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Analysis, Modeling, and Simulation Tools Projects

 Provide the necessary tools and best practices to facilitate smart transportation operational decisions investments.

Analysis, modeling, and simulation (AMS) tools projects conceptualize and refine AMS frameworks and investigate the application of AMS methodologies to address transportation system challenges. Projects in this area support the role of AMS in transportation development related to connected automation, congestion management and mitigation, and state of the practice.

Connected Automation

Agencies need a low-cost method to quantify impacts of connected and automated vehicle (CAV) deployments to make intelligent investment and operational decisions. In theory, this type of challenge—evaluating a new technology prior to implementation—is well suited to be solved with traffic analysis tools. Off-the-shelf AMS tools, however, were built to model human drivers. Thus, new CAV behavioral models are necessary to enable impact assessments of the technology. After developing a CAV AMS framework and conducting a CAV AMS gap analysis, the Federal Highway Administration (FHWA) structured the CAV AMS research program around three iterative pillars: collect robust, real-world datasets; develop AMS tools and methodologies that capture the behavior of CAV technologies in traffic; and conduct case studies to better understand the real-world impacts of CAVs. Researchers investigated several project concepts in this area, including:

CAV Data Collection: This research program is currently funding three projects to collect ground-truth data on how CAVs behave in traffic and how adjacent human drivers react to the presence of both discreet and readily identifiable CAVs in the traffic stream. Project researchers will collect diverse datasets using vehicles with varying levels of automated capabilities (i.e., SAE Levels 1–4) in many operational conditions (e.g., arterials, freeways, complex weaving and merging locations) with a variety of CAV applications (e.g., single vehicle operations, platooning operations) and in diverse geographical locations (e.g., Illinois, Maryland, Ohio, Virginia, and Washington, DC). The goal of these research projects is to collect and disseminate AMS-ready datasets about CAVs and human drivers to support the development of more robust traffic microsimulation models. These datasets are planned for collection during 2021 and 2022 and will be made available after validation.

CAV Model Improvement: The focus of CAV model improvement is to use the ground-truth data (i.e., data measured outside a computer model) to develop and validate new modeling tools to enable more robust impact assessments. Open source tools that were recently developed under this program include an automated vehicle lane-changing algorithm, an improved cooperative adaptive cruise control algorithm and connected-human-driver car-following algorithm, an improved speed-harmonization algorithm, and a new cooperative-merge algorithm. The models and their algorithm description documents are now on the ITS CodeHub and are available for download.

CAV Benefits Estimation: The focus of CAV benefits estimation projects is to conduct real-world case studies to help infrastructure owners and operators understand the impacts of CAVs on the facilities they manage. FHWA recently conducted four case studies: SR–99 in California, I–66 in Virginia, and two arterial case studies using the Traffic Optimization for Signalized Corridors application.

Congestion Management and Mitigation

Congestion management and mitigation project researchers develop AMS tools to demonstrate the benefits of alternative operational strategies to reduce congestion and improve mobility at bottleneck locations. Projects in this focal area investigate several concepts, including the following:

Roadway design: Researchers using AMS tools can test conceptual freeway and arterial designs never implemented in practice. Microsimulation models facilitate the quantitative and qualitative evaluation of alternative approaches to freeway movement for deployment consideration. Hundreds of possible designs and traffic management systems can be tested safely and efficiently with AMS tools. Examples of designs developed and tested by FHWA include:

  • Traffic Bottlenecks Identification and Solutions:  Project researchers developed a playbook of 70 bottleneck mitigation strategies that are low cost and do not require advanced vehicle technology to provide congestion relief. Researchers selected five of the most promising solutions—dynamic lane use, contraflow or reversible lane use, hard-shoulder lane use, lane-width reduction, and modest extension of auxiliary lanes—and they conducted cost-benefit analyses using impact assessment results obtained through microsimulation.
  • Simulator Assessment of Alternative Lane Grouping at Signalized Intersections: Motivated by the aforementioned Traffic Bottlenecks report, researchers behind this project explored a real-world implementation of the dynamic reversible left-turn lane at diamond interchanges and the contraflow left-turn lane at signalized intersections, which were found to increase significantly the capacity at intersections with high left-turn-lane volumes. Project researchers developed the Manual of Uniform Traffic Control Devices-compliant pavement markings and signage strategies for innovative treatments, and they tested the reaction of human drivers experiencing these intersections for the first time through the highway-driving simulator.
  • Narrowing Freeway Lanes and Shoulders to Create Additional Travel Lanes: This project explored the operational and safety benefits of reducing freeway lane and shoulder widths to create additional travel lanes by developing improved macroscopic analysis tools, calibrating car-following models that capture narrowed-lane driving behavior, conducting real world case studies, developing improved safety models of the narrow lanes treatment, developing narrowed-lanes deployment recommendations, and investigating dynamic lane-narrowing technologies.
  • Alternative Designs to Alleviate Freeway Bottlenecks at Merging, Diverging, and Weaving Areas: The objective of this project was to identify alternative freeway designs that achieved significant mobility benefits (e.g., reduced delay, increased throughput) in the virtual-simulation environment, such that subsequent human-factors studies or field testing would be warranted. Five candidate designs were selected for investigation in microsimulation: split merge and diverge points, managed lanes on the right, mainline meeting, coordinated ramp metering, and speed optimization via traffic-calming devices.

