Research On Vehicle Positioning In Highway Tunnel Based On Visible Light Communication

With the rapid development of our country’s road infrastructure,the number of vehicles has also increased sharply,which has led to an increasing number of road traffic problems.Among them,road tunnels cannot obtain information about their position and the distance between neighboring vehicles in time due to the narrow internal space,strong closedness,and the inability of radio frequency(RF)signals to communicate normally.As a result,traffic accidents frequently occur in this special section of the road.This paper uses a new information transmission method-Visible Light Communication(VLC)to solve the above problems.VLC mainly uses light-emitting diodes(Light Emitting Diode,LED)as the light source,uses light signals to transmit data,can exchange information with vehicles,road infrastructure,etc.,to make up for the limitations of radio frequency communication.The specific research content of this paper is as follows:(1)The problem of vehicle positioning in highway tunnels is studied,and a V2I(Vehicle to Infrastructure)positioning model for tunnels based on VLC is established.On this basis,the vehicle location problem under ideal imaging condition and noise imaging condition is studied,the least square estimation(Least Square Estimation,LSE)algorithm and the maximum likelihood estimation algorithm(Maximum Likelihood Estimation,MLE)are used to solve the vehicle coordinates.Among them,LSE does not require probability assumptions,so the estimation effect is not the most effective,but the calculation is simple and easy to implement;MLE requires a known probability distribution function,the estimation effect is ideal but the use scenario is limited.Finally,the factors affecting the Cramer-Rao Lower Bound(CRLB)are studied,and the performance of the two positioning algorithms is analyzed and compared with CRLB through simulation experiments.The results show that under the same set of experimental data,the positioning accuracy of the two algorithms is infinitely close to CRLB,and the positioning effect is good.(2)The application scenarios of highway tunnels are expanded,the distance estimation problem between adjacent vehicles in the tunnel is studied,and the V2V(Vehicle-to-Vehicle)distance estimation model of the tunnel based on VLC is established,and analyzes two kinds of distance estimation problems of image sensors under standard pose and arbitrary pose.In view of the unsatisfactory estimation effect brought by low-resolution image sensors,a resolution compensation optimization algorithm is proposed,and Kalman filter is used to further improve the accuracy of distance estimation.In the case of low image sensor resolution,a more accurate distance estimation problem is achieved.Finally,simulation experiments verify that the proposed algorithm has good practical effects.