Autonomous Driving Systems

From ADAS to Full Autonomy—One Platform, Many Possibilities

Engineering the Brain Behind Driverless Mobility

At Tech4LYF, we develop and integrate core components of Autonomous Driving Systems (ADS)—including computer vision, sensor fusion, path planning, and vehicle control algorithms. Whether you’re building an ADAS-enabled car or a fully autonomous EV prototype, our systems connect LiDAR, radar, cameras, GPS, and AI models to create safe, reliable, and real-time decision-making capabilities on the road.

12+ types

Sensor Modules Integrated

Including LiDAR, radar, GPS, cameras, IMUs

25+

ML Models Deployed

For object detection, lane keeping, obstacle avoidance

30+

Autonomous Prototypes Powered

Across 2W, 4W, and delivery bots

< 50ms

Real-Time Inference Speed

Achieved with onboard AI edge computing

Modular, Scalable, Safety-First Driving Intelligence

Core Capabilities of Our Autonomous Stack

Perception & Object Detection

Use AI/ML to detect vehicles, pedestrians, lanes, signs, and obstacles with 360° awareness.

Sensor Fusion & SLAM

Merge data from multiple sensors (LiDAR, radar, IMU, GPS) to create accurate environmental maps.

Path Planning & Motion Control

Generate safe and optimized driving paths with dynamic re-routing and obstacle avoidance.

Real-Time Decision Engine

Make millisecond-level decisions based on road context, rules, and predictive modeling.

ADAS Modules

Implement adaptive cruise control, lane keeping, auto braking, and driver alerts.

Simulation & Testing Tools

Train and validate models in real-world-like conditions before field deployment.

“Tech4LYF’s engineering team helped us build a robust ADAS prototype with LiDAR, real-time obstacle detection, and edge inference—all integrated into our electric scooter pilot.”

— Abhay Kulkarni,

CTO, GlideMotion Mobility Pvt. Ltd.

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