The invention relates to a multi-information-fusion-based high precision localization method for an unmanned vehicle, and the multi-information-fusion-based high precision localization method can be applied to environment perception and intelligent decision-making of the unmanned vehicle. Through cooperation of an offline map and online sensing information, high-precision real-time positioning can be realized. The offline map records road traffic information of a driving area of the unmanned vehicle. The online sensing information includes lane lines and road boundaries. When the unmanned vehicle runs in a map area, according to location information given by an inertial combined navigation system, an approximate location of the vehicle is determined, a local map near the approximate location is obtained, the lane lines in front of the vehicle and the road boundaries on both sides of the vehicle can be detected by a vehicle sensor, the relative position of the vehicle and the lane lines and the road boundaries can be determined, by contrast of the location of the vehicle in the map, deviation is calculated, a location error is corrected, and high-precision localization can be achieved.