1. A traveling environment recognition device recognizes a traveling environment of one's own vehicle, the device comprising: own vehicle position determining means for determining a position and a traveling direction of the own vehicle in an absolute coordinate system with its origin at an arbitrary point on the basis of information from one or more sensors for detecting a quantity of motion of the own vehicle; and occupancy grid map generating means for dividing the absolute coordinate system into a grid of equal cells, and generating an occupancy grid map that stores an occupancy probability of each of a plurality of obstacles to the position and traveling direction of the own vehicle for each cell of the grid, and updating the occupancy probability according to Bayesian inference, wherein the occupancy grid map generating means comprises: object occupancy probability calculating means for calculating, on the basis of information from a radar device that detects a forward object of the own vehicle, which is one of the obstacles, the occupancy probability of the forward object for each cell of the occupancy grid map; other vehicle occupancy probability calculating means for calculating, on the basis of information from a communication device that receives positional information transmitted from another vehicle around the own vehicle, which is one of the obstacles, the occupancy probability of the another vehicle for each cell of the occupancy grid map; traffic lane line occupancy probability calculating means for calculating, on the basis of information from a storage device that stores map data which allows a position to be specified of a traffic lane line which is one of the obstacles, the occupancy probability of the traffic lane line for each cell of the occupancy grid map; and occupancy probability blending means for blending for each cell of the occupancy grid map, the occupancy probability calculated by the object occupancy probability calculating means, the occupancy probability calculated by the other vehicle occupancy probability calculating means, and the occupancy probability calculated by the traffic lane line occupancy probability calculating means to provide a blended occupancy probability of the obstacles to the position and traveling direction of the own vehicle, wherein the radar device is configured to detect a three-dimensional object as the forward object, the object occupancy probability calculating means is configured to, when the radar device detects a single three-dimensional object, calculate the occupancy probability of the three-dimensional object according to a first sensor model that defines the occupancy probability of the three-dimensional object as a function of a direct distance from a detection wave emitting point of the radar device along a straight line through the detection wave emitting point and an observed point of the three-dimensional object, and when the radar device detects two three-dimensional objects at their respective observed points along a straight line through the two observed points and the detection wave emitting point of the radar device, the object occupancy probability calculating means calculates the occupancy probability of the two three-dimensional objects according to a second sensor model that defines the occupancy probability of two the three-dimensional objects as a function of a direct distance from the detection wave emitting point of the radar device along the straight line such that the occupancy probability at the observed point closer to the own vehicle is set smaller than the occupancy probability at the observed point further away from the own vehicle.