Vehicle-Road Collaboration (V2X) Intelligent Roadside Unit (Intersection) Practical Training Teaching System
This equipment is a V2X roadside unit (intersection type) practical training teaching system designed for intelligent connected vehicle road collaboration technology. It is centered around RSU roadsid
Product Overview
This equipment is a V2X roadside unit (intersection type) practical training teaching system designed for intelligent connected vehicle road collaboration technology. It is centered around RSU roadside equipment and MEC edge computing units, integrating real roadside sensing and communication devices such as millimeter-wave radar, 16-line LiDAR, intelligent cameras, and traffic signal control systems to construct typical intersection vehicle-road collaboration application scenarios. The equipment can be used for teaching and training tasks such as understanding V2X communication mechanisms, roadside sensing data collection and fusion, traffic signal control and target detection linkage, fault setting and diagnosis. It is suitable for vocational colleges, technical schools, and intelligent connected vehicle training bases to conduct vehicle-road collaboration-related course teaching and practical training.
Core Advantages
Real Components and System Display
Integrates RSU roadside unit, MEC edge computing unit, intelligent camera, millimeter-wave radar, 16-line LiDAR, and traffic signal control system to construct a complete intersection V2X roadside collaboration system architecture, showcasing the basic hardware composition and connection relationships of vehicle-road collaboration.
System Structure and Installation Position Awareness
Through intersection scenario-based deployment, the installation position relationships of cameras, millimeter-wave radar, LiDAR, RSU equipment, and traffic signal lights are presented, enabling students to understand the functional distribution and system structure logic of roadside sensing devices and traffic control equipment.
Sensing Function Testing
Based on millimeter-wave radar, 16-line LiDAR, and intelligent cameras, the system verifies sensing functions such as intersection target detection, vehicle tracking, and obstacle recognition, supporting training in traffic target detection and status recognition.
Multi-Sensor Fusion
Integrates data from millimeter-wave radar, LiDAR, and visual sensing to achieve multi-source information fusion processing of intersection environmental targets, used for teaching verification of traffic target recognition and environmental situation construction.
V2X Vehicle-Road Collaboration
Based on RSU roadside units, the system enables C-V2X communication function configuration and debugging, supporting information interaction between vehicles and roads and broadcasting intersection traffic signal data, achieving understanding and verification of vehicle-road collaboration communication processes.
Fault Setting and Diagnosis
Through the intelligent fault setting system, the system simulates fault states such as communication anomalies, sensor anomalies, and signal control anomalies, conducting system fault phenomenon analysis and vehicle-road collaboration system diagnosis training.
Safety Protection and Stable Operation
RSU equipment supports IP66 protection level, millimeter-wave radar and LiDAR have IP67 protection capabilities, and the system supports remote operation and online upgrade mechanisms to ensure stable operation and safety management of roadside equipment in training environments.
Teaching Content & Training Projects
Hands-on training covering the following topics:
- Millimeter-wave radar structure cognition
- LiDAR structure cognition
- Visual sensor structure cognition
- Installation and configuration of roadside perception equipment
- Parameter configuration of intelligent cameras
- Radar target distance and speed analysis
- Image data collection and target recognition analysis
- Intersection multi-source perception data analysis
- Target Detection Function Test
- Traffic Signal Control Linkage Test
- Vehicle-Road Collaborative Communication Verification
- Multi-Sensor Fusion System Joint Debugging
Technical Specifications
| Parameter | Value |
|---|---|
| RSU C-V2X Communication | Supports 3GPP R14 PC5 Mode 4, maximum communication distance 600m, communication latency <20ms |
| RSU Frequency Band and Positioning | 5905～5925MHz, supports GNSS positioning, horizontal positioning accuracy better than 0.5m |
| RSU Protection Level | IP66, supports remote operation and online upgrades |
| MEC Computing Unit | 6 cores, 12 threads, main frequency 2.9GHz; independent image processor, 12GB DDR6 video memory; 500GB SSD storage; supports Gigabit Ethernet, WiFi, and USB3.0 |
| Intelligent Camera | Resolution 1920×1080, 50Hz frame rate, low illumination 0.01Lux, protection level IP66 |
| Millimeter-Wave Radar | Operating frequency 76GHz～77GHz, detection range 0.2m～250m, protection level IP67 |
| 16-line LiDAR | Distance measurement accuracy ±3cm, scanning frequency 5Hz/10Hz/20Hz, protection level IP67 |
| Traffic signal light | Light diameter 200mm, DC12V power supply, supports multi-mode control and remote operation |
What's Included
- ✓ RSU roadside unit
- ✓ MEC edge computing unit
- ✓ Intelligent camera
- ✓ Millimeter-wave radar
- ✓ 16-line LiDAR
- ✓ Traffic signal light control system
- ✓ Intelligent fault setting system
Product Category
Automotive teaching equipment — suitable for vocational colleges, technical schools, and automotive training institutions.
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