A method for determining a position of a vehicle in a road network, which includes a plurality of edges (202a to 202f), which are each associated with a road section or a lane on a road section, by means of a sensor group of the vehicle, in which first sensor data is captured by means of the sensor group, based on the first sensor data, a first probability is respectively associated with each edge of a plurality of first edges of the road network, with which the vehicle is located in the road section respectively associated with the first edge or in the lane respectively associated with the first edge, second sensor data is captured by means of the sensor group, based on the second sensor data and the probabilities respectively associated with the first edges, a second probability is respectively associated with each edge of a plurality of second edges of the road network, with which the vehicle is located in the road section respectively associated with the second edge or in the lane respectively associated with the second edge, and the second edge with the highest associated probability is ascertained as the position of the vehicle, characterized in that the plurality of second edges is a subset of the plurality of first edges, and the second probabilities are ascertained using a Bayes filter by means of a transition matrix P t+1,y,t,x and the first probabilities, wherein the first probabilities correspond to the probabilities p(z t lx), with which the first sensor data z t captured at the point of time t is captured on the assumption that the vehicle is located in a position x, and the second probabilities correspond to the probabilities p(y), with which the vehicle is located in a position y at the point of time t+1, and the transition matrix is ascertained based on ego motion data and/or image data, and transitions into a position, which is opposite to the direction of travel of the vehicle, are herein evaluated as improbable, wherein the image data is captured by means of a camera of the sensor group as at least a part of the first sensor data and/or as at least a part of the second sensor data, wherein the image data corresponds to an image of a capturing range in front of or behind the vehicle, and wherein the ego motion data of the vehicle is captured at least as a part of the second sensor data by means of the image data. first sensor data is captured by means of the sensor group, based on the first sensor data, a first probability is respectively associated with each edge of a plurality of first edges of the road network, with which the vehicle is located in the road section respectively associated with the first edge or in the lane respectively associated with the first edge, second sensor data is captured by means of the sensor group, based on the second sensor data and the probabilities respectively associated with the first edges, a second probability is respectively associated with each edge of a plurality of second edges of the road network, with which the vehicle is located in the road section respectively associated with the second edge or in the lane respectively associated with the second edge, and the second edge with the highest associated probability is ascertained as the position of the vehicle, characterized in that the plurality of second edges is a subset of the plurality of first edges, and the second probabilities are ascertained using a Bayes filter by means of a transition matrix P t+1,y,t,x and the first probabilities, wherein the first probabilities correspond to the probabilities p(z t lx), with which the first sensor data z t captured at the point of time t is captured on the assumption that the vehicle is located in a position x, and the second probabilities correspond to the probabilities p(y), with which the vehicle is located in a position y at the point of time t+1, and the transition matrix is ascertained based on ego motion data and/or image data, and transitions into a position, which is opposite to the direction of travel of the vehicle, are herein evaluated as improbable, wherein the image data is captured by means of a camera of the sensor group as at least a part of the first sensor data and/or as at least a part of the second sensor data, wherein the image data corresponds to an image of a capturing range in front of or behind the vehicle, and wherein the ego motion data of the vehicle is captured at least as a part of the second sensor data by means of the image data.