U.S. Department of Transportation
Federal Highway Administration
1200 New Jersey Avenue, SE
Washington, DC 20590
202-366-4000
Federal Highway Administration Research and Technology
Coordinating, Developing, and Delivering Highway Transportation Innovations
REPORT |
This report is an archived publication and may contain dated technical, contact, and link information |
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Publication Number: FHWA-HRT-21-077 Date: September 2021 |
Publication Number: FHWA-HRT-21-077 Date: September 2021 |
PDF Version (7.22 MB)
Technical Report Documentation Page
1. Report No.
FHWA-HRT-21-077 |
2. Government Accession No. | 3 Recipient's Catalog No. | ||
4. Title and Subtitle
Developing Analysis, Modeling, and Simulation Tools for Connected and Automated Vehicle Applications |
5. Report Date
September 2021 |
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6. Performing Organization Code | ||||
7. Author(s)
Chapter 1: Zhitong Huang (ORCID: 0000-0003-2871-6302), David K. Hale (ORCID: 0000-0001-5486-9367), |
8. Performing Organization Report No. | |||
9. Performing Organization Name and Address
Leidos, Inc. |
10. Work Unit No. (TRAIS) | |||
11. Contract or Grant No.
DTFH61-12-D-00030, TO 22 |
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12. Sponsoring Agency Name and Address
Office of Operations Research and Development |
13. Type of Report and Period Covered
Final Report; September 2017–September 2020 |
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14. Sponsoring Agency Code
HRDO-20 |
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15. Supplementary Notes
The Government Task Managers were John Halkias (HOTM-1) and Gene McHale (HRDO-20; ORCID: 0000-0003-1031-6538). |
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16. Abstract
Connected and automated vehicle (CAV) technologies offer potentially transformative societal impacts, including significant mobility, safety, and environmental benefits. Traffic analysis, modeling, and simulation (AMS) tools provide an efficient means to evaluate transportation improvement projects before deployment. However, current AMS tools are not well suited for evaluating CAV applications due to their inability to represent vehicle connectivity, communication, and automated driving features. Many independent researchers have developed models of CAV systems based on a divergent array of underlying assumptions. As a result, there is little consensus in the literature about the most likely impacts of CAV technologies. Thus, a consistent set of models based on the best available data and most accurate possible representations of the behaviors of drivers of conventional vehicles and CAVs can produce realistic and believable predictions of CAV impacts. The Federal Highway Administration sponsored this project to develop AMS models for the most prominent CAV applications, incorporate these models into existing AMS simulation tools to improve the state of the practice, and conduct real-world case studies for the most prominent CAV applications to better understand their impact and deployment strategies and methods. |
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17. Key Words
Connected and automated vehicle, traffic simulation, microsimulation, cooperative adaptive cruise control, coordinated merging, speed harmonization, market penetration rate, variable speed advisory |
18. Distribution Statement
No restrictions. This document is available to the public through the National Technical Information Service, Springfield, VA 22161. |
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19. Security Classification (of this report) Unclassified |
20. Security Classification (of this page) Unclassified |
21. No. of Pages
192 |
22. Price
N/A |
Form DOT F 1700.7 (8-72) | Reproduction of completed page authorized |