城市主干路路段行程时间估计的BPR修正模型

Modified BPR Functions for Travel Time Estimation of Urban Arterial Road Segment

为提高城市主干路交通流平均行程时间的估计精度,根据路段上游检测器采集的截面流量,建立了3种BPR(bureau of public roads)修正模型,包括全状态累积流量BPR修正模型、分状态标定的BPR模型和分状态累积流量BPR修正模型.仿真结果表明:全状态累积流量BPR修正模型明显优于传统的BPR模型;分状态标定的BPR模型和分状态累积流量BPR修正模型可以进一步提高估计精度,且后者可将阻滞交通状态下的平均估计误差降低至8.05%.

To increase the estimation accuracy of average travel time for urban arterial roads, three kinks of modified BPR functions, namely accumulative volume BPR functions for general states, BPR functions specially calibrated for a given state and accumulative volume BPR functions for a given state, were proposed using the data of section volume collected by loop detectors installed in the upstream of the road segments. Simulation results for the same simulation scenario show that the accumulative volume BPR functions for general states significantly outperform the classical ones, and the two modified BPR functions for a given state are even better, with the smallest average estimation error of 8.05% obtained by the accumulative volume BPR functions for a given state under the medium heavy traffic state.