Field Implementation of an Eco-Cooperative Adaptive Cruise Control System at Signalized Intersections

The paper develops and implements an Eco-Cooperative Adaptive Cruise Control (Eco-CACC) system that computes and recommends/implements a real-time fuel-efficient trajectory using vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communicated data. The computed trajectory can either be delivered to the driver as an audio alert or be implemented directly to connected and automated vehicles (CAV). From an algorithmic standpoint, the proposed algorithm addresses all possible scenarios that a driver may encounter while approaching a signalized intersection. Additionally, from an implementation standpoint the study overcomes the challenges associated with communication latency, data errors, real-time computation, and ride smoothness. The system was tested on a connected vehicle testbed at the Virginia Smart Road. Four scenarios were tested for each participant, including a base case uninformed driver, a driver provided with a red indication countdown, a manual Eco-CACC system that the driver follows via an audio recommended speed, and finally an automated Eco-CACC system that provides longitudinal automated control for a CAV. The data from 256 trips by four different participants were collected in the preliminary field test. The analyzed results demonstrate the benefits of the Eco-CACC system in assisting the vehicle to drive smoothly in the vicinity of signalized intersections and therefore reduce vehicle fuel consumption levels. Compared to the uninformed driver, the longitudinally automated Eco-CACC system controlled vehicle resulted in savings in fuel consumption levels and travel times in the range of 37.4 and 8.6 percent, respectively.

• Supplemental Notes:
  • This paper was sponsored by TRB committee AHB30 Standing Committee on Vehicle-Highway Automation. Alternate title: Field Implementation of an Ecocooperative Adaptive Cruise System at Signalized Intersections.
• Corporate Authors:

  Transportation Research Board

  500 Fifth Street, NW
  Washington, DC  United States  20001
• Authors:
  • Chen, Hao
  • Rakha, Hesham A
  • 0000-0002-5845-2929
  • Almannaa, Mohammed H
  • Loulizi, Amara
  • El-Shawarby, Ihab
• Conference:
  • Transportation Research Board 96th Annual Meeting
  • Location: Washington DC, United States
  • Date: 2017-1-8 to 2017-1-12
• Date: 2017

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; Photos; References; Tables;
• Pagination: 16p
• Monograph Title: TRB 96th Annual Meeting Compendium of Papers

Subject/Index Terms

• TRT Terms: Algorithms; Autonomous intelligent cruise control; Drivers; Field tests; Fuel conservation; Fuel consumption; Mobile communication systems; Signalized intersections; Travel time
• Subject Areas: Energy; Highways; Vehicles and Equipment;

Filing Info

• Accession Number: 01624274
• Record Type: Publication
• Report/Paper Numbers: 17-04918
• Files: TRIS, TRB, ATRI
• Created Date: Jan 27 2017 9:28AM