Analyzing Traffic Operation Characteristics of Cold-Climate Cities Based on Multi-Source Data Fusion: A Case Study of Harbin

This study introduces an innovative approach based on multi-source data fusion to address the challenges of traffic operation management in cold-climate cities. Taking Harbin City as the research object, GPS trajectory data and checkpoint data were integrated to systematically analyze the seasonal fluctuation patterns and spatial distribution characteristics of traffic operations from the dimensions of time and space. The study shows that low temperatures and snow in winter significantly reduce traffic efficiency, with prominent traffic pressure during morning and evening peak hours. On weekdays, there is a clear “double peak” characteristic, while on non-working days, traffic flow is relatively stable. Moreover, compared to southern cities with a more pronounced “long-tail effect”, the long period of traffic congestion recovery significantly increases the resilience requirements of the traffic system in cold-climate cities. In terms of space, the concentrated commuting demand in the core circle leads to much higher traffic pressure than in the peripheral areas, creating a marked traffic gradient. Frequently congested road sections are mostly concentrated on commuting arteries and functional nodes, while peripheral areas have higher operational efficiency due to a balanced work–residence distribution. The study reveals the spatiotemporal characteristics of traffic operations in cold-climate cities, offering data support for precise management. By verifying the application value of multi-source data fusion under extreme climate conditions, this study provides important references for intelligent transportation management and sustainable development in cold-climate cities.