一款功能强大的大学生方程式赛车方向盘---A powerful steering wheel for formula student racing.
High-speed Autonomous Drifting with Deep Reinforcement Learning
A fast-paced 2D arcade racing game built with Python and Pygame. Enjoy!
A 3D Low Poly Racing game developed with Godot 4.
GPU-Accelerated Reinforcement Learning for Individual Wheel Drive Autonomous Drifting Control
针对武汉理工大学WUTE电动方程式赛车队2025赛季E03赛车开发的车规级后车身域控制器项目，主控采用车规级微控制器S32K344，嵌入式软件基于符合AUTOSAR规范的MBDT开发，集成车身控制、低压电池监测、智能配电与TBOX多项功能。该项目包括后车身域控制器软硬件及配套QT数传上位机。
Formula Student -- Brake System Plausibility Device
针对武汉理工大学WUTE车队电动方程式赛车开发的多功能仪表项目，主控采用STM32H7B0VET6，5寸TFT屏，图形界面基于LVGL库开发，具备屏幕自动亮度调节、GUI动态显示、CAN报文解析，及旋转编码器操作、跑马灯显示等多项功能。
3D Multiplayer racing game with realistic car model. Created in Unity Engine.
A project to race 1:10 RC cars autonomously around a track while going as fast as possible
针对武汉理工大学WUTE车队电动方程式赛车开发的智能低压配电板项目，主控采用STM32F407VET6，基于FreeRTOS实现多任务调度和任务间通信，支持多路配电管理与诊断、及OLED诊断可视化，并通过解析来自VCU的CAN指令报文实现智能化配电，支持过流保护、浪涌保护多项安全功能。
Repositório de códigos da equipe Xangô E-Racing para o projeto de veículo elétrico para a competição Fórmula SAE na categoria Elétrico. O repositório serve também como ferramenta cooperativa para desenvolvimento de projetos, e para o projeto de Extensão Universitária de mesmo nome da UFBA.
A nostalgia racing game developed by MohammadReza Davari using Flutter, that rekindle your childhood memories.
UniKart is a simple asset that includes a controller for driving a kart.
The AlphaGo for car racing.
This repository contains the source code for the F1 Thunder. This offers an exciting and immersive racing game experience with realistic physics, stunning graphics, and dynamic gameplay. Players can enjoy various game modes, customize their cars, and navigate challenging tracks to test their driving skills. For more details read REDME.me
Cars learn how to drive using evolutionary algorithms and neural networks.
🏎️ AI Gesture Controlled Racing Game using MediaPipe
Reinforcement Learning-based project using PPO algorithm to enable a car to drive autonomously and efficiently in the CARLA simulation environment, optimizing for both speed and safety.
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