Air Pollution and Fog Detection through Vehicular Sensors

Abstract

Abstract-We describe a method for the automatic recognition of air pollution and fog from a vehicle. Our system consists of sensors to acquire main data from cameras as well as from Light Detection and Recognition (LIDAR) instruments. We discuss how this data can be collected, analyzed and merged to determine the degree of air pollution or fog. S uch data is essentaial for control systems of moving vehicles in making autonomous decisions for avoidance. Backend systems need such data for forecasting and stragtegic traffic planning and control. Laboratory based experimental results are presented for weather conditions like air pollution and fog, showing that the recognition scenario works with better than adequate results. This paper demonstrates that LIDAR technology, already onboard for the purpose of autonomous driving, can be used to improve weather condition recognition when compared with a camera only system. We conclude that the combination of a front camera and a LID AR laser scanner is well suited as a sensor instrument set for air pollution and fog recognition that can contribute accurate data to driving assistance and weather alerting systems.

Weather Influence and Classification with Automotive Lidar Sensors

“…The number of points N t ( f 1,2,3 ) and mean distances r t are derived for each echo t ∈ 1, 2, 3 for the first, second or last return separately. The eigenvalues ( f13,14,16 ) were calculated from the covariance matrix of all points.…”

Real-Time Lane Region Detection Using a Combination of Geometrical and Image Features

“…In the case of camera sensors, the idea will be focused on the approach of enhancing visibility [25,26]. In the case of laser sensors, the analysis will be based on the surface patterns characteristic of the road in the presence of rain water [27] or fog [28]. Research in [7] showed that, in the case of nighttime, the laser demonstrates good performance.…”

Full Waveform LiDAR for Adverse Weather Conditions

“…However, examining Fig. 6 one can observe that relative to fog, in rain there is much higher attenuation [45], [46]. In an explicit study of the effects of adverse weather on automotive radar, Zhang et al [47] note that rain, snow, mist, and hail, can all have a significant impact, showing for example how the received power and probabilities of detection of vehicles and pedestrians reduce considerably as rain density increases.…”

“…If fog (or other weather) is an impediment to optical imaging because it attenuates and degrades the recorded image, the corollary is that measurements of passive optical and LiDAR image data can be used to estimate fog or other pollutant densities [45]. Pfennigbauer et al [22] suggested that it was possible to determine the visibility range and hence estimate fog density from a LiDAR waveform measured from immediately in front of the sensor to a maximum range of 30 m, since the rate of amplitude decay was a clear indication of this.…”