Workstation-grade embedded computing platform , accelerate Cooperative Vehicle Infrastructure System(CVIS)

Workstation-grade embedded computing platform , accelerate Cooperative Vehicle Infrastructure System(CVIS)

Vehicle Infrastructure Integration (VII) , the trend of the intelligent transportation system, aims to effectively compensate for the blind spots in perception, fully realize the effective coordination and interaction between people , vehicles, and roads. Therefore, to ensure traffic safety, improve traffic efficiency, and promote the intelligentization and networking of the intelligent transportation industry.

  1. Application cases

A leading domestic enterprise focusing on Internet of Vehicles and smart city services, chose JHC high-performance mobile edge computing platform BRAV-7302, equipped with MXM3.1 GTX-1060M graphics card, fully empowering people, vehicles, and urban infrastructure to help the implementation of vehicle-road collaborative solutions  and improve traffic efficiency.

  1. System Principle

A data collection system consisting of a dome camera, a detection radar, etc, collects road vehicle information in real time. This information includes the vehicle's position, speed, distance, road traffic lights, and pedestrian information. BRAV-7302 uses the dedicated algorithm to analyze and process these data, and then transmit effective data to the cloud platform and also feed these data back to the RSU device. After the RSU device transmits the received information to the on-board unit OBU, it can judge complex road conditions and provide a strong support for the driver or the automatic driving system. 

 BRAV-7302 Operation Topology

Automated driving systems can obtain more information about road dynamics (including vehicles and pedestrians) through vehicle-road collaboration systems, greatly reducing the computational burden of data fusion and path planning for autonomous vehicles, enabling efficient transmission and autonomous driving.

The function  of BRAV-7302 (mobile edge computing device): data storage + calculation analysis + data upload and feedback after analysis.

3.Product Introdution

1.CPU+GPU dual processor

2.Multi-network port, multi-display, wireless communication, shock absorption design, suitable for on-site flexible application in AIOT field

Key features

CPU and GPU fan cooling, independent air passage

Intel Kabylake-S/Skylake-S Core I3/I5/I7 CPU

2*DDR4 2400/2133MHz SODIMM, Up to 32GB

1*MXM 3.1 socket, support NVIDIA/AMD GPU

Intel 1*DP+1*HDMI+1*VGA, GPU 3*DP+1*HDMI

3/7*LAN, 6*USB3.0, 3*USB2.0, 4*COM,16DIO,Audio

1*Mini PCIe(PCIe+USB),1*M.2 2242 B-Key

1*mSATA, 1/2*2.5" SATA, suppprt Raid0,1

Support Intel iVpro and TPM2.0

DC 6~48V Wide Power Input