An effective method of pathfinding in a car racing game

The most common artificial intelligence in a racing game is waypoint navigation by carefully placing points (nodes) in the game environment to move the game-controlled characters between each point. This kind of pathfinding algorithm is a very time consuming and CPU intensive problem. In this paper, we present an algorithm to reduce the consuming time and simplify the implementation process. We simply put two collision detection points in front of the right and left side of the car, and then utilize the trick of collision detection by different color to automatic move the cars around the racetrack. In our algorithm, two adjusted variables have been carefully studied. The first variable is the collision detection distance, and the second variable is the turning radian of the car when collision is detected. The experimental results show that the lap time decreases as the collision detection distance increases, when the car do not stick by any curve. That is, the lap time decreases while the collision detection point is far from the car. It is because the car has more time to perceive the edge of motordrome to respond the collision. Similarly, the turning radian of the car increases, the time needs for turning the curve decreases, causing a decrease in lap time. However, when the cars change the racetrack from straight to the more curvature curve, or meet the successive curve in a short distance, large value of the collision detection distance or turning radian will cause the car stick in the corner of racetrack.