updated website

Author: Julian1777

README copy.md

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+<p align="center">
+  <img src="media/bannernobg.png" alt="VisionPilot Banner" height="200" />
+</p>
+
+# VisionPilot: Autonomous Driving Simulation, Computer Vision & Real-Time Perception (BeamNG.tech)
+
+<p align="center" style="margin-bottom:0;">
+  <a href="https://star-history.com/#visionpilot-project/VisionPilot&Date">
+    <img src="https://api.star-history.com/svg?repos=visionpilot-project/VisionPilot&type=Date" alt="Star History Chart" height="300" />
+  </a>
+</p>
+
+## Table of Contents
+
+- [VisionPilot: Autonomous Driving Simulation, Computer Vision \& Real-Time Perception (BeamNG.tech)](#visionpilot-autonomous-driving-simulation-computer-vision--real-time-perception-beamngtech)
+  - [Table of Contents](#table-of-contents)
+  - [Overview](#overview)
+  - [Demos](#demos)
+    - [Emergency Braking (AEB) Demo](#emergency-braking-aeb-demo)
+    - [Sign Detection \& Detection and classification](#sign-detection--detection-and-classification)
+    - [Traffic Light Detection \& Classification Demo](#traffic-light-detection--classification-demo)
+    - [Latest Lane Detection Demo (v2)](#latest-lane-detection-demo-v2)
+      - [Previous Lane Detection Demo (v1)](#previous-lane-detection-demo-v1)
+    - [Foxglove Visualization Demo](#foxglove-visualization-demo)
+    - [Segmentation Demo](#segmentation-demo)
+  - [Sensor Suite](#sensor-suite)
+  - [Roadmap](#roadmap)
+    - [Perception](#perception)
+    - [Sensor Fusion \& Calibration](#sensor-fusion--calibration)
+    - [Control \& Planning](#control--planning)
+    - [Simulation \& Scenarios](#simulation--scenarios)
+    - [Visualization \& Logging](#visualization--logging)
+    - [Deployment \& Infrastructure](#deployment--infrastructure)
+    - [README To-Dos](#readme-to-dos)
+    - [Other](#other)
+  - [Note on Installation](#note-on-installation)
+  - [Known Limitations](#known-limitations)
+    - [Simulator-Specific Limitations](#simulator-specific-limitations)
+  - [Credits](#credits)
+  - [Citation](#citation)
+    - [BeamNG.tech Citation](#beamngtech-citation)
+  - [License](#license)
+
+## Overview
+
+A modular Python project for autonomous driving research and prototyping, fully integrated with the BeamNG.tech simulator and Foxglove visualization. This system combines traditional computer vision and state-of-the-art deep learning (CNN, U-Net, YOLO, SCNN) with real-time sensor fusion and autonomous vehicle control to tackle:
+
+- Lane detection (Traditional CV & SCNN)
+- Traffic sign classification & detection (CNN, YOLO)
+- Traffic light detection & classification (YOLO)
+- Vehicle & pedestrian detection and recognition (YOLO)
+- Multi-sensor fusion (Camera, LiDAR, Radar, GPS, IMU)
+- Multi-model inference, real-time simulation, autonomous driving with PID control (BeamNG.tech)
+- Containerized multi-model architecture (Docker-based), orchestrated via a central inference aggregator service
+- Cruise control
+- Automatic Emergency Breaking AEB
+- Real-time visualization and monitoring (Foxglove WebSocket)
+- Modular configuration system (YAML-based)
+- Drive logging and telemetry
+
+## Demos
+
+### Emergency Braking (AEB) Demo
+
+Watch the Emergency Braking System (AEB) in action with real-time radar filtering and collision avoidance:
+
+<img src="media/demo_gifs/aeb_gif.gif" alt="AEB Demo" width="600" height="337" />
+
+**Extended Demo:** [Watch the full video here](https://www.youtube.com/watch?v=Z8Y2-MpmrRg)
+
+---
+
+### Sign Detection & Detection and classification
+
+This demo shows real-time traffic sign detection and classification:
+
+<img src="media/demo_gifs/sign_demo.gif" alt="Sign Detection Demo & Vehicle Pedestrian" width="600" height="337" />
+
+**Extended Demo:** [Watch the full video here](https://youtu.be/ujGkQJ2BqV0)
+
+> VisionPilot does not yet support multi-camera. This is for demonstration purposes only.
+
+---
+
+### Traffic Light Detection & Classification Demo
+
+This demo shows real-time traffic light detection and classification:
+
+<img src="media/demo_gifs/traffic_light_demo.gif" alt="Traffic Light Detection & Classification Demo" width="600" height="337" />
+
+> No extended Demo avaliable yet.
+
+---
+
+### Latest Lane Detection Demo (v2)
+
+Watch the improved autonomous lane keeping demo (v2) in BeamNG.tech, featuring smoother fused CV+SCNN lane detection, stable PID steering, and robust cruise control:
+
+<img src="media/demo_gifs/lane.gif" alt="Lane Detection Demo" width="600" height="337" />
