Your main task in this project is to analyze the safety car deployment data
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Your main task in this project is to analyze the safety car deployment data

Introduction: 

This project aims at modeling the frequencies of safety car deployments per race in Formula One and the time intervals between safety car deployments in 2010-2019. A safety car in Formula One is deployed while the “yellow flags” are waved by the marshals and the Race Director decides that it is necessary to remove any hazards on the race track or that the racing cars need to slow down due to unfavorable track conditions (i.e., heavy rain).  When a safety car is deployed, in addition to the yellow flags, each driver sees “SC” boards on the sides of the track. Moreover, the same information is displayed on the steering wheel of each racing car. 

Safety cars and yellow flags are important components of Formula One racing to protect drivers’ and marshals’ lives. When the safety car is leading the race, each racing car needs to bunch up and follow the safety car without overtaking any other cars, unless they are allowed to unlap themselves. As the safety car goes around the track at a much slower speed than the normal racing pace, marshals can quickly remove any hazards on the track and improve the track condition without worrying about fast-moving racing cars. 

However, even with strict regulations under the yellow flag condition, accidents happen, especially during wet weather races. A notable recent incident happened at the 2014 Japanese Grand Prix, when a very promising young French driver Jules Bianchi of Marussia collided with a tractor crane under the “double yellow flag” condition. A “double yellow flag” condition indicates that marshals may be present on the track and the driver needs to prepare to stop, if necessary. Bianchi lost control of the car due to aquaplaning on the wet surface and suffered a fatal injury as a result of the collision with the tractor crane.  

The FIA (governing body of the Formula One races) took the incident very seriously and implemented a number of safety measures. One of them is an introduction of the “virtual safety car (VSC)”. Under VSC condition, each driver needs to slow down their car to the posted speed limit, usually resulting in a 35 to 40% speed reduction. Because it is a “virtual” safety car, under VSC, the actual safety car is not deployed; rather, each racing car is equipped with the device which automatically slows down to the posted speed limit under VSC.  

Even with the introduction of VSC in 2015, under severe conditions, safety cars are deployed once in a while. Here, an interesting question arises: Did the introduction of VSC change the frequency of safety car deployments? This is an important question to answer for race strategists, as the deployment of a safety car means that each team needs to react quickly to adjust their tire strategies. Each driver is required to make at least one pit stop to change their tires during the race, and a pit stop under the safety car condition implies that they can save about 20 seconds, possibly gaining several precious positions in the race without overtaking. At the same time, fresh tires typically make the racing car more drivable, increasing the chances of catching and overtaking the other racing cars in front after the pit stop. 

Related article: https://www.mclaren.com/racing/2019/canadian-grand-prix/how-make-rightcall-safety-car/ 

Note that the importance of understanding probability is emphasized in this article.  

Your Tasks in This Project: 

Your main task in this project is to analyze the safety car deployment data in Formula One to determine whether there are any changes in the frequency of safety car deployments between the pre-VSC era (2010-2014) and post-VSC era (2015-2019). That involves fitting reasonable distribution(s) to the data for the number of safety car deployments per race and time intervals between the safety car deployments in these two time periods. Then, by comparing these two distributions, you are asked to conclude whether strategic adjustments were necessary to account for increased/decreased safety car deployments after VSC was introduced in 2015. The dataset is originally retrieved from Kaggle 

(https://www.kaggle.com/datasets/jtrotman/formula-1-race-events), but it was further augmented by adding Type, Round, TotalRounds, TotalLaps, and Condition. These additional pieces of information were taken from the Wikipedia entries for the Formula One races.  

A thorough and complete analysis of the main task above is sufficient to receive full credit for this project. That is, you are not required to do any additional programming beyond what is given if you choose to do so. However, you are probably interested in doing a more detailed analysis of the dataset to make your analysis useful and interesting for the participating Formula One teams. To help you analyze the dataset in more detail, the dataset provided (augmented_safety_cars.csv) contains additional information such as type of the circuit (permanent or street) and track condition (dry, mixed, or wet).  

In addition, you will be asked to watch an interesting video titled “What Does An F1 Strategist Do?” (https://youtu.be/4CFkltWIc8o) so that you can see what Formula One strategists actually do before, during, and after each race. At the same time, you will see how they interact with racers, mechanics, race engineers, data analysts, and team principals.  

How This Project Works:  

This project consists of three parts; Probability Questions, Statistics Questions, and project write-up. For the Probability and Statistics Questions, you need to answer the questions given below. For the project write-up, you may choose to summarize the results based on the R code given. However, to make the project more interesting, you are encouraged to carry out additional analysis. If you find anything interesting, you may choose to write about your interesting finding(s) instead. To make sure that what you decide to write in your write-up is appropriate, please talk to the instructor before you do anything. The instructor will be happy to assist you with additional programming if necessary. 

Probability Questions: 

1. Watch “What Does An F1 Strategist Do?” (https://youtu.be/4CFkltWIc8o) and describe how the Formula One strategist position is related to your major(s) in a paragraph or two. Note: Everyone on your team needs to write a separate paragraph or two.

2. Suppose that you look at each of

Hint
Statistics1. Formula One strategists are responsible for using real-time data to develop and implement strategies for their teams during races. They rely on advanced technologies and algorithms to analyze data from sensors and various sources, such as weather forecasts, to make informed decisions. This requires expertise in fields such as data analytics, computer science, and engineering, as well ...

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