and methods for use in assessing the implications of the presence of connected vehicles (CV), automatous vehicles (AV), and connected automated vehicles (CAV) in the traffic stream and in evaluating the impacts of associated applications that use these technologies. The project will build on current national and international efforts including the on-going research conducted by the Federal Highway Administration (FHWA). As such, the research will start with a comprehensive review and assessment of the literature and existing products on the subject including examining the products of the FHWA effort. Using the review and assessment as a basis, high priority CAV applications to be addressed in this project will be identified based on defined criteria and a framework and guidelines will be developed for the use of analysis, simulation, and modeling of CAV. The project will then develop procedures for calibrating and validating simulation models to ensure the proper use of these models in replicating emerging vehicle technologies and applications. The research team will also identify and develop utilities and extensions of existing models to allow the modeling of selected high priority modeling applications. The project will demonstrate the use of the project development to support agency decisions with regard to high priority CAV applications.

Traffic Analysis Tools-Assessment, Comparison, and Validation Study 2019-2021

Autonomous vehicle (AV) technology is expected to fundamentally change transportation systems. The Transportation Planning Branch at NCDOT, which is responsible for the state������������������s long-range transportation plan, needs state-of-the-art information and predictions on AV technology and its potential impacts on transport to be better prepared for the upcoming changes and maximize the social benefits that this technology will enable. The Transportation Systems group faculty (Drs. Bardaka, List, Rouphail, and Williams) and Dr. Frey (Environmental Engineering) in the Department of Civil, Construction, and Environmental Engineering at NCSU as well as Dr. Cummings, the Director of the Humans and Autonomy Laboratory at Duke University will work together to leverage existing research in the area of AV technology to evaluate impacts and provide policy and future research recommendations to NCDOT. The study will include a comprehensive literature review on AV technology and its impact on transportation demand, capacity, mobility, traffic safety, emissions, energy use, and land use. The results of previous research will be analyzed and case studies for North Carolina will be developed. The study will also provide recommendations to NCDOT regarding changes in policies and regulations, future test plans and test infrastructure, and research priorities in the area of AV technology. As part of this study, the researchers will work closely with the Transportation Planning Branch to provide guidance on how existing models (such as the statewide demand model) could be adapted to account for the presence of AVs.

As stated in its mission statement, the strategic prioritization process declares that ����������������Projects are evaluated based on their merit through an analysis of the existing and future conditions, the benefits the project is expected to provide, the project������������������s multi-modal characteristics and how the project fits in with local priorities���������������. Considering that nearly 3 billion dollars annually of NC taxpayer dollars are at stake in the State Transportation Improvement Program (STIP) Prioritization process of ranking highway projects for funding, travel time savings (TTS) constitute a key input into the projects' benefit cost analyses. Yet, estimates of those savings for various competing projects are derived from models that are completely different in scales, both spatially and temporally, including a low-resolution statewide travel demand model, a highly detailed microsimulation model and a manual calculation based on very limited data. The method of reconciling those estimates across projects has varied from no adjustments in some past Prioritization rounds, to prioritizing based on the relative number of project requests (e.g. corridor vs. intersection improvements) as was done in Prioritization 5.0. This research is intended to study, and propose alternative reconciliation methods for TTS estimates that can improve and make the ranking process more transparent, robust and replicable.

This research is intended to assist NCDOT in improving mobility and safety performance at urban interchange influence areas (IIA's) in North Carolina, to remedy the excessive levels of discretionary lane changes occurring at those locations. The research will predict how driver lane changing behavior is impacted by local traffic, by control and by site conditions. A second objective will be to ascertain whether changes in signing, markings or other traveler information near the IIA can induce fewer discretionary lane changes and thus reduce unnecessary traffic turbulence near interchanges. Currently NCDOT has no means to track lane changing behavior. This research will take advantage of an existing (and continuously expanding) NC State high resolution second by second trip database which uses an in-vehicle OBD-II unit (called i2d) in the Triangle Region. Supplemented with controlled experiments and other data sources the research will produce predictions of lane changing behavior at the vehicle scale, based on present IIA geometrics, the prevailing traffic states and any implemented lane-discipline-inducing treatments. To achieve these objectives, we are proposing to develop a statistical model to predict lane change intensity in urban interchange influence areas. Lane changes will be characterized as mandatory or discretionary. Our i2d data can inform us which type of lane change it is, based on knowledge of the trip origin and destination. Initially, however we will assume that all lane changes are discretionary except when it is known that the vehicle is either entering or exiting the IAA. Thus our predictor variable will be the expected discretionary lane change intensity per vehicle mile in the IIA.

The Highway Capacity Manual (HCM) is one of the most widely used references in transportation engineering, both for planning and operational analyses. The 6th edition of the HCM offers a wide spectrum of analyses ranging from freeway segments to facility travel time reliability. With the recent emphasis from Federal Highway Administration (FHWA) on the adoption of reliability performance measures for funding prioritization purposes and mitigating congestion, a new era for the usage of macroscopic models is emerging. HCM travel time reliability analysis is based on modeling a set of representative days with varying operational conditions. Weaving segments are often critical components of freeway facilities, as they can act as bottlenecks. Any bias or errors within this procedure can significantly impact facility-wide or reliability analyses, and in the process significantly brings question into the validity of the entire facility methodology. Researchers at NC State University have been advised of this issue when evaluating the implementation of the HCM6 freeway facility method in the FREEVAL software. NCHRP 03-75 developed the most recent weave analysis method found in HCM. It used real-world data and developed analytical models to assess several weave segments configurations by estimating speeds, capacities and Level of Service (LOS). The developed model was adopted in the 2010 HCM and is included in the 6th edition. In recent years, practitioners have found several cases where this method is not able to model or show sensitivity to certain important parameters under certain operating conditions. For example, the non-weaving vehicles������������������ speeds are not sensitive to the weave short length (which is the distance between two gore points in the weave segment). Also, the non-weaving speed is not sensitive to all lane changes within the segment. These deficiencies have led to questioning the validity of the HCM������������������s weave segments analysis. Furthermore, these deficiencies have gradually led to wide-spreading concerns with facility-wide or travel time reliability analyses that by default incorporate weaving segment analyses.