| Summary: | As we known, new high technology has played an important role in human life now. It is common that vehicle such as car, has become a basic means of transportation. More and more people relay on car instead of public transport no matter it’s in developed or developing country. However, with the popularity of cars, traffic safety has become a big problem and traffic accident occurred almost every day in the world. So it becomes extremely important to reduce the occurrence of traffic accident and increase traffic safety. On the basis of this principle, self-driving has come to the mind of human. With the success of self-driving, no skilled driver is needed and driving will become very easy and comfortable. In this case, it will reduce the traffic accident due to human factors. Radar is an essential factor in order to realize the self-driving. Automotive radar sensors are able to detect the obstacles around vehicles and collect all required real data. This project is aimed to develop obstacles detection and tracking algorithms using real radar measurement (points) data from automotive grade radars. Obstacles are able to be plotted using C++ programming through analyzing the real data measured by automotive radars. Several measurement parameters from sample real data are used to plot and display obstacles in order to analyze the pattern of surrounding environment of vehicles. Furthermore, several scenarios have been conducted from one sensor to four sensors to complete software functional testing using C++ programming.
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