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AMS Projects

Individual Project Information

There are several current and recently completed projects in the AMS study area:

Each project is spearheaded by a research team in FHWA’s Office of Operations Research and Development.


Connected Automation

Development of an Analysis, Modeling, and Simulation (AMS) Framework for V2I and Connected/Automated Vehicle Environment (Ongoing)

Current AMS tools are not well-suited for evaluating CAV applications because of their inability to incorporate communication and automated features, as well as their inability to predict planning-level impacts of CAV deployment. This project will create a foundational framework for the development of AMS tool capabilities and engage in a small-scale vehicle-to-infrastructure (V2I) AMS case study using this framework to encourage future development activities. This project is moving practice toward a vision where practitioners have CAV-aware tools available. Specifically, this project will:

  • Review and assess prior and current CAV AMS work.
  • Assess CAV data availability and future data sources for model development.
  • Assess capabilities of existing AMS tools for analyzing CAV applications.
  • Identify current CAV modeling gaps and needs.
  • Develop a CAV AMS framework capable of addressing these needs.
  • Conduct a small-scale CAV case study for proof of concept.
 

Illustration. One of the three main components of the conceptual framework: a performance simulation tool. This illustration shows the conceptual framework of the performance simulation tool. The simulation tool (titled as “Integrated Traffic-Telecom Simulation Platform”) is centered and defined by a blue box. Inputs into the tool surround the blue box and include: (1) external factors (gray box with arrow), (2) OEM logic (gray box with arrow), (3) agency communication protocols (gray box with arrow), (4) demand patterns (orange box with arrow), and (5) system configuration (green box with arrow). Output of the simulation tool is below the blue box: performance measures (purple box with arrow). Components of the simulation tool are inside the blue box and include: (1) wireless telecommunications (white box with arrows), (2) isolated manual driver behavior (white box with arrow), (3) connected manual driver behavior (white box with arrow), (4) isolated automated driver behavior (white box with arrow), (5) connected automated driver behavior (white box with arrow), and (6) heterogeneous traffic interactions (white box with arrow).
Source: FHWA
Figure 1. A Performance Simulation Tool. One of the three main components of the conceptual framework.

Hardware-in-the-Loop (HIL) Testing of Connected Automated Vehicle Applications (Ongoing)

One of the major challenges in testing and demonstrating benefits of CAV applications is the small number of test vehicles available for experiments. Field tests of such small numbers of test vehicles cannot easily impact traffic flow nor can they respond/interact with other vehicles, such as CAVs, whose performance reflects possible future innovations. Larger-scale field operational tests are extremely expensive and still do not allow full-scale assessments of the effects on overall performance. One approach to overcoming these challenges is to use emerging HIL tools, which allow physical test vehicles to interact with virtual vehicles from traffic simulation models. This creates an evaluation environment that can replicate actual deployment conditions.

This project will conduct HIL testing of two CAV applications–signalized intersection approach/departure (SIAD) and cooperative adaptive cruise control (CACC)—and develop software-in-the-loop models of these applications (based on the HIL field tests).

For more information, download the Hardware in the Loop (HIL) Testing of Connected and Automated Vehicle (CAV) Applications fact sheet for this project.

Chart. Implemented hardware-in-the-loop system at Turner-Fairbank Highway Research Center (TFHRC) for the Signalized Intersection Approach/Departure (SIAD) application. This chart shows the hardware-in-the-loop system. It designates the system into two main components: (1) “CAV Applications Testing Environment” (transparent box with orange border) and (2) “Hardware Testing Environment” (blue box with blue border). Additional components are inside these main boxes and indicate information flow by solid or dashed black arrows. Solid arrows indicate information being communicated via Ethernet. Dashed arrows indicate information being communicated via DSRC.
Source: FHWA
Figure 2. Implemented hardware-in-the-loop system at Turner-Fairbank Highway Research Center (TFHRC) for the Signalized Intersection Approach Departure (SIAD) application.

