Automated Roadway Conflicts Identification System


Pixel to pixel manner automated safety diagnostics and conflict identification system

About The System

High-Resolution Analysis

High Robustness

High Accuracy

Pixel Level Video Stabilization

Car Pose Estimation

Lost and Missing Vehicles Re-matching

Semantic Segmentation

Fusion of Deep Learning and Traditional Method

System Overview

This system, applicable in particular to road traffic analysis, uses drone/Unmanned Aerial Vehicle (UAV) videos. Video data from drones/UAVs are stabilized first, and then be processed through the automatic detection and tracking system based on state-of-the-art algorithms. This system also further corrects vehicles’ tracking areas based on vehicles’ moving conditions and detection results to provide more accurate outputs, especially for turning vehicles. Based on the detection and tracking results, the systems can generate the following types of outputs using drone/UAV video data:

  • Trajectory data of road users including vehicles and vulnerable road users
  • Road users’ classifications
  • Traffic statistics (e.g., volume, speed)
  • Safety indicators (e.g., Post-Encroachment Time (PET))

The system can be applied for drone videos that are collected from different types of roadways, including freeway, arterial, and intersection.

ARCIS diagram

System Demo

Hours Testing
Sample Size
University Partners

Our Performance

Accuracy: 95+%
Expected Average Overlap (EAO): 95+%
Robustness: 85+%

OUR Example