Federal Highway Administration (FHWA) Connected and Automated Vehicles (CAV) Analysis, Modeling, and Simulation (AMS) Program Future Effective Capacity: Assessing Traffic Flow Impacts for Variable Levels of Automation and Market Acceptance

Automated vehicle (AV) technologies promise numerous benefits to highway capacity and stability through improved reaction times and optimized decision-making processes. However, commercially available automated features (mostly at lower levels of automation) do not exhibit the same behaviors assumed in theoretical studies, which limits near-term benefits (or even causes efficiency to deteriorate) in many real-world operational conditions. These same discrepancies also lead to modeling errors when simulating diverse scenarios for capacity planning exercises. This analysis addresses these uncertainties by reviewing relevant literature with a specific focus on the optimistic and pessimistic viewpoints of AVs related to highway capacity and stability, with a focus on car-following and lane-changing behaviors. Gaps and challenges are identified that limit realistic modeling of AVs in mixed traffic. Potential future research directions are also presented that address specific AV modeling gaps for near- and mid-term operational planning.

  • Record URL:
  • Corporate Authors:

    Noblis, Incorporated

    500 L’Enfant Plaza, S.W., Suite 900
    Washington, DC  United States  20024

    Department of Transportation

    Intelligent Transportation Systems Joint Program Office
    1200 New Jersey Avenue, SE
    Washington, DC  United States  20590
  • Authors:
    • Grahn, Rick
    • Silverstein, Claire
    • Wang, Peiwei
    • Wunderlich, Karl
  • Publication Date: 2024-11

Language

  • English

Media Info

  • Media Type: Digital/other
  • Edition: Final Report
  • Features: Figures; References; Tables;
  • Pagination: 47p

Subject/Index Terms

Filing Info

  • Accession Number: 01938506
  • Record Type: Publication
  • Report/Paper Numbers: FHWA-JPO-24-146
  • Contract Numbers: GS00Q14OADU143; 693JJ321F0003 81
  • Files: NTL, TRIS, USDOT
  • Created Date: Nov 30 2024 3:26PM