V2I Infrastructure Placement and Safety Implications of CAVs in an Interconnected Network

With communication and computational capabilities of connected and automated vehicles (CAVs) evolving rapidly overtime, CAVs can receive and process large amount of data in real-time to dynamically adjust their travel states (e.g., speed, lanes, and/or travel paths). Because of these advanced features, CAVs have great potential to improve the mobility and safety of transportation systems. Existing research has been conducted to leverage information sharing through vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) technologies to mitigate intersections and road segments safety risks. However, since transportation is an interconnected network, local traffic adjustments (such as flow or speed changes) could lead to broader impacts by traffic diversion. Therefore, research is urgently needed to investigate the safety implications from a system perspective with these advanced technologies. In this project, the authors focus on the impacts of information-sharing locations of V2I devices on the system-level safety implications considering adaptive decision-making of CAVs with information updates through V2I communication nodes. The authors propose a novel transportation network equilibrium model to consider the adaptive decision making of CAVs responding to mobility information updates along their travel paths. Microscopic simulation is conducted to estimate key parameters for network equilibrium model, including surrogate safety measurements (e.g., time-to-collision (TTC)), collision risk functions, and link performance functions. Different V2I information sharing strategies are evaluated and compared to understand the impact of information sharing locations on transportation network safety with CAVs using both a four-node test network and Orlando transportation network. The authors found that: (1) more information shared is not always better for network safety; (2) information sharing at different locations could dramatically impact the network safety risk; (3) information sharing will influence the rerouting decisions and the collision risk for those links that vehicles reroute to after receiving information updates will determine the network safety. The specific impacts of information sharing locations will depend on specific settings of the network but the proposed methodology provides a general way to quantify the impacts for different network settings.

• Record URL:
  http://safersim.nads-sc.uiowa.edu/final_reports/UCF-1-Y3_Final%20Report.pdf
• 
• Supplemental Notes:
  • This document was sponsored by the U.S. Department of Transportation, University Transportation Centers Program.
• Corporate Authors:

  University of Central Florida, Orlando

  Department of Civil, Environmental and Construction Engineering
  Orlando, FL  United States  32816

  Safety Research Using Simulation University Transportation Center (SaferSim)

  University of Iowa
  Iowa City, IA  United States  52242

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590
• Authors:
  • Guo, Zhaomiao
  • 0000-0002-1665-5437
  • Afifah, Fatima
  • 0000-0001-8434-8124
• Publication Date: 2021-5-1

Language

• English

Media Info

• Media Type: Digital/other
• Edition: Final Research Report
• Features: Appendices; Figures; Maps; References; Tables;
• Pagination: 74p

Subject/Index Terms

• TRT Terms: Autonomous vehicles; Connected vehicles; Decision making; Traffic safety; Traffic simulation; Vehicle to infrastructure communications
• Geographic Terms: Orlando (Florida)
• Subject Areas: Data and Information Technology; Highways; Safety and Human Factors; Vehicles and Equipment;

Filing Info

• Accession Number: 01848014
• Record Type: Publication
• Report/Paper Numbers: UCF-1-Y3
• Contract Numbers: 69A3551747131
• Files: UTC, TRIS, ATRI, USDOT
• Created Date: Jun 6 2022 4:54PM