Sensor Performance and Weather Effects Modeling for Intelligent Transportation Systems

Abstract

Optical sensors are used for several ITS applications, including lateral control of vehcles, traffic sign recognition, car following, autonomous vehicle navigation and obstacle detection. This paper treats the performance assessment of a sensor/image processor used as part of an on-board countermeasure system to prevent single vehicle roadway departure crashes. Sufficient image contrast between objects of interest and backgrounds is an essential factor influencing overall system performance. Contrast is determined by material properties affecting reflected/radiated intensities, as well as weather and visibility conditions. This paper discusses the modeling of these parameters and characterizes the contrast performance effects due to reduced visibility. The analysis process first involves generation of mherent roadoff-road contrasts, followed by weather effects as a contrast modification. The sensor is modeled as a charge coupled device (CCD), with variable parameters. The results of the sensor/weather modeling will be used to predict the performance on an in-vehicle warning system under various levels of adverse weather. Software employed in this effort was previously developed for the US Air Force Wright Laboratory to determine target/background detection and recognition ranges for different sensor systems operating under various mission scenarios.