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

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.