Building a Hardware-in-the-Loop Testbed for Evaluating Connected Vehicle Applications (Ongoing)

This project created an HIL testbed capable of evaluating the performance (mobility, energy, and safety) of connected vehicle (CV) applications in an efficient, safe, and economical manner. The HIL testbed integrates a microscopic traffic model and a wireless communication model (software), a laboratory powertrain research platform (hardware), and a testing vehicle (hardware). The communication model is connected with the traffic simulation to evaluate the communication between vehicles and infrastructure. A representative vehicle can be selected from the simulated traffic flow to send data on its power demand to the powertrain research platform in real-time to mimic the actual operation of the vehicle. The HIL testbed can evaluate various CV applications with a target vehicle emulated in the lab. Additionally, it can maintain the precise measurement of vehicle fuel consumption and emissions as the vehicle is operating in actual traffic (such as in a living laboratory environment) or virtual traffic. The testbed could be a key enabler for new technology development for the Nation’s future CV highway systems.The HIL testbed is currently being utilized to analyze the energy and emission benefits of the eco-drive CAV application.

For more information on the HIL testbed, see this publication

Illustration. Basic hardware-in-the-loop testbed structure. This illustration shows the structure of the hardware-in-the-loop testbed. The main components are depicted as transparent boxes with a thick, black border: (1) “Signal Controller Cabinet”, (2) “SMART-Signal”, (3) “Connected Vehicle Controller”, and (4) “Powertrain Research Platform”. At the center of the illustration is the “Microscopic Traffic Simulator” component (box with image of transportation network) with double-arrows connecting it to each of the main components listed above. The “Powertrain Research Platform” is depicted by a photograph of the laboratory with an engine and other engine-in-the-loop connections/hardware.
Source: FHWA
Figure 3. Basic hardware-in-the-loop testbed structure.

New Approaches for Testing Connected Highway and Vehicle Systems (Completed)

This project developed a Connected Vehicle Assessment System that can be used to develop, test, and validate CV concepts and technologies in a realistic evaluation environment that is capable of replicating real-world conditions. It is a comprehensive evaluation platform that integrates multimodal microscopic traffic simulation software and an advanced wireless communication simulation model into an HIL platform. This enables the installation and testing of different vehicle- and infrastructure-based CV applications on real technologies.

Chart. Connected Vehicle Assessment System and its components. This chart shows the “Connected Vehicle Assessment System”. The main components are geographically grouped together and enclosed by boxes: (1) “Hardware Testing Environment” (transparent box with black, dashed border), (2) “Traffic Simulation Environment” (transparent box with red, dashed border), (3) “Connected Vehicles Application Environment” (gray box), and (4) “Communication Simulation Environment” (blue box). Additional components are inside the main boxes, and black arrows indicate the flow of information.
Source: FHWA
Figure 4. Connected Vehicle Assessment System and its components.

Congestion Management/ Mitigation

Narrowing Freeway Lanes and Shoulders to Create Additional Travel Lanes (Ongoing)

Despite increasing freeway congestion, the options to gain significant capacity in the short term are limited. Some cost-effective solutions include shoulder use, ramp metering with possible integrated freeway management, and lane narrowing. This project explores the latter treatment of narrowing freeway lanes. Specifically, this project will:

  • Develop improved macroscopic (e.g., Highway Capacity Manual) and microscopic (e.g., calibrated driver models in VISSIM and AIMSUN) analysis methodologies for narrow lanes on freeways.
  • Implement these methodologies in at least three test cases.
  • Explore technologies (e.g., illuminated pavement markers) that could be used dynamically to narrow lanes.
  • Provide analysis recommendations for evaluating operational and safety performance measures.

Simulator Assessment of Alternative Lane Grouping at Signalized Intersections (Ongoing)

This project conducts a series of human factors experiments to evaluate the most effective signing and marking strategies for the implementation of a dynamic reversible left-turn lane (DRLT) and a contraflow left-turn lane (CLTL) pocket. Previous AMS studies have shown that a DRLT can significantly increase throughput–compared to conventional diamond interchanges–when traffic flows are heavy with unbalanced turning movements, such as during a peak period. Likewise, previous AMS studies have shown that CLTL design can significantly reduce intersection delay.

