Abstract
To improve the safety capabilities of expressway service stations, this study proposes a method for detecting dangerous goods vehicles based on surveillance videos. The information collection devices used in this method are the surveillance cameras that already exist in service stations, which allows for the automatic detection and position recognition of dangerous goods vehicles without changing the installation of the monitoring equipment. The process of this method is as follows. First, we draw an aerial view image of the service station to use as the background model. Then, we use inverse perspective mapping to process each surveillance video and stitch these videos with the background model to build an aerial view surveillance model of the service station. Next, we use a convolutional neural network to detect dangerous goods vehicles from the original images. Finally, we mark the detection result in the aerial view surveillance model and then use that model to monitor the service station in real time. Experiments show that our aerial view surveillance model can achieve the real-time detection of dangerous goods vehicles in the main areas of the service station, thereby effectively reducing the workload of the monitoring personnel.
Highlights
An expressway service station is an area that is established along the expressway as a place for passengers to rest and refuel
According to “GB 6944-2012 Classification and Code of Dangerous Goods, a standard proposed by the Chinese Ministry of Transport [2], “dangerous goods” refer to chemical products with hazardous properties, and the term “DG vehicles” refers to specific vehicles which transport those dangerous goods by road
When a DG vehicle is involved in an accident at a service station, secondary accidents, such as toxic gas leaks and chemical explosions, can cause significant damage to surrounding facilities and personnel. erefore, improving the risk control capabilities regarding DG vehicles can significantly improve the safety of service stations
Summary
An expressway service station is an area that is established along the expressway as a place for passengers to rest and refuel. To improve the efficiency of safety management in the service station, a new method is required to reduce the workload of surveillance personnel. There needs a method to combine the information of different cameras, to realize the positioning function of the vehicle in the service station. Ese methods are suitable for some images with large overlapping areas but not for the surveillance video systems typically found in service stations. Because the installation of surveillance cameras in service stations is similar to their installation in traffic areas, it may be feasible to use IPM to process surveillance videos in a service station. Is method is best used in the expressway service station, and it is ideal for reducing the workload of surveillance personnel, thereby improving the efficiency of safety management in the service station.
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