Traffic density estimation using vehicle sensor data

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.