TAILIEUCHUNG - New trends and developments in automotive industry Part 7

Tham khảo tài liệu 'new trends and developments in automotive industry part 7', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | 170 New Trends and Developments in Automotive Industry As a matter of fact the implementation of a solution robust enough to deal with the strict requirements of the proposed application is not easy. In particular such a system must guarantee at the same time a few missed alarms . the number of missed vehicle object detections and a few false alarms . the number of wrongly detected vehicles objects . To this aim a feature-based tracking method is proposed where a Kanade-Lucas-Tomasi KLT feature tracking is used in a particle filter framework to predict local object motion Dore et al. 2009 . In particular such a multitarget tracking algorithm exploits a sparse distributed shape model to handle partial occlusions where the state vector is composed by a set of points of interest . corners enabling to jointly describe position and shape of the target. An instance of the results obtained with the cited algorthm is presented in Fig. 8 Fig. 8. Vehicle s tracking algorithm an example CAN-bus The Controller Area Network also known as CAN-bus is a vehicle bus standard designed to allow microcontrollers and devices to communicate with each other within a vehicle without a host computer. The CAN-bus interface allows extracting context data related to the vehicle s internal state. The data are sent asynchronously via an internal Ethernet network as UDP packets. A not exhaustive list of the data made available by the CAN-bus is provided in the following Light it indicates activation of the lights of the vehicle Lateral acceleration positive value corresponds to the left Longitudinal acceleration Parking brake Speed Steering angle positive value corresponds to the left . These and other data are made available and properly used according to the different type of application. Fig. 9 shows an example where the video stream coming from the camera positioned in order to frame the external context and the temporal evolution graph of three different data coming from the .

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