Developing and Testing an Advanced Hybrid Electric Vehicle Eco-Cooperative Adaptive Cruise Control System at Multiple Signalized Intersections (Collaborative Project)

Project Abstract

This research develops an advanced Eco-Cooperative Adaptive Cruise Control System (Eco-CACC) for hybrid electric vehicles (HEVs) to pass signalized intersections with energy-optimized speed profiles, with the consideration of impacts by multiple signalized intersections. The research extends the Eco-CACC at signalized intersections (Eco-CACC-I) system previously developed by the research team for conventional internal combustion engine (ICE) vehicles to HEVs. In the proposed system, a simple HEV energy model is used to compute the instantaneous energy consumption level for HEVs. In addition, a vehicle dynamics model is used to capture the relationship between speed, acceleration level, and tractive/resistance forces on vehicles. The constraints of energy model and vehicle dynamics are used to develop two HEV Eco-CACC-I controllers for single-intersection and multiple-intersection, respectively. The developed HEV Eco-CACC-I controllers include two modes: automated and manual, for vehicles with or without an automated control system. The automated mode was implemented into the microscopic traffic simulation software so that connected and automated vehicles (CAVs) can directly follow the energy-optimized speed profile. Simulation tests using the INTEGRATION software validated the performances of the proposed controllers under the impact of signal timing, speed limit, and road grade. The simulation tests also demonstrated the improved benefits of using the proposed HEV Eco-CACC-I controllers in a traffic network with multiple intersections. Lastly, the manual model of the proposed HEV Eco-CACC controller was implemented in a driving simulator at Morgan State University so that drivers in connected vehicles (non-automated driving) can follow the recommended speed advisories. The data collected by the driving simulator with 48 participants demonstrated that the speed advisories calculated by the proposed controller can help drivers drive smoothly and save fuel while passing signalized intersections.

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Impacts and Outcomes

Vehicles that are already fuel-efficient can further improve their efficiency, as well as traffic flow. The speed advisories calculated by the proposed controller can help drivers to drive smoothly and save fuel in the vicinity of signalized intersections

Universities and Sponsoring Organizations Involved

Virginia Tech

Morgan State University

U.S. Department of Transportation Office of the Secretary-Research

Principal Investigators

Hao Chen (VT), hchen@vt.edu; Hesham Rakha (VT), hrakha@vt.edu; Mansoureh Jeihani (MSU), mansoureh.jeihani@morgan.edu; Samira Ahangari, samira.ahangari@morgan.edu

Funding Sources and Amounts

USDOT: $135,000 (Federal), Virginia Tech: $50,000 (Match), Morgan State University: $22,780 (Match)

Completion Date

October 2020

Keywords

eco driving, Eco-Cooperative Adaptive Cruise Control, hybrid electric vehicles, multiple signalized intersection, driving simulator, microscopic traffic simulation