Modeling the Estimation Errors of Visual-based Systems Developed for Vehicle Speed Measurement

Abstract

This paper aims to modeling the relationship between the error of visual-based systems developed for vehicle speed estimation (as dependent variable) and each of the detection region length, the camera angle, and the volume-tocapacity ratio (V/C), as independent variables. Simulation software (VISSIM) is used to generate a set of video clips of predefined traffic based on different values of the dependent variables. These videos are analyzed with a video-based detection and tracking model (VBDATM) developed in 2015. Errors are expressed as differences between each of the actual speeds generated by VISSIM and the speeds computed by the VBDATM divided by the actual speed. The results conducted by the forward stepwise regression analysis show that the V/C ratio does not affect the accuracy of the estimate and there are weak relationships between the estimation error and each of camera position and the detection region length.