Evaluating Safety with Automated Vehicles at Signalized Intersections: Application of Adaptive Cruise Control in Mixed Traffic

Automated Vehicles (AV) can potentially improve the performance of transportation system by reducing human errors and enhancing mobility and safety. In lower levels of automation, humans are still controlling the vehicle and receiving some advisory information regarding their surrounding environment. This paper investigates the safety impact of low and high levels of AVs, and their interaction with conventional human-driven vehicles at intersections. In order to enhance our understanding of the future interactions between conventional vehicles with AVs, the authors developed a framework to simulate the mixed traffic environment. Different market penetration scenarios are simulated using VENTOS (VEhicular NeTwork Open Simulator) software. A modified Wiedemann car-following model was calibrated to represent the behavior of human drivers of both conventional and low-level AVs, while an Adaptive Cruise Control model was used to represent high-level AVs. Notably, this study investigates purely the automation improvement in the system. The authors modified the acceleration and deceleration regimes of the Wiedemann model and tuned it by harnessing real-world connected vehicle data. Next, the simulation was calibrated utilizing two measures of driving volatility to ensure it closely represents the volatility measures of the real-world data. To evaluate the safety performance of a representative intersection under different scenarios, the number of longitudinal conflicts and driving volatility are used as surrogate safety indicators. The results reveal that increase in market penetration rate of LAVs and HAVs substantially improves intersection safety performance by reducing the number of conflicts and driving volatility.

  • Supplemental Notes:
    • This paper was sponsored by TRB committee AHB45 Standing Committee on Traffic Flow Theory and Characteristics.
  • Corporate Authors:

    Transportation Research Board

    ,    
  • Authors:
    • Arvin, Ramin
    • Khattak, Asad J
    • Rios-Torres, Jackeline
  • Conference:
  • Date: 2019

Language

  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; References; Tables;
  • Pagination: 6p

Subject/Index Terms

Filing Info

  • Accession Number: 01698042
  • Record Type: Publication
  • Report/Paper Numbers: 19-05063
  • Files: TRIS, TRB, ATRI
  • Created Date: Dec 7 2018 9:44AM