Research On Vehicle Trajectory Optimization At Signalized Intersections Under Connected Vehicle Environment

The driving behaviors of vehicles such as frequent acceleration,deceleration,and idle stopping near signalized intersections seriously affect the traffic efficiency of intersections,and easily cause additional fuel consumption and exhaust emission problems in the intersection area.Improving the efficiency of intersection traffic and reducing the stop-and-go phenomenon of vehicles by optimizing the vehicle trajectory in the intersection area has always been a concern in the industry and academia.The paper aims to use the traffic state information available in the connected environment to study the traffic control strategy and trajectory optimization method of Intelligent Connected Vehicles at intersections to prove the service efficiency of intersections and reduce fuel consumption.Based on an in-depth study of signal intersection trajectory optimization theory and speed guidance model.Traffic decision models under different scenarios were established for vehicle trajectory optimization at the isolated intersection,and the speed trajectory optimization under different decisions was studied.A new S-type speed acceleration/deceleration guidance model was proposed,and on this basis,speed optimization models for ecological driving under different traffic decisions were established.Aiming at the multi-intersection vehicle trajectory optimization problem,firstly,the phase and signal light remaining time of the current signalized intersection and the next signalized intersection were obtained by using the connected environment,and the ecological driving trajectory optimization model of the two intersections was established,and the Branch and Bound algorithm was used to solve the model.Then,based on the two-intersection ecological driving model,the multi-intersection trajectory optimization strategy based on the rolling optimization idea was proposed to realize the energy-saving driving speed guidance of multi-intersection.Finally,based on the SUMO simulation platform,the paper built the simulation test scenarios of isolated intersection and multi-intersection,respectively.Simulation experiments were carried out on the isolated intersection traffic decision model,isolated intersection ecological driving trajectory optimization model,and multi-intersection ecological driving trajectory optimization model proposed in the paper,and the fuel consumption under the same simulation conditions with trajectory optimization guidance and without guidance.The simulation results show that in the isolated intersection scenario,the new S-type acceleration/deceleration model combined with the decision model can guide vehicles through the intersection as early as possible,and the maximum fuel consumption saving is 55.9%compared with the situation without guidance.In multi-intersection scenarios,the vehicle trajectory guidance method proposed in the paper can effectively reduce vehicle fuel consumption,which can save up to 31% of fuel consumption compared with the scenario without guidance.It can be seen that the vehicle trajectory optimization method proposed in the paper realized energy-saving driving in the intersection area and improves the traffic efficiency of the intersection.