| CPC G06V 20/58 (2022.01) [B60W 60/001 (2020.02); G01C 21/3815 (2020.08); G01S 13/89 (2013.01); G01S 13/931 (2013.01); G06V 10/26 (2022.01); G06V 10/82 (2022.01); G06V 20/54 (2022.01); B60W 2420/403 (2013.01); B60W 2420/408 (2024.01); G06V 10/774 (2022.01)] | 17 Claims |

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1. A vehicle drivable area detection method, comprising:
processing, using a neural network, image data obtained by a camera apparatus, to obtain a first probability distribution of an obstacle;
obtaining a second probability distribution of the obstacle based on a time of flight and an echo width of a radar echo signal, wherein the echo width is a difference between a second time of flight of the echo signal and a first time of flight of the echo signal, wherein the second time of flight corresponds to a longest echo distance between a radar and the obstacle, and wherein the first time of flight corresponds to a shortest echo distance between the radar and the obstacle;
obtaining, based on the first probability distribution of the obstacle and the second probability distribution of the obstacle, a drivable area of a vehicle represented by a probability, wherein the probability is a probability that the vehicle cannot drive through the area; and either:
a) wherein the vehicle is an autonomous vehicle, planning a driving route for the vehicle based on the obtained drivable area;
or
b) wherein the vehicle is a manually driven vehicle, wherein the drivable area of the vehicle is represented in a form of a probability grid map; and wherein the probability that the vehicle cannot drive through the area is represented in the probability grid map, displaying the probability grid map on a display of the vehicle.
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