+
+**Extended Demo:** [Watch the full video here](https://www.youtube.com/watch?v=7eA_XfIkLWQ)
+
+> Note: Very low-light (tunnel) scenarios are not yet supported.
+
+### Previous Lane Detection Demo (v1)
+
+The original demo is still available for reference:
+
+[Lane Keeping & Multi-Model Detection Demo (v1)](https://youtu.be/f9mHigMKME8)
+
+---
+
+### Foxglove Visualization Demo
+
+See real-time LiDAR point cloud streaming and autonomous vehicle telemetry in Foxglove Studio:
+
+<img src="media/demo_gifs/foxglove.gif" alt="Foxglove Visualization Demo" width="600" height="337" />
+
+**Extended Demo:** [Watch the full video here](https://www.youtube.com/watch?v=4HJDvL2Q6AY)
+
+---
+
+### Segmentation Demo
+
+See real-time image segmentation using front and rear cameras:
+
+<img src="media/demo_gifs/segmentation.gif" alt="Segmentation Demo" width="600" height="337" />
+
+**Extended Demo:** [Watch the full video here](https://youtu.be/4PAqcUKqn6c?si=UHw-mw7iLZKGXvav)
+
+> More demo videos and visualizations will be added as features are completed.
+
+## Sensor Suite
+
+The vehicle is equipped with a comprehensive multi-sensor suite for autonomous perception and control:
+
+| Sensor                      | Specification                                        | Purpose                                                         |
+| --------------------------- | ---------------------------------------------------- | --------------------------------------------------------------- |
+| **Front Camera**            | 1920x1080 @ 50Hz, 70° FOV, Depth enabled             | Lane detection, traffic signs, traffic lights, object detection |
+| **LiDAR (Top)**             | 80 vertical lines, 360° horizontal, 120m range, 20Hz | Obstacle detection, 3D scene understanding                      |
+| **Front Radar**             | 200m range, 128×64 bins, 50Hz                        | Collision avoidance, adaptive cruise control                    |
+| **Rear Left & Right Radar** | 30m range, 64×32 bins, 50Hz                          | Blindspot monitoring, rear object detection                     |
+| **Dual GPS**                | Front & rear positioning @ 50Hz                      | Localization                                                    |
+| **IMU**                     | 100Hz update rate                                    | Vehicle dynamics, pose estimation                               |
+
+<table>
+  <tr>
+    <td align="center"><img src="media/beamng_images/sensors.png" alt="Sensor Array 1" width="280"/></td>
+    <td align="center"><img src="media/beamng_images/radar_front.png" alt="Sensor Array 2" width="280"/></td>
+    <td align="center"><img src="media/beamng_images/lidar.png" alt="Sensor Array 3" width="280"/></td>
+  </tr>
+  <tr>
+    <td align="center"><em>Sensor Array</em></td>
+    <td align="center"><em>Front Radar</em></td>
+    <td align="center"><em>Lidar Visualization</em></td>
+  </tr>
+</table>
+
+> Configuration files are located in the `/config` directory:
+
+## Roadmap
+
+### Perception
+
+- [x] Sign classification & Detection (CNN / YOLOv11m)
+- [x] Traffic light classification & Detection (CNN / YOLOv11m)
+- [x] Lane detection Fusion (SCNN / CV)
+- [x] Advanced lane detection using OpenCV (robust highway, lighting, outlier handling)
+- [x] Integrate Majority Voting system for CV
+- [x] ⭐ Semantic Segmentatation (Already built not implemented here yet)
+- [x] ⭐ Real-Time Object Detection (Cars, Trucks, Buses, Pedestrians, Cyclists) (Trained)
+- [ ] 🔥 Speed Estimation using detection from camera and lidar
+  - [ ] Potentially use Multiple Object Tracking (MOT) for better speed estimation
+- [ ] Pedestrian intent prediction (crossing, standing, walking along road)
+- **Note:** Would Have to be tested in Carla as BeamNG.tech does not have pedestrians implemented
+- [ ] Vehicle State Classification (Break Lights, Turn Signals, Reverse Lights)
+- [ ] 🔥 Handle dashed lines better in lane detection
+- [ ] 🔥 Lidar Object Detection 3D
+- [ ] Detect multiple lanes
+- [ ] 💤 Multi Camera Setup (Will implement after all other camera-based features are finished)
+- [ ] 💤 Overtaking, Merging (Will be part of Path Planning)
+
+### Sensor Fusion & Calibration
+
+- [ ] 🔥 Kalman Filtering
+- [x] Integrate Radar
+- [x] Integrate Lidar
+- [ ] Integrate GPS
+- [ ] Integrate IMU
+- [ ] Ultrasonic Sensor Integration
+- **Note:** Can easily be implemented with prebuilt Beamng ADAS module
+- [ ] Map Matching algorithm
+- [ ] 💤 SLAM (simultaneous localization and mapping)
