Evaluating Safety with Automated Vehicles at Signalized Intersections: Application of Adaptive Cruise Control in Mixed Traffic
Abstract
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, we 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. We 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 numbermore »
- Authors:
-
- University of Tennessee, Knoxville (UTK)
- The University of Tennessee, Knoxville
- ORNL
- Publication Date:
- Research Org.:
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1493116
- DOE Contract Number:
- AC05-00OR22725
- Resource Type:
- Conference
- Resource Relation:
- Conference: 2019 Transportation Research Board Annual meeting - Washington D.C., District of Columbia, United States of America - 1/13/2019 3:00:00 PM-1/17/2019 3:00:00 PM
- Country of Publication:
- United States
- Language:
- English
Citation Formats
Arvin, Ramin, Khattak, Asad, and Rios Torres, Jackeline. Evaluating Safety with Automated Vehicles at Signalized Intersections: Application of Adaptive Cruise Control in Mixed Traffic. United States: N. p., 2019.
Web.
Arvin, Ramin, Khattak, Asad, & Rios Torres, Jackeline. Evaluating Safety with Automated Vehicles at Signalized Intersections: Application of Adaptive Cruise Control in Mixed Traffic. United States.
Arvin, Ramin, Khattak, Asad, and Rios Torres, Jackeline. 2019.
"Evaluating Safety with Automated Vehicles at Signalized Intersections: Application of Adaptive Cruise Control in Mixed Traffic". United States. https://www.osti.gov/servlets/purl/1493116.
@article{osti_1493116,
title = {Evaluating Safety with Automated Vehicles at Signalized Intersections: Application of Adaptive Cruise Control in Mixed Traffic},
author = {Arvin, Ramin and Khattak, Asad and Rios Torres, Jackeline},
abstractNote = {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, we 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. We 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.},
doi = {},
url = {https://www.osti.gov/biblio/1493116},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Tue Jan 01 00:00:00 EST 2019},
month = {Tue Jan 01 00:00:00 EST 2019}
}