Product Description

The Roadside Shrub Green Belt Target is designed for autonomous driving, lane-keeping assistance, road-edge recognition and ADAS-related function testing in controlled proving-ground environments. It provides a realistic and repeatable roadside vegetation surrogate for evaluating how intelligent vehicles perceive, classify and respond to green belts, roadside shrubbery and landscaped road boundaries.

The product is developed with reference to CJJ/T 75-2023, Standard for Urban Road Greening Design, and its dimensions are further optimized based on field research of typical Chinese urban roads. It is suitable for testing lane-keeping systems, road boundary recognition, obstacle avoidance, path planning and multi-sensor perception performance in complex roadside environments.

Other roadside vegetation and road safety facility targets can be customized according to specific test scenarios.

Configuration

• Foam support structure
• Artificial shrub appearance kit

Key Features

The target adopts a realistic roadside shrub and green belt appearance, providing representative visual and geometric characteristics for intelligent vehicle testing.

It supports multiple sensing solutions, including camera, millimeter-wave radar and LiDAR, enabling comprehensive evaluation of perception algorithms under typical roadside vegetation scenarios.

The flexible foam-based structure contains no sharp or rigid damaging components, helping reduce the risk of damage to test vehicles during impact. The target is lightweight, modular and suitable for repeated closed-course testing.

The product can withstand impact speeds up to 60 km/h without damage, making it suitable for autonomous driving, lane-keeping and road-edge recognition validation.

Technical Specifications

Single-group length: 1500 ± 20 mm
Height: 850 ± 10 mm
Width: 500 ± 10 mm