Air pollution and fog detection through vehicular sensors

Sallis, P
Dannheim, C
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IEEE Xplore

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. Such data is essential for control systems of moving vehicles in making autonomous decisions for avoidance. Backend systems need such data for forecasting and strategic 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 LIDAR 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.

Air pollution detection; Fog detection; Weather detection; Remote sensing; LIDAR; Colaborative driver assistant functions; Spatial resolution; Air pollution forecasting services
Asia Modelling Symposium 2014 held at Caesar Park Hotel, Taipei; Pacific Regency Hotel, Kuala Lumpur, Taipei and Kuala Lumpur, 2014-09-23 to 2014-09-25
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