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# Euclidean distance and others: bikers, taxi drivers and the distance definition [Part 1]

**Hello again everyone!**

For those who don’t know us, a very brief introduction on who we are and where we go! **MathIsInTheAir** is an italian blog of Applied Maths and surroundings and here are the links: english version and italian version. Although our english blog contains not so many posts, we would like to expand it in the very near future. I don’t want you to get bored, so if you like you may visit our websites or you may read the “not so quick introduction” to MathIsInTheAir I did last year.

Today I just want to present our next english mathematical post, called “**Euclidean distance and others [part 1]**” written by Pasquale Napolitano. This is a great post by Pasquale, which explores the concept of distance and tries to explain it in a very easy and friendly way.

Be Euclidean today and read it!

**by MathIsInTheAir**

# Euclidean distance and others: bikers, taxi drivers and the distance definition [Part 1]

In these days I and a collegue of mine had a conversation on a recent law proposed by Ségolèn Royal in French Parlament.

Shortly, this law would provide a monetary refund for those who go to work by bike; the refund is proportional to the distance covered every day.

After a moment, everyone of us started thinking at the main point of it; everyone knows that there are lots of choices of paths when going from a point A to a point B in a city and everyone knows that the paths have different lengths. Which of those paths is used for deciding the amount of money to be refunded? We agreed on the answer…the shortest one; and you, do you agree with us? Probably someone among my readers doesn’t know there are a lot of way to calculate the shortest distance between two points. In this post we will talk about distances, the way used to calculate them and some basic concepts in topology and limits.

The easiest way to calculate the distance between two points is the Euclidean distance. The Euclidean distance is the first we learn at school and the one we are confident to. Imagine an employee that lives in an imaginary point A on a bi-dimensional plane. The company is situated in a point B on the same plane. The best choice to go to work for him is to move straight on from A to B. To draw it, we can fix two different points in the plane and connect them with a stright line: this is the Euclidean distance.

For a more detailed discussion suppose to introduce a reference system with the origin in a certain point O. In the reference system both point A and B would have two coordinates (we are using a bi-dimensional plane, in a three dimensional space such as the Earth there are three coordinates).

The formula for Euclidean distance between A and B is

\[d=\sqrt{(x_2−x_1)^2+(y_2−y_1)^2}\]

really easy to figure out.

# You are not the only one…

It is well known that the civilization improves and some houses are built on the spece between point A and B.

Our friend, now, has to change the way to go from home to work according to the streets available between the houses.

The employee will pass two houses in vertical direction (up – down direction on your screen) and three houses in horizontal direction (left – right direction) and this the shortest way from home to work and is surely grater than Euclidean distance… a lucky fact for the company who refund the worker.

The distance shown above is called taxi distance or Manhattan distance and is expressed by the following equation

\[d=|x_2−x_1|+|y_2−y_1|\]

This is a valid alternative to Euclidean distance in everyday life; for example when we drive we use the taxi distance to decide the shortest way to go from our position to the final destination.

But now we have a problem: in order to save some money, the company establishes to refund only higher distance between the vertical and the horizontal. In the case of our employee only the horizontal distance will be refunded (three houses versus two houses in vertical direction). This could seem a stretch of taxi distance but there is a refined equation to express this distance:

\[d=max(|x_2−x_1|,|y_2−y_1|)\]

this is called distance of infinity.

At the end, there is another distance we can investigate: the minimum distance. It is obtained changing max with min in the distance of infinity; simply only the shortest distance is kept in account and is written as

\[d=min(|x_2−x_1|,|y_2−y_1|)\]

As we have seen, there are lots of different distances between two points. We are more familiar with some definitions of distance than others but, each definition given above, is a valid distance in the physical word.

An entirely mathematical definition rises up some questions; What is the best way to measure a distance? How many different distances are there?

We will answer these questions in reverse order. With a little imagination we can suppose that there are infinite ways to define a distance. From a mathematical point of view every equation involving subtractions of coordinates of two points is a distance. After this answer, some of us are starting to have doubts the existence of a universal definition for distances.

It is almost totally true. We cannot define a unique distance definition but we can define some criteria a distance definition must be respect.

### …Continue reading our post:

**English version: here**

**Italian version: here**

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