Whenever you’ve played a video game, there’s almost a hundred percent chance you’ve interacted with artificial intelligence (AI). Whether you’re a fan of racing, strategy, shooters, or other game genres, there will always be elements in games controlled by AI. We figured out how AI was implemented in racing games specifically and found examples of games with this technique applied.
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Implementation of AI in games
Developing artificial intelligence for a racing game is quite a challenge. At the most basic level, computer-controlled cars should at least be able to move around the track. There are various ways of making that work. One of the earliest methods, used even before central processors could perform complex calculations, was to use lines drawn in advance along the track, which the machines controlled by the AI were moving along. These are known as splines. Splines can be simple geometric shapes such as rectangles and complex polygons or curves, in this case – cars. Later, the splines became more complex and were no longer just lines but contained data sets that suggested behavior for the car in different conditions. For example, if there is a sharp turn in the spline, there will also be information that the car needs to slow down.
How the tracks are constructed
With the development of central processors, programmers began to teach AI to find a path on a track based on its physical shape. In this case, the same spline was also put into the track, but only as a guide, a sample of the most efficient route. The nature of this route depends on the genre of the racing game. In arcades, where you need to improve the track, the spline is sharpened to pick up the most effective improvements, such as speed boosts, rather than the fastest car passing the track.
However, in challenging simulations, such as Formula 1 racing, the spline is a single line packed with detailed information about the tactics of each section of the track. Yet, if different cars compete in a race with different characteristics, there is a lot of data to be loaded into the spline, which makes it more difficult to process. Therefore, in such cases, developers resort to creating methods that estimate the optimum speed of each car in real-time, taking into account all changes on the track.
What the competition strategy is based on
Whenever AI is used, the main objective is to recreate the feeling of another car being driven by a human and, secondly, to make the race fascinating. No matter how good the AI is, it would be wrong if all the cars driven by the computer drove far ahead. In this case, the user will find alone on the track and get bored. The most popular method, which helps to avoid such a situation, is called the rubber band. It is used almost in any racing game as if tying the rubber band of the AI racers to the player’s car. AI-driven cars are not trying to beat players but rather play different roles in making competing more exciting.
This way, the Need for Speed game series used the Catch-up system, a rubber band. The idea behind this system is that computer-controlled cars go faster the further away you are from them. Conversely, their speed will be artificially reduced if you suddenly lag far behind. Ultimately, no matter how hard you try to get away from your rivals, they will catch up with you. So when you decide to play a race next time, pay attention to the patterns repeated in the races and how the AI works in reality.