Autonomous Vehicle
Autonomous Vehicle
AI-driven systems enabling vehicles to perceive surroundings, make decisions, and navigate safely without human intervention for smarter mobility.
Real-Time Collision Detection System
  • Detects imminent crashes using object proximity and motion vectors.
  • Uses camera for alert generation.
  • Auto-triggers braking or steering actions in assisted driving mode.
  • Tested in simulation and real-road environments.
  • Supports ROS and autonomous stack integration.
Traffic Sign Recognition
  • Detects and classifies speed limits, stop signs, warnings in real time.
  • Trained on global sign datasets and regional variants.
  • Supports on-dash overlay or AR integration.
  • Improves driver awareness and autopilot response.
  • Used in ADAS and smart vehicle systems.
Pedestrian and Cyclist Detection
  • YOLOv8-based model for precise pedestrian and cyclist localization.
  • Handles occlusions, night, and urban clutter conditions.
  • Essential for AV navigation and safety modules.
  • Integrated with braking and navigation logic.
  • Supports real-time inference on automotive-grade GPUs.
Lane Detection and Road Edge Tracking
  • Semantic segmentation model that detects lanes and road boundaries.
  • Robust to curves, shadows, and lane fading.
  • Used in AV path planning systems.
  • Supports lane change and auto-steering decisions.
  • Fusion with GPS for enhanced localization.
Vehicle Distance and Speed Estimator
  • Monocular camera model that estimates speed and distance of vehicles.
  • Assists in adaptive cruise control and collision mitigation.
  • Combines CNN depth estimation with object tracking.
  • Optimized for embedded NVIDIA Jetson and NXP platforms.
  • Tested in Indian and US road conditions.
Signboard & Exit Detection in Highways
  • Detects exit signs and direction boards for navigation assistance.
  • Improves route alignment in fast-driving AVs.
  • Uses OCR + visual detection pipeline.
  • Useful in highway autopilot and last-mile delivery bots.
  • Tested in multiple road signage systems.
Obstacle Detection for Parking and Low-Speed AVs
  • Detects potholes, curbs, animals, and debris in slow-moving environments.
  • Used in parking, valet systems, and warehouse AVs.
  • Supports 360-degree cameras and low-cost ultrasonic sensors.
  • Real-time alerts and obstacle map generation.
  • Reduces minor accidents in constrained spaces.
Road Damage and Pothole Detection
  • Analyzes road quality using dashcam or drone footage.
  • Identifies cracks, pits, uneven surfaces for repair planning.
  • Helps in municipal audits and AV navigation safety.
  • Integrates with GIS systems.
  • Trained with global road defect datasets.
Delivery Robots
  • AI controller for autonomous last-mile robots in gated communities.
  • Follows GPS and visual SLAM for navigation.
  • Avoids pedestrians, pets, and obstacles dynamically.
  • Provides package pickup/drop automation with security verification.
  • Tested in smart campuses and residential areas.
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