vinybrasil/race-simulation

This repository contains a race simulation to determine a race strategy for motorsport circuit races. Race strategy in this context means the determination of pit stops.

Introduction

This repository contains a race simulation for the simulation of motorsport circuit races. The intended application is the determination of an appropriate race strategy, i.e. of the pit stops (number of stops, inlaps, tire compound choice, possibly refueling). The race simulation considers long-term effects such as mass reduction due to burned fuel and tire degradation as well as the interactions between all race participants. It is based on a lap-wise discretization for fast calculation times. Probabilistic influences are also modeled and can be evaluated using Monte Carlo simulation.

Contact person: Alexander Heilmeier.

List of components

• helper_funcs: This folder contains helper functions that are used in more than one of the programs.
• racesim: The folder includes all class definitions required to simulate an entire race (src folder). The input folder contains the required parameter files for every race, the output folder is created during execution and will then contain .csv files with lap times, race times, and positions in every lap.
• racesim_basic: This folder calculates the best race strategy (leading to a minimal race time) under the assumption of a free track, i.e. without opponents. Therefore, it can be seen as a minimalistic race simulation.

Dependencies

Use the provided requirements.txt in the root directory of this repo, in order to install all required modules.
pip3 install -r /path/to/requirements.txt

The code is developed with Python 3.8 on Windows 10 and tested with Python 3.8 on Ubuntu.

Solutions for possible installation problems (Windows)

cvxpy, cython or any other package requires a Visual C++ compiler -> Download the build tools for Visual Studio 2019 (https://visualstudio.microsoft.com/de/downloads/ -> tools for Visual Studio 2019 -> build tools), install them and chose the C++ build tools option to install the required C++ compiler and its dependencies

Solutions for possible installation problems (Ubuntu)

1. matplotlib requires tkinter -> can be solved by sudo apt install python3-tk
2. Python.h required quadprog -> can be solved by sudo apt install python3-dev

Intended workflow

The intended workflow is as follows:

• racesim_basic: Use the simplified race simulation to determine the fastest basic race strategy. It can be used as a first guess for the race strategy in the race simulation.
• racesim: Use the race simulation to simulate the race and to optimize the race strategy.

Running the basic race simulation

If the requirements are installed on the system, follow these steps:

• Step 1: You have to adjust a given or create a new parameter file (.ini) for the simulation. The parameter files are contained in /racesim_basic/input/parameters.
• Step 2: Check the user inputs in main_racesim_basic.py.
• Step 3: Execute main_racesim_basic.py to start the race simulation.

Running the race simulation

If the requirements are installed on the system, follow these steps:

• Step 1: You have to adjust a given or create a new parameter file (.ini) for the race to simulate. The parameter files are contained in /racesim/input/parameters.
• Step 2: Check the user inputs in the lower part of main_racesim.py.
• Step 3: Execute main_racesim.py to start the race simulation.

Contained parameter files

We included exemplary parameter files for the 121 Formula 1 races in the seasons 2014 - 2019. They were automatically created on the basis of our Formula 1 timing database (link is below). The program used for this was developed by Marcel Faist as part of his master's thesis within the project. Please keep in mind that an exact reproduction of the real races in the simulation is practically impossible.

Detailed description of the race simulation (deterministic parts)

Please refer to our paper for further information:
Heilmeier, Graf, Lienkamp
A Race Simulation for Strategy Decisions in Circuit Motorsports
DOI: 10.1109/ITSC.2018.8570012

Detailed description of the race simulation (probabilistic effects and random events)

Please refer to our paper for further information:
Heilmeier, Graf, Betz,Lienkamp
Application of Monte Carlo Methods to Consider Probabilistic Effects in a Race Simulation for Circuit Motorsport
DOI: 10.3390/app10124229

Related open-source repositories

• Lap time simulation: https://github.com/TUMFTM/laptime-simulation
• Race track database: https://github.com/TUMFTM/racetrack-database
• Formula 1 timing database: https://github.com/TUMFTM/f1-timing-database