Traffic bottleneck solutions: Per the 2018 INRIX Global Traffic Scorecard, Americans lost an average of 97 hours in 2019 because of congestion. This equates to an average loss of $1,348 in wages per driver, or $87 billion in total. Per the 2004 report Traffic Congestion and Reliability: Linking Solutions to Problems, bottlenecks are the largest single source of traffic congestion, accounting for 40 percent of congestion. Projects conducted by FHWA to reduce the impact of bottlenecks include:

  • Congestion Bottleneck Identification (CBI) Tool: The bottleneck mitigation process can be divided into three subprocesses: identification, diagnosis, and solutions. To be mitigated, the bottleneck must first be identified and diagnosed. The CBI tool was developed to help visualize the duration, intensity, variability, and extent of traffic bottlenecks. The CBI tool can draw a traffic state matrix (STM) for any day of the year. It can also draw an STM for “percentile” days of the year, according to certain performance measures (e.g., the day having the 85th percentile worst bottleneck intensity). Researchers used the CBI tool to develop a new performance graphic called the annual reliability matrix, allowing practitioners to easily observe annual bottleneck intensity and reliability within a single graphic. A new, delay-based performance measure for annual reliability called the bottleneck intensity index was implemented within the CBI tool for a more robust ranking of bottlenecks. Finally, a wavelet method for signalized arterials was added to the tool to filter out delays that are unrelated to congestion.

State of the Practice

The AMS research program seeks to develop and disseminate best practices on the appropriate application of AMS tools and methodologies as well as explore practical improvements to the state of the practice. Emphasis areas include the following:

Stakeholder engagement: The Traffic Analysis, Modeling, and Simulation Pooled Fund Study (TAMS PFS) is an FHWA-led pooled fund study that is intended to serve as a forum and provide an opportunity for the participants to identify, address, and collectively tackle key issues and challenges that are common among public agencies in conducting, managing, and/or approving traffic analysis and simulation studies. The TAMS PFS will address key technical and programmatic traffic analysis issues through the investigation and development of best practices, lessons learned, and recommended guidelines or methodologies. The TAMS PFS will also provide an opportunity to facilitate the interaction, sharing of information, and exchange of knowledge with a broader audience to advance and improve upon the current state of the practice related to the usage, management, and/or approval of traffic analysis and simulation tools.

Exploring new data sources: The current state of the practice is to use aggregated performance measures (e.g., throughput and speed data obtained from readily available loop detectors) to calibrate the microscopic driver behavior (e.g., car-following models) in microsimulation. This program area explores innovative new data sources to explore their applicability to model development and calibration. Examples of data sources of interest include:

  • Instrumented personal-vehicle data.
  • Instrumented research-vehicle data.
  • High-altitude fixed cameras.
  • Aerial data collection.

Methodological improvements: Projects in this area seek to improve the state of the practice of traffic AMS:

  • Trajectory Investigation for Enhanced Microsimulation Guidance: Through interviews conducted by the Transportation System Simulation Manual team, it was confirmed that many modelers overlook the driver-behavior-calibration process when developing traffic simulation models because of the excessive time and resources required for this complex process. Moreover, these interviews confirmed that the driver behavior components of traffic simulation models (e.g., car-following, lane changing) are commonly calibrated using macroscopic data such as 15-min aggregated speed, travel time, and counts data. Recent advances in computing power and data collection strategies now enable the collection of full-length vehicle trajectories. Integrating vehicle trajectories into traffic analysis models may provide greater insight into the calibration of driver behavior submodels, diagnosis of bottlenecks, and recommendations for treatments. This project used data collected via drones and helicopters to develop a semiautomated, seven-step procedure for calibrating the driver behavior components of microsimulation models using trajectory data.
  • Multiresolution Modeling (MRM): Transportation AMS tools exist at a variety of resolutions: microscopic, mesoscopic, and macroscopic. Each of these models has specific advantages and disadvantages. The selection of which model resolution to use depends on the question an agency is trying to answer, as each of these models has specific tradeoffs with its application. The applications of these different types of models, however, are not mutually exclusive. To unlock the full potential of transportation AMS tools, analysts should explore the complete, multidirectional integration of an array of tools with different capabilities, increasingly called MRM. The objectives of this project are to assess the current state of practice of MRM in transportation analyses comprehensively; to evaluate and assess gaps preventing the adoption of MRM by agencies; to develop a software-agnostic guidebook to assist agencies with developing a fully integrated MRM model; and to illustrate the benefits of applying MRM, as opposed to single-resolution models, in two case studies. This will help transportation professionals assess the level of effort and benefits of developing multiresolution models for their analyses and provide transportation professionals with guidance for model development.
  • Work Zone Driver Behavior Model: Work zone driver behavior models comprise one area of interest for investigations into predicting and minimizing the operational impacts of freeway flow disruptions. Work zone car-following models interfacing with existing microsimulation tools were found to predict travel times and queue locations more accurately than calibrated microsimulation software packages using suggested model parameters, thereby enabling more accurate simulations of car-following through freeway and work zones.

A comprehensive repository of projects and project data is available through the FHWA Research Projects Search.

Recent News

  • November/December 2019 edition of FHWA R&T Now  features a suite of tools designed to evaluate the safety and operational effects of project-level geometric design decisions on highways.
  • FHWA awards $8 million to 10 States for innovative highway projects.