+  - [ ] Build HD Map from Scratch
+  - [ ] Localize Vehicle on HD Map
+- [ ] Sensor Health Monitoring & Redundancy
+  - [ ] Redundant Front Radar for AEB
+  - [ ] Sensor status diagnostics and failover
+
+### Control & Planning
+
+- [x] Integrate vehicle control (Throttle, Steering, Braking Implemented) (PID needs further tuning)
+- [x] Integrate PIDF controller
+- [x] ⭐ Adaptive Cruise Control (Currently only basic Cruise Control implemented)
+- [x] ⭐ Automatic Emergency Braking AEB
+  - [ ] Support using Camera and Lidar detections
+- [ ] Trajectory Predcition for surrounding vehicles
+- [ ] Blindspot Monitoring (Using left/right rear short range radars)
+- [ ] Traffic Rule Enforcement (Stop at red lights, stop signs, yield signs)
+- [ ] Dynamic Target Speed based on Speed Limit Signs
+- [ ] Global Path planning
+- [ ] Local Path planning
+- [ ] Lane Change Logic
+- [ ] Parking Logic (Path finding / Parallel or Perpendicular)
+- [ ] 💤 End-to-end driving policy learning (RL, imitation learning)
+- [ ] 💤💤 Advanced traffic participant prediction (trajectory, intent)
+
+### Simulation & Scenarios
+
+- [x] Integrate and test in BeamNG.tech simulation (replacing CARLA)
+- [x] Modularize and clean up BeamNG.tech pipeline
+- [x] Tweak lane detection parameters and thresholds
+- [ ] Fog Weather conditions (Rain or snow not supported in BeamNG.tech)
+- [ ] Traffic scenarios: driving in heavy, moderate, and light traffic
+- [ ] Test all Systems in different lighting conditions (Day, Night, Dawn/Dusk, Tunnel)
+- [ ] 💤💤 Test using actual RC car
+
+### Visualization & Logging
+
+- [x] ⭐ Full Foxglove visualization integration (Overhaul needed)
+- [x] Modular YAML configuration system
+- [x] Real-time drive logging and telemetry
+- [ ] Real time Annotations Overlay in Foxglove
+- [ ] Show predicted trajectories in Foxglove
+- [ ] Show Global and local path plans in Foxglove
+- [ ] Live Map Visualization
+
+### Deployment & Infrastructure
+
+- [ ] Containerize Models for easy deployment and scalability (Also eliminates dependency issues)
+  - [ ] Message Broker (redis/rabbitmq)
+  - [ ] Create docker compose
+  - [ ] Aggregator service
+  - [ ] Refactor beamng.py
+
+### README To-Dos
+
+- [x] Add demo images and videos to README
+- [ ] Add performance benchmarks section
+- [x] Add Table of Contents for easier navigation
+
+### Other
+
+- [x] Vibe-Code a website for the project
+- [x] Redo project structure for better modularity
+
+> Driver Monitoring System would've been pretty cool but human drivers are not implemented in BeamNG.tech
+
+## Legend
+
+> 🔥 = High Priority
+
+> ⭐ = Complete but still being improved/tuned/changed (not final version)
+
+> 💤 = Minimal Priority, can be addressed later
+
+> 💤💤 = Very Low Priority, may not be implement
+
+## Note on Installation
+
+> **Status:** This project is currently in **active development**. A stable, production-ready release with pre-trained models and complete documentation will be available eventually.
+
+## Known Limitations
+
+- **Tunnel/Low-Light Scenarios:** Camera depth perception fails below certain lighting thresholds
+- **Multi-Camera Support:** Single front-facing camera only (future roadmap)
+- **Dashed Lane Detection:** Requires improvement for better accuracy
+- **PID Controller Tuning:** May oscillate on aggressive maneuvers
+- **Real-World Testing:** Only validated in simulation (BeamNG.tech), for now...
+
+### Simulator-Specific Limitations
+
+- Rain/snow physics not supported in BeamNG.tech
+- No native ROS2 support (custom bridge required)
+- Pedestrians
+- Human Drivers
+
+## Credits
+
+**Datasets:**
+
+- CU Lane, LISA, GTSRB, Mapillary, BDD100K
+
+**Simulation & Tools:**
+
+- BeamNG.tech by [BeamNG GmbH](https://www.beamng.tech/)
+- Foxglove Studio for visualization
+
+**Special Thanks:**
+
+- Kaggle for free GPU resources (model training)
+- Mr. Pratt (teacher/supervisor) for guidance
+
+## Citation
+
+If you use VisionPilot in your research, please cite:
+
+```bibtex
+@software{visionpilot2025,
+  title={VisionPilot: Autonomous Driving Simulation, Computer Vision & Real-Time Perception},
+  author={Julian Stamm},
+  year={2025},
+  url={https://github.com/visionpilot-project/VisionPilot}
+}
+```
+
+### BeamNG.tech Citation
+
+> **Title:** BeamNG.tech  
+> **Author:** BeamNG GmbH  
+> **Address:** Bremen, Germany  
+> **Year:** 2025  
+> **Version:** 0.35.0.0  
+> **URL:** https://www.beamng.tech/
+
+## License
+
+This project is licensed under the MIT License - see [LICENSE](LICENSE) file for details.

