Estimation of Intersection Signal Timing Parameters Based on Low Frequency GPS Trajectory Data
A new estimation method of signal control parameters based on low frequency and sparse GPS trajectory data was proposed.Based on the difference of distribution patterns in periodic aggrega-tion of vehicle trajectory data,a projection cumulative density curve method was proposed to estimate the signal period,and the minimum sample size required for correct estimation of the period was ob-tained based on Monte Carlo simulation.In time-distance graph,the phase organization of signalized intersection and the effective green time of each phase are estimated by using the relative position rela-tionship between the intersection of the dissipated shock wave in different phases and the correspond-ing stop line flowing to the entrance.Through the comprehensive verification of actual and simulation data,the results show that the established model can obtain higher estimation accuracy with only doz-ens of low-frequency trajectory data,which is better than the existing methods.
urban transportationcumulative density curveGPS trajectory datatrainmonte carlo simulationsignal timing parameter estimation
万方数据
维普
