EP-MPC: An Emergency Vehicle Priority Method at Isolated Intersections in mixed Connected Environment*

Abstract

Emergency Vehicle Priority (EVP) is a crucial component in Intelligent Transportation Systems (ITS). To improve the efficiency of emergency vehicles (EVs) at isolated intersections in mixed traffic environments comprising human-driven vehicles (HVs) and connected vehicles (CVs), this study proposed a novel EVP method named Emergency Priority Model Predictive Control (EP-MPC). Firstly, a trajectory re-construction model based on limited CV data is developed to estimate lane-level traffic states at an isolated intersection. Secondly, spatial-temporal priority strategies are introduced to ensure the right-of-way of EVs, and an algorithm based on the Model Predictive Control (MPC) framework is designed for optimizing EV's trajectory. Finally, the proposed EP-MPC method is compared with two baseline scenarios (i.e., passive EVP, and no EVP) using the Simulation of Urban MObility (SUMO) software. Experimental results demonstrate that the proposed EP-MPC method can significantly reduce the delay of EVs while maintaining the efficiency of social vehicles. Furthermore, sensitivity analysis reveal that increasing the CV penetration rate and traffic volume further enhances the performance of EP-MPC.