| Summary: | 碩士 === 國立臺灣大學 === 電機工程學研究所 === 104 === As V2V (Vehicle to Vehicle) and V2I (Vehicle to Infrastructure) area are well researched in recent years where the V2V technology can allow vehicles share information with nearby vehicles and the V2I technology can allow vehicles share information with nearby infrastructures by wireless communication device. The advanced driving assistance system can be divided into self-sufficient systems and interactive systems. The interactive systems, as the name implies, interact with infrastructures and/or other vehicles where these systems receive spatial information from nearby vehicles to prevent from forward collision. While the self-sufficient systems are limited to line-of-sight detection, the interactive systems account for scenarios farther ahead by predicting the position of occluded vehicle.
In this thesis, each vehicle is assumed to generate a local map which is a set of position measurements of nearby vehicles by using onboard low-cost GPS and ranging sensor, and shares it with the nearby vehicles by broadcasting via wireless communication device. When the ego-vehicle receives multiple local maps from nearby vehicles, the received local maps are matched with the local map generated by ego-vehicle by topology matching. The position measurements belong to the same vehicle are clustered by automatic points clustering based on k-Nearest Neighbor algorithm. Those position measurements belong to the same vehicle are combined by adaptive position estimation which updates position estimation according to accuracy of the sensor currently.
In this thesis, both simulation results and experimental results by proposed cooperative vehicle positioning system are presented. The simulation results show that the number of detected vehicle by the proposed cooperative vehicle positioning system is more than by a single sensor alone in most of the time. It turns out that a vehicle can get an extended view of surroundings to improve driving safety. The stereo camera is used as a ranging sensor equipped on the vehicle to produce position measurements in a real scenario. In the scenario, there are 3 vehicles nearby the ego-vehicle. First, the ego-vehicle estimates the range to the other 3 vehicles by stereo camera only. The experimental result show that the stereo camera gets a higher range estimation accuracy to the middle vehicle than the side vehicle. Second, the ego-vehicle estimates the range to the other 3 vehicles by the proposed cooperative vehicle positioning system. The position of the ego-vehicle is estimated by 4 measurements where 1 measurement is measured by GPS sensor of the ego-vehicle and the other 3 measurements are measured by both GPS sensors and ranging sensors of the other 3 vehicles respectively. The experimental results show that the accuracy of range estimation by the proposed system is better than by the stereo camera only.
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