Abstract

The objective of this study is to analyze the possibility of using vehicle sensors to estimate traffic density in future traffic environments. For the analysis, the simulation experiments used in this study consist of three steps to estimate traffic density based on vehicle sensor data. The first step is to develop software module that can generate error of distance measurement in a similar way to the real road driving. In the second step, this study conducted traffic simulation experiments by combining the true distance value measured in the simulation with the error value calculated by the error generating module of the first step. Finally, we conducted evaluation procedure by comparing the estimation results of traffic density to the true density value. According to the experiment results, the use of front and rear radar showed best performance in that this case maintained low MAPE (Mean Absolute Percentage Error) results even at low probe vehicle ratio as compared to other cases. In case of camera sensor, it can be important alternative at the standpoint of potential future applications, especially under limited traffic environments of high ratio of sensor-equipped vehicle and congested traffic conditions such as LOS (Level of Service) D or E.

摘要

本研究的目的是分析在未来交通环境中使用车辆传感器估计交通密度的可能性。为了进行分析，本研究中使用的模拟实验包括三个步骤，以根据车辆传感器数据估计交通密度。第一步是开发软件模块，以类似于真实道路驾驶的方式产生距离测量误差。第二步，本研究将模拟中测得的真实距离值与第一步的误差生成模块计算出的误差值相结合，进行了交通仿真实验。最后，我们通过将交通密度的估计结果与真实密度值进行比较来进行评估程序。根据实验结果，前后雷达的使用表现出最佳性能，因为与其他情况相比，即使在低探测车辆比率的情况下，这种情况也能保持低 MAPE（平均绝对百分比误差）结果。在摄像头传感器的情况下，从潜在的未来应用的角度来看，它可能是重要的替代品，特别是在配备传感器的车辆比例高的有限交通环境和诸如 LOS（服务水平）D 或 E 的拥挤交通条件下。