A Method for Optimizing Vehicle Energy Consumption Using Speed Guidance in A Connected Vehicle Environment

Based on the signal phases and timing of traffic lights and the distance to the downstream intersection, traditional speed guidance strategies provide advisory speed, in order to improve the efficiency of road transportation and reduce vehicle energy consumption. However, it is difficult to recommend and guide the speed of vehicles in real time due to the limitation of traditional communication methods. With the development of vehicle to infrastructure (V2I) technology, it is possible to access multi-dimension information of traffic flow instantly and simultaneously, and a real-time variable speed guidance method, which can adapt to real-world driving scenarios, is proposed. A three-stage variable speed guidance model is developed by considering signal phase time and road capacity as the constraints. Moreover, the speed guidance problem of vehicle crossing multiple intersections is decomposed into sub-problems defined by each pair of consecutive ones. Between any two adjacent intersections, the feasible time range for vehicle arriving at the downstream junction is solved first, and then it is discretized to calculate the energy consumed at each time node. In the meantime, the speed guidance problem for vehicle traveling through continuous intersections is transformed into an optimal speed control problem. Taking energy consumption of vehicles as the weight, a Dijkstra algorithm is applied to compute the desired path that generates the most efficient speed profile with the lowest energy consumption among all feasible options. The simulation is conducted to verify the proposed method using the simulation of urban mobility (SUMO) simulator, and a case study is carried out for three consecutive intersections of Dongfeng Avenue in Wuhan Economic Development District. Experimental results show that, under scenarios of oversaturated, saturated, and undersaturated traffic flow, the proposed speed guidance method can reduce energy consumption by 0.68%, 1.64%, and 3.97%, when compared with the multi-level optimal method; and by 0.7%, 2.60%, and 9.80%, when compared with the constant speed method, respectively. The proposed variable speed guidance method can provide an energy-efficient trajectory for vehicles to pass through intersections under different traffic volumes and performs best in an undersaturated traffic flow condition.