The Traffic Monitoring Decision Support Tool: A Web-Based Decision Support Tool for Enhanced Traffic Data Collection, Analysis, and Estimation
DOI:
https://doi.org/10.70112/tarce-2024.13.1.4230Keywords:
Traffic Monitoring, Knowledge-Based Systems, Traffic Data Collection, Traffic Pattern Groups, Decision Support ToolAbstract
Accurate collection and analysis of traffic data are essential for effective transportation planning and management. The Traffic Monitoring Decision Support Tool (TMDEST) is an innovative web-based expert system designed to enhance the capabilities of transportation professionals in traffic data collection, analysis, and reporting. TMDEST integrates federal guidelines, established research methods, and state-specific information into a comprehensive knowledge base. The system comprises multiple core modules, including the MADT/AADT Methods Module, the TPG Methods Module, and the Adjustment Factors Module. Each module addresses distinct aspects of traffic monitoring, providing intuitive interfaces for user data input and generating tailored recommendations. The MADT/AADT Methods Module improves the estimation of Monthly Average Daily Traffic (MADT) and Annual Average Daily Traffic (AADT) through three methods: Simple Average, AASHTO, and HPSJB, each evaluated based on complexity and data completeness. The TPG Methods Module uses clustering techniques to form Traffic Pattern Groups (TPGs), enhancing the accuracy of short-duration count data. The Adjustment Factors Module helps determine the necessary adjustment factors for precise AADT and MADT estimations. TMDEST’s validation, verification, and evaluation processes ensure reliability by checking for completeness, consistency, and correctness. Its web-based design facilitates easy access and updates, making it an invaluable tool for transportation agencies. Future enhancements include an online feedback system to continuously improve TMDEST’s functionality and user experience.
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