Traffic Flow Analysis and Parking Demand Estimation in Tourist Areas Using Moving Average and Location Backtracking Methods

With the rapid development of tourism, traffic congestion and parking demand issues in scenic areas have become increasingly prominent, particularly at the intersection of Jingzhong Road and Weizhong Road in a renowned scenic town. Significant peak-period differences exist: the morning peak (7:00-9:00) witnesses 385,495 vehicles in the north-to-east direction, while the evening peak (17:00-19:00) records 122,671 vehicles in the south-to-north direction, with peak traffic accounting for 35% of daily volume. This study uses methods like moving averages, time discretization, and location backtracking to analyze data, identifying distinct peak periods and directional flow variations while quantifying 283,885 cruising vehicles (via a 300-second time threshold) to estimate a demand for 340,662 temporary parking spaces during the May Day Golden Week. The findings enable scientific optimization of traffic signal configurations—such as allocating 40% more green light time to peak directions—and rational parking resource allocation, providing a data-driven framework to alleviate congestion, enhance traffic management efficiency, and improve travel experiences in scenic areas and urban destinations.