1-3: System Monitoring of Auto Traffic
|Principal Investigator||Robert E. Brydia, PMP|
|Final Report (DOI)||View Final Report|
|TRID||TRID – 1737419|
|Policy Brief||View Policy Brief|
No matter where they form and why, queues are impactful to traffic, causing delay and increased accident potential. The overall goal of this effort is to explore methodologies for automatically detecting the development of queues in a street network. Additional objectives would be to determine the spread of the queue, the rate of spread, and identify their impact area. By automatically determining these parameters from real-time information, the next step of predictive management (not taken in this project) could be analyzed to proactively employ real-time strategies to minimize queue formation, spread, and impact. While any real-time analytics approach faces significant challenges, new research in big-data monitoring, assessment, and analysis techniques provide the premise for finding a practical real-time solution.