3D MLFF LiDAR

360° Scanning with 4-Lane Coverage and 300m Range

OVERVIEW

Agnibaan Utra

Rocket’s Agnibaan Ultra is a next-generation 3D LiDAR sensor engineered for smart cities, high-speed roads, and advanced transportation systems. With its revolutionary 360° horizontal scanning and 300m range, a single Agnibaan Ultra unit monitors up to 4 lanes simultaneously, accurately detecting vehicle height even when vehicles run in parallel.

Combining advanced Time-of-Flight technology, precise optics, and robust multi-echo capabilities, it delivers reliable performance in all conditions—rain, fog, snow, or shine. The sensor provides ready-to-deploy intelligence with an inbuilt classification engine, eliminating coding hassles for system integrators while working in tandem with 4 cameras to deliver precise axle counting for revenue-accurate tolling operations.

Product Highlights

360° Coverage

Single LiDAR unit covers 4 complete lanes with 360° horizontal and 40.5° vertical field of view focused downward. Eliminates need for multiple sensors while delivering comprehensive coverage for wide expressway configurations with reduced infrastructure costs.

300m Extended Range

Superior ranging capability covers 300m detection distance at 10% reflective surface with ±3cm accuracy. Enables early vehicle detection for high-speed MLFF scenarios ensuring accurate classification in a wide speed range from 10 km/h to 220 km/h.

Camera-Integrated System

Works in tandem with 4 cameras (one per lane) to deliver ≥99% axle count accuracy for revenue protection. Integrated approach combines LiDAR dimensional data with camera-based axle detection for foolproof toll classification across all vehicle types.

Extreme Weather Reliability

IP68 rating with -40°C to +80°C operating range ensures year-round operation in harshest conditions. Compact Φ162mm × 126.2mm design with 2.6kg weight enables flexible gantry mounting while maintaining industrial-grade durability standards.

Key Specifications

Parameter Specification
Scanning principle TOF (Time of Flight)
Horizontal field of view 360°
Vertical field of view 40.5° (-1.5° to -42°)
Horizontal angle resolution 0.1° / 0.2° / 0.4°
Vertical angle resolution 0.1° to 4°
Ranging capability 200-300 meters
Ranging accuracy ±3 cm (typical)
Scan frequency 05 / 10 / 25 Hz
Return model Single / Dual Return
Laser wavelength 905 nm (Class 1)
Operating voltage 24±4V DC
Power consumption 20W (50 W heating)
Communication interface Ethernet UDP/IP
Time synchronization GPS/NTP/PTP
GPS sync accuracy ≤10 ms
Dimensions Φ162 × 126.2 mm
Weight 2.6 kg

Operating Conditions

Parameter Specification
Operating Temperature -40°C to +80°C
Storage Temperature -50°C to +85°C
Humidity / Sealing IP68 fully sealed
Eye Safety Class 1 (Safe for continuous operation)

Applications and Deployment

Purpose-built for multi-lane free flow tolling and advanced traffic management systems.

Multi-Lane Free Flow AVC Classification

Delivers revenue-accurate automatic vehicle classification across 4 lanes with single LiDAR unit working with 4 cameras. Achieves ≥99% vehicle type accuracy and ≥99% axle count accuracy enabling confident toll collection in free-flow scenarios without revenue leakage.

Smart City & Urban Traffic Analytics

Provides comprehensive 360° traffic monitoring for urban intersections, tunnels, and smart city corridors with complete coverage. Real-time vehicle count, speed, headway, and occupancy data streams to city management centers for congestion analysis and adaptive signal control.

High-Speed Expressway Monitoring

Monitors traffic in a wide speed range from 10 km/h to 220 km/h with precise vehicle dimension detection and classification accuracy. Detects oversized vehicles, monitors compliance in restricted zones, and integrates seamlessly with ANPR systems for automated enforcement operations.

Why Choose Agnibaan Ultra?

Proven multi-lane performance backed by extensive field deployment experience.

4-Lane Coverage with Single Unit

Revolutionary 360° scanning eliminates need for 4 separate sensors saving infrastructure costs and complexity. Single Agnibaan Ultra with 4 cameras delivers complete MLFF solution reducing installation time, maintenance overhead, and total cost of ownership.

Proven On-Site Expertise

Backed by multiple LiDAR deployments across traffic-flow surveys, vehicle sizing, and classification applications. RST's team brings extensive algorithm development experience using LiDAR point-cloud data specifically optimized for Indian highway traffic conditions and vehicle mix.

Superior 300m Range Capability

Industry-leading detection range at 200m for 10% reflective surfaces enables early vehicle detection for MLFF scenarios. Extended range provides advance warning for oversized vehicles and supports wide gantry spans on modern expressway infrastructure.

Camera-Integrated Intelligence

Integrated system approach combines 3D LiDAR dimensional data with camera-based axle detection for foolproof classification. Achieves ≥99% axle accuracy when deployed with 1 camera per lane ensuring revenue protection and regulatory compliance.

Extreme Temperature Performance

Operates reliably from -40°C to +80°C covering full spectrum of Indian climatic conditions from Himalayan winters to Rajasthan summers. IP68 sealing ensures continuous operation during monsoons, dust storms, and extreme weather without performance degradation.

Advanced Multi-Echo Processing

Supports single and dual return modes for superior object detection in heavy rain, fog, and complex traffic scenarios. Multi-echo capability ensures reliable performance when vehicles run in parallel or during dense traffic conditions with minimal headway.

Compact Industrial Design

Φ162mm × 126.2mm compact form factor with 2.6kg weight enables flexible mounting on existing gantry infrastructure. Integrated design with minimal external components reduces failure points and simplifies field maintenance operations.

Deploy 4-Lane MLFF Intelligence with Single LiDAR

Experience ≥99% axle accuracy with 360° coverage for your next multi-lane free flow tolling project.