From Empirical Judgment to Data-Driven Approaches: A Survey of Traffic Reorganization and Management During Urban River-Crossing Corridor Construction

Urban river-crossing corridors serve as critical bottlenecks within urban transportation networks, where traffic management during construction periods directly influences urban operational efficiency and socioeconomic activities. Traditional management approaches based on empirical judgment exhibit fundamental limitations when confronting large-scale infrastructure construction projects, including low prediction accuracy, delayed response times, and insufficient systematic coordination. This survey aims to synthesize existing data-driven approaches, identify research gaps, and establish a roadmap for intelligent traffic management advancement. Unlike previous surveys focusing on individual technologies, this review constructs a complete technical chain from data sensing to intelligent decision-making and systematically reveals implementation pathways for paradigm transformation. The research establishes technical architecture encompassing data sensing, intelligent analysis, predictive warning, and decision support systems, while elucidating the application mechanisms of cutting-edge technologies such as multi-source data fusion, artificial intelligence, and digital twins in urban traffic management. Through analysis of six representative engineering case studies from China, the United States, Republic of Korea, Russia, and Europe, including bridge construction, emergency repair, and highway reconstruction projects, the investigation reveals that data-driven approaches not only achieve improvements in technical performance but also facilitate fundamental paradigm shifts in traffic management philosophy from passive response to proactive prevention, and from localized optimization to systematic coordination. The findings enable policymakers to develop standardized frameworks for data-driven traffic systems, assist urban planners in selecting appropriate technologies based on project characteristics, and guide engineers in implementing integrated traffic management solutions during critical infrastructure construction.