Research on urban traffic congestion prediction and governance strategies based on big data
基于大数据的城市交通拥堵预测与治理策略研究

摘要

城市交通拥堵已成为现代城市发展中亟待解决的问题。随着城市化进程的加速，交通压力日益增加，大规模的交通拥堵不仅影响城市居民的日常生活，还带来了经济损失和环境污染。基于大数据的交通拥堵预测为城市管理者提供了有效的决策支持，通过实时数据的收集和分析，可以准确预测交通流量的变化趋势，及时调整交通控制策略，从而缓解拥堵现象。结合大数据分析，制定科学的治理策略有助于改善交通效率，提升城市运行质量。本文旨在探讨大数据在城市交通拥堵预测与治理中的应用，分析其实现路径，并提出具体的治理策略。

Abstract

Urban traffic congestion has become an urgent issue to be addressed in the development of modern cities. With the acceleration of urbanization, traffic pressure is increasing day by day. Large-scale traffic congestion not only affects the daily life of urban residents but also causes economic losses and environmental pollution. Big data-based traffic congestion prediction provides effective decision support for urban managers. Through the collection and analysis of real-time data, it can accurately predict the changing trends of traffic flow and timely adjust traffic control strategies, thereby alleviating congestion. Combining big data analysis to formulate scientific governance strategies helps improve traffic efficiency and enhance the quality of urban operation. This paper aims to explore the application of big data in urban traffic congestion prediction and governance, analyze its implementation paths, and propose specific governance strategies.