# Why is the equation $S = ut + \frac 1 2 a t^2$ not used directly to calculate final position of an object?

Most articles I've read on physics integration in games say to do it like this:

1. first we calculate velocity after a certain elapsed time dt like this:
velocity.x += acceleration.x * dt

2. then we calculate position as: x += velocity.x * dt

But this will definitely give an inaccurate result.

Therefore, what is the reason to not use the equation of motion $$\S = ut + \frac 1 2 a t^2\$$ to calculate an accurate displacement and add it to the position?

• What you're describing in steps 1 & 2 is called (symplectic) Euler integration. It's popular to show in tutorials because it's simple, easy to understand, and easy to build upon (even a reader who's unfamiliar with calculus can reasonably guess at how they'd add a new physics influence into either the velocity or position step). It's not the only tool in use in shipped game systems though. – DMGregory Jun 1 '19 at 20:17
• In games, positions and velocities are usually changing all the time, especially when a game has physics and collisions (and given that it has gravity it almost certainly has). A simple approach is better in that case. However, there is nothing that prevents you from using more accurate formula, except that you will have to recompute coefficients on every external change of position, speed or gravity. – trollingchar Jun 1 '19 at 20:17

First, the expression $$S = u\,dt + \frac{1}{2}\,a\,dt^2$$ is not "accurate" in absolute sense. It is just a second order (in dt) approximation to the real solution. And actually, the other one you provided (which is called symplectic euler) is also a second order approximation, as you can see if you plug the first equation

velocity.x = old_velocity.x + acceleration.x * dt


into the second equation

 x = old_x + velocity.x * dt
= old_x + (old_velocity.x + acceleration.x * dt) * dt
= old_x + old_velocity.x * dt + acceleration.x * dt * dt


the difference is that here you are using the new velocity for updating x. The consequence is a nice physical property that is the conservation of (a quantity close to) the energy. Conservation of energy means that you do not get an unstable simulation, which is important.

In fact, the order of approximation is not the most important aspect to consider when choosing an integration scheme. Lower order symplectic algorithms are sometimes preferred to other higher order algorithms (like Runge Kutta) even in some scientific simulations.

If you are looking just for the most accurate solution, then you should look into the Implicit Euler method solved iteratively with the Newton method which can be made accurate until a desired threshold.

We can do this:

position = initial_position + velocity * t + 0.5 * acceleration * t * t;


First remember that there could be collisions. We need to detect and solve collisions. Perhaps we do, we solve the collision by picking a new initial_position and velocity for the object.

Second remember that not every object that has physical interaction follows the laws of motion. Yeah, I know, you use the formula for those which do. The issue is that there are motions that the physics engine cannot predict.

Let us take the simple example of the game asteroids. The user steers and accelerate the avatar ship. We are not only talking about an acceleration that change over time, we are talking about an acceleration that change over time in an unpredictable manner (it depends on user input). In this case you will need to compute the position of the avatar ship each frame.

That means that you will have two different pipelines for physics. One for things that the user controls or triggers, and one for thing that it does not.

For another example, platformers have some interesting challenges. Let us say, it is a bad platformer, where you cannot control the avatar midair. So, in the air, it behave as an object beyond user control, but on land it can walk, the user has control over its speed. Now you got an object that switches gears.

How about enemy agents? Perhaps we can push them as per physics, but they will move according to some form of AI. Therefore the physics engine cannot predict their motion, which means we will need the physics we created for player controlled things.

Would it not be better to have a single physics pipeline instead of two? Well, the one that is used for the player controlled things is more versatile. That one wins. So, we compute at increments, frame by frame.

Perhaps you want something like this:

position = position + velocity * dt + 0.5 * old_acceleration * dt * dt;
acceleration = compute_acceleration();
velocity = velocity + 0.5 * (old_acceleration + acceleration) * dt;
old_acceleration = acceleration;


That is a variant of Second Order Verlet Integration known as Velocity Verlet (it is similar to leapfrog integration). And, yes, some games use it. It is better than Euler integration. Many people recommended, usually it is all you need.

With that said, Velocity Verlet will have stability problems (it will drift when dt is not stable). A variant known as Time Adjusted Velocity Verlet is used to compensate for that problem. However, depending on the simulation, objects simulated with can seem to lose energy (which is hidden if you are doing drag or friction too).

Notes:

• With Euler integration objects can gain energy. Which is worse.
• It is possible to make a Time Adjusted Euler Integration to be stable for common use, and it behave better than Time Adjusted Velocity Verlet in some situations.
• The Velocity Verlet algorithm assumes that acceleration depends on the updated position, but not the velocity.

There are algorithms with better properties in exchange of more computing time. Although that trade-off is less relevant for modern computers, it still is (in particular for the higher frame rates and large numbers of objects).

That is why different games use different integration methods. Being Euler and Velocity Verlet among the more popular.

This discussion often leads to Fourth order Runge-Kutta (RK4). It is more CPU expensive, and harder to understand and implement.

I will refer you to Physics for Flash Games by Richard Lord for a comparison of the common implementations.

• Note that he's using symplectic euler, not explicit euler. So the system should not gain energy. – Turms Jun 1 '19 at 22:49