Further Refinement and Integrated Platform for INDOT Traffic Management and Safety Toolset

Details

• Creators:
  Chien, Stanley ; Hu, Shu ; Chen, Yaobin ; Qiu, Mei ; Reindl, William Lorenz ; Meng, Noah ; Koshy, Liya ; Kuma, Sajan
• Corporate Creators:
  Purdue University. Joint Transportation Research Program
• Corporate Contributors:
  Indiana Department of Transportation ; United States. Department of Transportation. Federal Highway Administration
• Subject/TRT Terms:
  Analysis Closed Circuit Television Cloud Computing Detectors Digital Displays Highway Traffic Control Lane-wise Traffic Analysis Multi-model Anomaly Detection Road-dependent Anomaly Detection Road-independent Anomaly Detection Traffic Control Traffic Flow Traffic Lanes Weaving Analysis Web Applications

  More +
• Publication/ Report Number:
  FHWA/IN/JTRP-2025/36
• DOI:
  https://doi.org/10.5703/1288284318603
• Resource Type:
  Tech Report
• Geographical Coverage:
  United States ; Indiana
• Edition:
  Final Report
• Corporate Publisher:
  Purdue University. Joint Transportation Research Program
• Abstract:
  The project aims to further refine the previously developed Anomaly Detection and Weaving Analysis programs and create a unified, Web-based user interface for users to access TASI-developed software tools conveniently. 1. The INDOT Application Suite has been successfully developed for centralizing the digital platform developed by Purdue University’s Transportation and Autonomous Systems Institute (TASI). It offers a secure, single point of access to a range of specialized applications, consolidating multiple tools into a unified system. 2. A scalable, lane-wise highway traffic anomaly detection framework that operates exclusively on video-based data was designed. By leveraging AI-driven vision techniques, the anomaly detection system extracts interpretable lane-specific traffic features, including vehicle count, occupancy, and truck percentage. We introduced a novel dataset derived from real-world highway surveillance, capturing fine-grained traffic dynamics across multiple time periods and anomaly types. 3. The Highway Weaving Analysis Program has been successfully developed. Due to the technical challenges of vehicle re-identification from CCTV footage, the automated matching process can produce false positives. To address this, the system incorporates a human-in-the-loop verification step in the Web-Based Vehicle Matching Verification and Result Generation GUI. Based on this verified data, the system calculates the final lane-to-lane weaving percentages. The results are presented in a comprehensive, user-friendly report that includes Sankey diagrams visualizing the traffic flow for all vehicles, as well as for cars and trucks separately. The entire system operates on a cloud maintained by Purdue University.
• Format:
  PDF
• Funding:
  SPR-4930
• Collection(s):
  US Transportation Collection
• Main Document Checksum:
  urn:sha-512:f5559eb9e01392f0c0f4619c7388e976dd0d65829d74b50a305a1298f1ab6fd881f8f7d31b932a7fbc48939f368b291dc4aafd07b276b82c6ff11a071993f93f
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/91224/dot_91224_DS1.pdf
• File Type:
  [PDF - 11.76 MB ]