Abstract
In this paper, we propose a new free space detection algorithm for autonomous vehicle driving. Previous free space detection algorithms often use only the location information of every frame, without information on the speed of the obstacle. In this case, there is a possibility of creating an inefficient path because the behavior of the obstacle cannot be predicted. In order to compensate for the shortcomings of the previous algorithm, the proposed algorithm uses the speed information of the obstacle. Through object tracking, the dynamic behavior of obstacles around the vehicle is identified and predicted, and free space is detected based on this. In the free space, it is possible to classify an area in which driving is possible and an area in which it is not possible, and a route is created according to the classification result. By comparing and evaluating the path generated by the previous algorithm and the path generated by the proposed algorithm, it is confirmed that the proposed algorithm is more efficient in generating the vehicle driving path.
Highlights
In order for an autonomous vehicle to travel stably in various environments, it is important to recognize obstacles around the vehicle
If it is possible to know at what speed and direction the surrounding obstacles are moving with respect to the driving vehicle, more efficient path generation will be possible. To solve this problem and increase the efficiency of path generation in free space, we propose a new algorithm for detecting free space based on the speed information of obstacles
As a result of Free Space Detection (FSD) without speed information, it can be seen that a path with a collision risk is created even though there is an obstacle moving in the direction opposite to the vehicle direction
Summary
In order for an autonomous vehicle to travel stably in various environments, it is important to recognize obstacles around the vehicle. In an environment in which lanes are not recognized while driving or in a road environment in which a precise map is not built, a path must be created by detecting an obstacle-free space, that is, a free space to generate a driving path. There are many cases of detecting free space using only the location information of obstacles. In this case, the behavior of the surrounding obstacles cannot be predicted, meaning there is a high possibility of creating an inefficient path in terms of safety.
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