KUKU

KU ScholarWorks

  • myKU
  • Email
  • Enroll & Pay
  • KU Directory
    • Login
    View Item 
    •   KU ScholarWorks
    • Dissertations and Theses
    • Dissertations
    • View Item
    •   KU ScholarWorks
    • Dissertations and Theses
    • Dissertations
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Microscopic Simulation Model for Mixed Traffic of Connected Automated Vehicles and Conventional Vehicles on Freeways

    Thumbnail
    View/Open
    Srisurin_ku_0099D_17414_DATA_1.pdf (2.362Mb)
    Issue Date
    2020-12-31
    Author
    Srisurin, Punyaanek
    Publisher
    University of Kansas
    Format
    161 pages
    Type
    Dissertation
    Degree Level
    Ph.D.
    Discipline
    Civil, Environmental & Architectural Engineering
    Rights
    Copyright held by the author.
    Metadata
    Show full item record
    Abstract
    This study developed mixed-traffic simulation models of connected automated vehicles (CAVs) and manually-driven vehicles (MDVs) at the full-spectrum of mixed penetration rates on a freeway segment by incorporating the car-following and lane-changing models via a conditional linkage to investigate the sensitivities in highway capacity and travel time. The car-following models for CAVs and MDVs were modified from the full-velocity difference (FVD) car-following model, while the lane-changing logic was adopted to regulate the lane-changing decisions for both CAVs and MDVs. The desired speeds of each MDVs were determined on the basis of stochasticity to represent various desired speeds taken by human drivers, while the uniform desired speed was employed for CAVs. The stochastic gap acceptance was applied for MDVs to replicate the stochasticity of the gaps accepted by human drivers, whereas the static gap acceptance was adopted to establish the safe decision-making thresholds for CAVs prior to performing lane changes. Two algorithms were proposed separately for governing the movements of CAVs and MDVs in the traffic simulation models. The proposed algorithms, along with a 3-to-2 virtual freeway lane drop, were coded in JAVA to develop a simulation platform, prior to calibrating the default model with field data. Eleven mixed traffic scenarios were simulated in the developed platform, along with parallel simulation in VISSIM, to generate and validate the resultant speed-flow diagrams. The results were then analyzed and compared to determine the changes in highway capacity and travel time with respect to the variations in CAV penetration rate. The resultant vehicular trajectories in the scenarios of interest were also analyzed to perceive the impact of CAVs on the trajectories and speeds of the interacting vehicles in traffic. The results showed increase in capacities in the range of 25.9 – 26.9 percent, while travel time decreased by up to 55.4 percent, as the CAV penetration rate shifted from 0 to 100 percent. The trajectory analysis indicated that CAVs have an influence on guiding the smoother speed and acceleration rates of MDVs while an MDV is following a CAV. The results suggest that although headways increased with increasing CAV penetration rate, capacity also increased; however, there should be an optimal headway that maximizes the capacity.
    URI
    http://hdl.handle.net/1808/32632
    Collections
    • Dissertations [4474]

    Items in KU ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.


    We want to hear from you! Please share your stories about how Open Access to this item benefits YOU.


    Contact KU ScholarWorks
    785-864-8983
    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
    785-864-8983

    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
    Image Credits
     

     

    Browse

    All of KU ScholarWorksCommunities & CollectionsThis Collection

    My Account

    LoginRegister

    Statistics

    View Usage Statistics

    Contact KU ScholarWorks
    785-864-8983
    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
    785-864-8983

    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
    Image Credits
     

     

    The University of Kansas
      Contact KU ScholarWorks
    Lawrence, KS | Maps
     
    • Academics
    • Admission
    • Alumni
    • Athletics
    • Campuses
    • Giving
    • Jobs

    The University of Kansas prohibits discrimination on the basis of race, color, ethnicity, religion, sex, national origin, age, ancestry, disability, status as a veteran, sexual orientation, marital status, parental status, gender identity, gender expression and genetic information in the University’s programs and activities. The following person has been designated to handle inquiries regarding the non-discrimination policies: Director of the Office of Institutional Opportunity and Access, IOA@ku.edu, 1246 W. Campus Road, Room 153A, Lawrence, KS, 66045, (785)864-6414, 711 TTY.

     Contact KU
    Lawrence, KS | Maps