Edge Computing and Sensor Fusion System for Comprehensive Monitoring of Traffic and Road Conditions

Real-time monitoring of traffic conditions is crucial for improving traffic safety and efficiency, and there is an urgent need for the development of in situ traffic sensing & computing technologies leveraging the recent advancements in edge computing. This project will develop an edge computing and sensor fusion system for comprehensive traffic and road conditions data collection and efficient transmission of critical information to decision makers to improve transportation safety and efficiency. The objectives of the project are to (1) develop an edge computing sensor fusion device that integrates multiple sensors to collect and process real-time data on traffic and road conditions; (2) develop AI/ML algorithms to analyze and fuse data from multiple sensors to collect motorized data (i.e., volume, speed, and classification), non-motorized data (e.g., pedestrian, cyclists, scooters, people in wheelchairs), road surface conditions (i.e., dry, wet, snow, ice), visibility and weather & environmental conditions (e.g., temperature, humidity, fog, smoke, air quality, emission); (3) conduct field tests and evaluate the accuracy, latency, and reliability of the developed system; and (4) develop a communication module that enables the device to transmit the collected data/analyzed results to transportation agencies, TMCs, and road users.