Screenshot. Driving simulator experiment of the contraflow left-turn lane (CLTL) pocket scenario. This image shows a bird’s eye view of a four-legged urban intersection with three lanes and a left-turn lane in the northbound direction and three lanes in the southbound direction. The intersection is systematical. The intersection is surrounded by green grassy hills and several buildings. The image shows where the left-turning northbound traffic can cross the opposing lane of traffic to execute the left-turn. The image shows upstream traffic signals for such a maneuver: (1) a red “X” over the leftmost lane of traffic, (2) green downward pointing arrow with a white left-turn signal over it (opposing lane where the left-turn can be executed), and (3) a green downward pointing arrow (in the normal, left-turn lane). The concrete median tapers open with double, dashed yellow lines marking the reversible lane.
Source: FHWA
Figure 5. Driving simulator experiment of the CLTL pocket scenario.

Traffic Bottlenecks: Identification and Solutions (Completed)

This project developed practical methods for prioritizing and mitigating traffic bottlenecks, which are one of the top causes of surface transportation congestion in the United States. This project led to the development of the following:

  • A new approach for ranking traffic bottlenecks.
  • A new playbook of 70 bottleneck mitigation strategies.
  • A benefit-cost (B/C) analysis of five low-cost bottleneck mitigation strategies.
  • Three new bottleneck mitigation strategies.

A data-driven congestion and bottleneck identification software tool was created with numerous performance measures. In parallel, extensive traffic simulations were conducted to assess the operational benefits of underutilized strategies as opposed to popular strategies. The project focused on low-cost solutions, omitting solutions requiring excessive infrastructure investments or advanced vehicle technologies. Explored intervention strategies include dynamic lane use, contraflow or reversible lane use, hard shoulder lane use, lane width reduction, and modest extension of auxiliary lanes. Results demonstrated that these solutions produced favorable B/C ratios with only minor modifications to existing infrastructure.

For more information, download the Traffic Bottlenecks: Identification and Solutions fact sheet.

Download the Congestion and Bottleneck Identification (CBI) tool software. 

AMS State-of-the-Practice

Development of a Transportation System Simulation Manual (TSSM) (Ongoing)

Transportation system simulation is the mathematical modeling of transportation systems through the application of software to better plan, design, and operate transportation systems. Simulation software is widely used by State, regional, and local transportation agencies (and their consultants) and its use is expected to rise given the growing emphasis on performance management, travel time reliability, multimodal solutions, performance-based design, and connected and automated vehicles. Despite the importance of simulation, there is no authoritative guidance document on its use and application. This research project will develop the first edition of a national, definitive Transportation System Simulation Manual (TSSM)–delivering to users the concepts, guidelines, and procedures of simulation modeling.

The TSSM will include:

  • Definitions (and distinction) of model scoping, building, calibration, and validation with specific examples from traffic operations.
  • Recommended practices and needs for model scoping, selection, calibration, validation.
  • Current practices for providing guidance for use of traffic simulation models.
  • Key parameters used in calibration and validation of microsimulation models.
  • Identify data sources that can be used in calibration and validation of the models and guidelines for how this data is collected and prepared for modeling. Provide guidance on how to manage the iterative nature of the calibration and validation processes (manual, heuristic search, etc.).
  • Performance measurement reporting and visualization.
  • Best practices specifically for model calibration and validation recommended by researchers and scholars.

For more information, please visit the Traffic Analysis and Simulation Pooled Fund Study (TPF-5(176)) website.

Developing the FHWA Driver Model Software for Practical Application (Ongoing)

This project will enhance the capability, functionality, and usability of the software created for “Moving FHWA Work Zone Driver Model towards Practical Application” into a robust software platform—the FHWA Driver Model Software. The FHWA Driver Model Software will incorporate specialized driver models (e.g., for work zones, adverse weather, connected and automated vehicle applications), a suite of model calibration and validation tools (including automated data processing and model calibration functions), in-simulation diagnostic tools, and analysis tools that provide streamlined simulation output analytics. Specifically, current research includes:

  • Incorporating signalized intersection approach/departure (SIAD) and cooperative adaptive cruise control (CACC) driver models.
  • Creating a traffic analysis function into the platform and developing model validation tools.
  • Creating data processing and model calibration tools and incorporating them into the platform.
  • Developing and interfacing a user feedback system into the platform.

