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A system that helps driver to reduce stress, improve performance and protection.

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πŸš— AIForDriver

AIForDriver is a driver assistance system designed to reduce stress, improve driving performance, and enhance safety.

AIC Logo

AIForDriver for AIC
Decentralized nodes β€’ Ethical scaling β€’ auto-driven

🧠 Objectives

  • Analyze the driver's mental and physical state through sensors and behavioral data.

  • Provide recommendations or warnings to improve concentration and reduce stress.

  • Integrate AI technologies to support real-time decision-making.

πŸ“¦ Key Features

  • Recognizes driver emotions and fatigue levels.

  • Suggests appropriate music, rest breaks, or route adjustments.

  • Warns of distraction or drowsiness.

  • Intuitive and easy-to-use interface.

Structure

AIForDriver/
β”‚
β”œβ”€β”€ core/                  # TrΓ‘i tim hệ thα»‘ng, xα»­ lΓ½ thời gian thα»±c
β”‚   β”œβ”€β”€ kernel/            # Bα»™ lΓ΅i (reactor loop, memory, adaptive runtime)
β”‚   β”œβ”€β”€ protocol/          # Giao thα»©c giα»―a cαΊ£m biαΊΏn, AI vΓ  trΓ¬nh Δ‘iều khiển
β”‚   β”œβ”€β”€ behavior/          # Logic hΓ nh vi Δ‘iều khiển vΓ  phαΊ£n α»©ng
β”‚   └── security/          # BαΊ£o vệ, phΓ‘t hiện bαΊ₯t thường, tα»± vệ
β”‚
β”œβ”€β”€ modules/               # CΓ‘c module mở rα»™ng cΓ³ thể thay thαΊΏ hoαΊ·c plug-in
β”‚   β”œβ”€β”€ sensor/            # Camera, Lidar, Radar, IMU, GPS,...
β”‚   β”œβ”€β”€ safety/            # Hệ thα»‘ng phanh, trΓ‘nh va chαΊ‘m, fallback
β”‚   β”œβ”€β”€ control/           # Adaptive Control, PID/LQR/Fuzzy
β”‚   └── analytics/         # PhΓ’n tΓ­ch dα»― liệu, thα»‘ng kΓͺ, logs, học tΔƒng cường
β”‚
β”œβ”€β”€ protocol/              # Giao thα»©c truyền thΓ΄ng & Δ‘iều phα»‘i
β”‚   β”œβ”€β”€ core/              # C++ lα»›p Δ‘iều phα»‘i chΓ­nh
β”‚   β”‚   β”œβ”€β”€ control_channel.cpp
β”‚   β”‚   β”œβ”€β”€ driver_state.cpp
β”‚   β”‚   β”œβ”€β”€ emergency_protocol.cpp
β”‚   β”‚   └── sensor_sync.cpp
β”‚   └── lua/               # Layer trΓ­ tuệ thΓ­ch nghi vΓ  an toΓ n
β”‚       β”œβ”€β”€ adaptive_driver.lua
β”‚       └── safety_trigger.lua
β”‚
β”œβ”€β”€ runtime/               # CΖ‘ chαΊΏ chαΊ‘y vΓ  phα»‘i hợp runtime (giα»‘ng Adaptive OS)
β”‚   β”œβ”€β”€ executor.cpp       # Bα»™ thα»±c thi nhiệm vα»₯ (cΓ‘c lệnh Δ‘iều khiển)
β”‚   β”œβ”€β”€ scheduler.cpp      # LαΊ­p lα»‹ch phαΊ£n α»©ng theo chu kα»³ cαΊ£m biαΊΏn
β”‚   β”œβ”€β”€ bridge_lua.cpp     # Giao tiαΊΏp vα»›i Lua layer
β”‚   └── event_loop.cpp     # Reactor/Observer để quαΊ£n lΓ½ sα»± kiện
β”‚
β”œβ”€β”€ utils/                 # Tiện Γ­ch nền
β”‚   β”œβ”€β”€ serializer.cpp
β”‚   β”œβ”€β”€ checksum.cpp
β”‚   β”œβ”€β”€ packet_parser.cpp
β”‚   β”œβ”€β”€ compress.cpp
β”‚   └── logger.cpp
β”‚
β”œβ”€β”€ config/                # Tệp cαΊ₯u hΓ¬nh hệ thα»‘ng
β”‚   β”œβ”€β”€ protocol_spec.json
β”‚   β”œβ”€β”€ packet_structure.json
β”‚   β”œβ”€β”€ adaptive_metadata.json
β”‚   β”œβ”€β”€ version_manifest.yaml
β”‚   └── error_code.json
β”‚
β”œβ”€β”€ docs/                  # TΓ i liệu nα»™i bα»™
β”‚   β”œβ”€β”€ architecture.md
β”‚   β”œβ”€β”€ design_notes.md
β”‚   └── safety_standards.md
β”‚
└── tests/                 # Unit test vΓ  simulation
    β”œβ”€β”€ test_protocol.cpp
    β”œβ”€β”€ test_lua_bridge.cpp
    └── test_emergency.lua

Detailed operating flow :

Sensors β†’ SensorSync β†’ DriverState β†’ Lua:SafetyTrigger
                     ↓
              Lua:AdaptiveDriver
                     ↓
           ControlChannel β†’ Vehicle Actuators
                     ↓
           EmergencyProtocol (nαΊΏu cαΊ§n)

Combining hardware response (C++) and software learning (Lua):

  • C++: ensures immediate response, hardware control, real-time.

  • Lua: adjusts strategies, adapts, self-learns, handles complex exceptions.

Logic layer.

β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
β”‚     Application Layer    β”‚ β†’ Dashboard, User Feedback, HMI
β”œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€
β”‚     Adaptive Protocol    β”‚ β†’ Lua + Core for driver protocol. 
β”œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€
β”‚     Behavior Engine      β”‚ β†’ compiler, learning, behavior
β”œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€
β”‚     Sensor Integration   β”‚ β†’ sensor, synchronize raw data
β”œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€
β”‚     Runtime Layer        β”‚ β†’ Scheduler, Executor, Lua Bridge
β”œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€
β”‚     Security Layer       β”‚ β†’ Self-defense, Intrusion detection
β”œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€
β”‚     Kernel Layer         β”‚ β†’ Memory, State Control, Introspection
β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜

Vision :

| Phase            | Mission                                      | Main Components                   |
| -------------------- | -------------------------------------------- | ------------------------------------------------- |
| **11-12/2025** | Complete `protocol/core` + `lua` + bridge  | `control_channel`, `lua_bridge`, safety unit test |
| **Q1/2026**          | Add `runtime/` and `security/` sandbox       | `executor`, `scheduler`, `intrusion_detector`     |
| **Q2/2026**          | Expand `behavior/` and `analytics/`          | Reinforcement Learning, Behavior Log              |
| **Q3/2026**          | Distributed connection (AIForDriver Cloud Network) | `p2p_protocol`, `trust_manager`, `update_sync`    |

πŸ› οΈ Settings

git clone https://github.com/AdaptiveIntelligenceCircle/AIForDriver.git
cd AIForDriver

πŸš€ Testing

gcc -o helpdriver.cpp helpdriver

The system will begin collecting data and providing responses appropriate to the driver's state.

Projects

πŸ“„ LICENSE

Dα»± Γ‘n được phΓ‘t hΓ nh theo giαΊ₯y phΓ©p GNU GPL-3.0.

🀝 Contributing

We welcome all contributions! Please create a pull request or open an issue for discussion.


The project is in its launch phase.

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