3D traffic situation analysis

Combines road history information (TAAS) and current speed information of vehicle (radar), identifies road surface conditions (icy, wet roads) using , IoT sensor (air temperature, humidity, road surface temperature) information, controls LED brightness using illuminance sensors (preventing light pollution).

Prevents traffic accidents in advance by delivering information on upcoming roads (icy roads), and when configuring a multi-system, road section information is transmitted to induce the driver to decelerate or avoid a particular road section.

Context-aware computing-based traffic accident warning system

Based on various IoT sensor information and TAAS information, displays real-time risk analysis and warning messages at the embedded level. Classifies situations into caution, warning, and risk categories, and predicts the possibility of an accident occurring.

Sensing of risk, User Experience(UX)

A danger warning/alert is displayed on a large LED panel. The message is expressed using letters, numbers, pictograms, and animations so that the driver can sense risk at a more intuitive level.

oneM2M

Transfers, synchronizes, and controls data acquired and analyzed from the system to other smart devices developed based on oneM2M.

Transfers, synchronizes, and controls data acquired and analyzed from the system to other smart devices developed based on oneM2M

Transmits data acquired and analyzed from the system to other smart devices used by local governments and road control officers. Analyzes the cause of accidents through Bigdata analysis and compatible with the Ministry of Land, Infrastructure and Transport’s smart city integrated platform.

Autonomous driving support V2I

Supports safe driving by delivering information on a section of road acquired through the second-phase development to be carried out in the future to autonomous vehicles (e.g. Selecting detours, slow-moving traffic, etc.)