Screenshot. Main menu and components of the FHWA Driver Model Software: calibration, simulation, and analysis. This image shows the main menu of the FHWA Driver Model Software. The title (at the top of the window) reads “FHWA Driver Model Tool” directly left of the USDOT triskelion logo. Beneath the title are the main tabs: “File”, “Calibration”, “Simulation”, “Analysis”, and “Help”. Beneath the tabs are the three main components of the software: “Calibration”, “Simulation”, and “Analysis”. Each component has a logo: (1) “Calibration” – a mechanic diagnosing a vehicle’s engine, (2) “Simulation” – vehicles simulated on a roundabout, (3) “Analysis” – various colored bar and pie charts.
Source: FHWA
Figure 6. Main menu and components of the FHWA Driver Model Software: calibration, simulation, and analysis.

Moving FHWA Work Zone Driver Model towards Practical Application (Ongoing)

Freeway work zones can cause significant operational impacts. As the number of roadway segments on the interstate system reaching their 50-year design-life increases, so does the number of projected freeway work zones. Studies have shown that driver behavior in work zones—specifically car-following and lane-changing—is different than in nonwork zones. However, current microsimulation tools do not include applications that capture this difference. The goal of this project is to create a work zone software that interfaces with existing microsimulation software tools and will enable these tools to accurately simulate car-following behavior through a freeway work zone. This project collects driver behavior data through work zones in northern Virginia and Massachusetts and develops a unique car-following model for work zones, completes the corresponding calibration and validation process, and is packaged into an easy-to-use software.

For more information, download the Work Zone Driver Model fact sheet.

Photograph. Instrumented research vehicle (IRV) used to collect data through work zones with Taylor Lochrane (left) from FHWA, Christopher Melson (center) from FHWA, and Andrew Berthaume (right) from the Volpe Center. The back of a blue 2007 Jeep Grand Cherokee is open, showing electronic data collection equipment installed on black metal brackets. Three young gentlemen in suites and ties pose around the Jeep. The Jeep is stationed in a parking lot, in an urban setting with surrounding brick buildings.
Source: FHWA
Figure 7. Instrumented research vehicle (IRV) used to collect data through work zones with Taylor Lochrane (left) from FHWA, Christopher Melson (center) from FHWA, and Andrew Berthaume (right) from the Volpe Center.

Open Source Microscopic Flow for Researchers University and Special Projects (Ongoing)

This project will develop an open-source traffic simulation software: Enhanced Transportation Flow Open-Source Microscopic Model (ETFOMM). ETFOMM utilizes state-of-the-art advanced computing technologies while inheriting 40 years of FHWA research on traffic simulation algorithms and flow theories. ETFOMM’s primary components are its core microscopic traffic simulation engine, a graphical user input editor, a 3D traffic visualization tool, and a database in cloud service environment. ETFOMM’s open-source approach and its application-programming interface offers the transportation research community the opportunity to add new simulation rules, which fosters the incorporation of new technologies and traffic operational strategies as they are developed. Furthermore, all these improvements can be shared with the transportation research community at large.

For more information, download the Open Source Microscopic Flow tech brief.

Chart. ETFOMM and its components. This chart illustrates the ETFOMM system components. The top level of the chart in green shows the open source ETFOMM Simulation Engine (ESE) and its interface (ETAPI), which provides functions and variables for applications developed by other users to access. When ETRunner starts, it implements ESE and ETAPI. The middle level in yellow shows proprietary components, including an editor (ETEditor), animator (ETAnamator), and a database. Those two levels are bundled to provide ETFOMM Cloud Service (ECS). The bottom represents ETFOMM’s integration with legacy FHWA traffic simulation software, TSIS. The chart also illustrates the data flow of the components: ETFOMM reads .trf files. ETFOMM Interface connects data among Editor, ESE and ETRunner, which in turn connects to ETAPI. ESE provides simulation data to ETAnimator and TSIS.
Source: FHWA
Figure 8. ETFOMM and its components.

Updated: Monday, December 2, 2019