Research Of The Coordination Control Of The Intersection Based On The Cooperative Vehicle-infrastructure System

Intelligence Traffic System (ITS) has commonly been accepted as an efficient method to improve traffic performance. Nowadays Cooperative vehicle-infrastructure system (CVIS), which is an important part of ITS, has become hot point in traffic research. CVIS improves the efficiency of intersections by adjusting the vehicle speed which is based on the vehicle-to-vehicle and vehicle-to-infrastructure communication. Based on cooperative vehicle-infrastructure technology, this paper studies control model for unsignalized intersections in different traffic flows and proposes the intersection coordinated control strategy. At last, simulation experiments are done by Cellular Automaton (CA). The main research including the following aspects:1. Based on cooperative vehicle-infrastructure technology, the intersection control models with different traffic flow are put forward. An optimized control model targeting safety and minimal travel time at low traffic flow is put forward. Firstly, to guarantee safety, according to vehicle space-time path chart and the feature of cross intersection conflict, this paper transforms the problem of intersection safety into a nonlinear constraint optimization problem with velocity and acceleration as variables and proposes an optimization model with minimum arc length as target. Then this paper proposes an optimization model with minimum total travel time. Lastly, the total target is established by weighting the two goals.The harmonizing effect of the model is poor at high traffic flow, so this paper transforms the coordination problem of intersection into inter programming problem to seek the minimum average travel time. This method could avoid accidents through controlling stop and go of the target vehicles.2. Designing and verifying the algorithm to solve the proposed model in low traffic flow and make the sensitivity analysis for the related parameters. This paper solves the proposed model based on genetic algorithm (GA) and shows every step in detail. The results proved the GA could find the optimal solution. The sensitivity analysis helps to set the initial parameters of algorithm more reasonably and guarantee the optimization problem converge to the optimal solution.3. The intersection simulation experiments are done by CA under the CVIS. This paper proposes the intersection coordinated control strategy based on the CVIS. And the simulation link is divided into four parts. Based on the vehicle’s position, different vehicle evolution rules are proposed. We take average parking time, average travel time and average queue length to evaluate the effectiveness of intersection. We do the simulation experiment with CVIS control, signalized control and no control. The experiment results show that the effectiveness of the intersection under the cooperative vehicle-infrastructure control strategies proposed in this paper is the best.