components/Navbar.tsx

@@ -18,6 +18,7 @@ const Navbar: React.FC = () => {
   }, []);
 
   const navLinks = [
+    { name: 'Home', path: '/' },
     { name: 'Technical', path: '/technical' },
     { name: 'Demos', path: '/demos' },
     { name: 'Models', path: '/models' },

index.html

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     <meta charset="UTF-8" />
     <link rel="icon" type="image/svg+xml" href="/vite.svg" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-    <title>VisionPilot | Autonomous Driving Simulation</title>
+    <meta name="description" content="VisionPilot: A modular Python project for autonomous driving research, integrating BeamNG.tech soft-body physics with state-of-the-art computer vision (YOLO, SCNN), sensor fusion, and real-time control." />
+    <meta name="keywords" content="Autonomous Driving, BeamNG.tech, Computer Vision, YOLO, SCNN, Sensor Fusion, Robotics, Simulation, Python, Deep Learning, VisionPilot" />
+    <meta name="author" content="Julian Stamm" />
+    <meta property="og:title" content="VisionPilot | Autonomous Driving Simulation & Perception" />
+    <meta property="og:description" content="VisionPilot: A modular Python project for autonomous driving research, integrating BeamNG.tech soft-body physics with state-of-the-art computer vision (YOLO, SCNN), sensor fusion, and real-time control." />
+    <meta property="og:type" content="website" />
+    <title>VisionPilot | Autonomous Driving Simulation & Perception</title>
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