istraffic Automatic Traffic Monitoring system

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1 istraffic Automatic Traffic Monitoring system

2 Goal The goal of the system is to perform an automatic analysis of the traffic flow to detect events like slow traffic, queues, stopped vehicles, etc. using only image processing. The main processing is performed on board of an intelligent cam: the system has been developed using a Sony Smart Cam, with LINUX operating system on board. The system has been tuned on the A11 motorway, nearby Florence. Processing During the camera installation the system is configured by the definition of the interested area, the lanes inside it and some geometrical references. At the start up a reference background is set and then is continuously updated. Each image is then processed for detecting vehicle blobs. Each minutes some traffic parameters are updated: - lanes occupation. - lanes average speed. - number of vehicles per lanes. These parameters are the inputs of a fuzzy logic system based on rules used to set the traffic flow state for both each lane and the entire roadway: - null or low traffic. - regular traffic. - slow traffic. - queue. Furthermore, particular traffic behaviours are detected, that is: - stopped vehicle. - started up vehicle. - vehicle moving in the opposite direction. When one of these behaviours is detected or the traffic state is changed a corresponding event is generated, and a corresponding video clip is recorded. When an event is generated an alarm signal is generated. Another feature of the system is the generation of an MPEG4 video stream for remote monitoring of the controlled roadway stretch. System architecture The system is composed by three main subsystems, apart from the network equipements: - SC: Smart Cam, an intelligent LINUX-based camera, for image acquisition and image processing as described in the previous section. - VS: Video Server, for MPEG4 streaming and events video clip recording. - MU: Monitoring Unit, for remote system monitoring and events handling.

3 In this architecture, MU can connect several VS, that in turn can connect several SC. If enabled, each SC creates a continuous JPEG image streaming towards VS, that converts it in an MPEG4 streaming towards MU. Depending on the network, a limited number of streaming can be monitored simultaneously. VS has a local mass storage where can be stored the video clips corresponding to the events detected by SC are stored. MU has a GUI for monitoring the mpeg streaming of the selected cams, and for advising the operator of the events generated by any cam. The operator can view the corresponding video clip. MU can also interface a Variable Message System to advise the road users. The block diagram of the architecture is represented in the following figure: The system con be configured in a simplified version, without video server, where MU receives directly from the SCs the JPEG streaming, and performs the video clip filing. The smart cam generates an M-JPEG streaming that can have problems with a slow or busy networks. We are going to implement the MPEG4 streaming and the second generation XCI cams, for a better performance of this solution. The block diagram of this simplified architecture is represented in the following figure:

4 Network interface Generally, in an open environment, SC and VS can be connected via a local WI-MAX lan. In tunnel application, where power line for tunnel lights is present, can be used a powerline lan. Mixed solution are possible. User interface A GUI is implemented in the MU running on both WINDOWS and LINUX operating systems. ON this GUI, the operator can perform the following operations: - real time monitoring of a selected smart cam. - real time monitoring of the traffic state detected by the fuzzy system. - watching the events video clips. - Watching the traffic statistics for minute, hour or day. Some screen shots from the GUI:

5 Traffic flow state monitoring: Statistic monitoring:

6 Event monitoring: Detailed Event Video Clip Monitoring:

7

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