An efficient path planning GLOSA‐based approach over large scale and realistic traffic scenario

Vehicle speed and trajectories play an important role in influencing fuel consumption, gas emissions and travel time. ITS services are often proposed in order to reduce the impact of these issues on the environment and the comfort of drivers. Cooperative Intelligent Transport Systems (C‐ITS) introduced many services that target traffic efficiency management and road safety. Green Light Optimal Speed Advisory (GLOSA) is one of the traffic efficiency services that can significantly cut fuel consumption and decrease waiting time while crossing intersections. When approaching a signalized intersection, GLOSA informs the driver of an advisory speed to respect in order to reach the intersection while the traffic light is green. In this paper, we propose an Efficient Path Planning GLOSA‐based (EPP‐GLOSA) approach using Dijkstra greedy algorithm and GLOSA service. EPP‐GLOSA aims at proposing the fastest path for the driver to follow in order to reach its destination. The estimated duration to reach the destination takes into consideration the state of traffic lights along the path on top of Dijkstra algorithm. The proposed approach is evaluated under a large scale scenario in free flow and rush‐hour conditions. Our findings show that EPP‐GLOSA offers a balanced scale between travel time reduction and fuel saving especially in free flow conditions.