公共交通运营管理智能化创新 -公共事业管理专业

摘要

随着城市化进程的加速和居民出行需求的持续增长，公共交通系统面临运营效率低、资源分配不均及服务质量难以满足多样化需求等诸多挑战，亟需通过智能化手段提升管理水平。本研究以公共交通运营管理智能化创新为核心，旨在探索大数据、人工智能及物联网等新兴技术在公共交通领域的应用潜力，构建一套高效、精准且灵活的智能化管理框架。研究采用多源数据融合与深度学习算法，结合实际案例分析，开发了基于实时数据驱动的动态调度优化模型和乘客行为预测系统。结果表明，该智能化框架能够显著提高车辆调度效率，降低运营成本，并有效改善乘客体验。研究的主要创新点在于首次将跨模态数据分析与自适应决策机制引入公共交通管理，实现了从静态规划到动态调控的转变。这一成果为未来智慧交通系统的建设提供了重要参考，同时为全球范围内类似城市的公共交通优化提供了可复制的经验。

关键词公共交通智能化；动态调度优化；跨模态数据分析；自适应决策机制；乘客行为预测

Abstract

With the acceleration of urbanization and the continuous growth of residents' travel demands, public transportation systems are facing numerous challenges, such as low operational efficiency, uneven resource distribution, and difficulty in meeting diversified service requirements. There is an urgent need to enhance management capabilities through intelligent means. This study focuses on the innovation of intelligent operation and management of public transportation, aiming to explore the application potential of emerging technologies such as big data, artificial intelligence, and the Internet of Things in the public transportation sector. By employing multi-source data fusion and deep learning algorithms, and integrating case study analyses, this research develops a real-time data-driven dynamic scheduling optimization model and a passenger behavior prediction system. The results indicate that the proposed intelligent fr amework can significantly improve vehicle scheduling efficiency, reduce operational costs, and effectively enhance passenger experience. A major innovation of this study lies in the first-time integration of cross-modal data analysis and adaptive decision-making mechanisms into public transportation management, achieving a transformation from static planning to dynamic regulation. This achievement provides crucial references for the construction of future smart transportation systems and offers replicable experiences for public transportation optimization in similar cities worldwide.

Keywords Public Transportation Intelligence;Dynamic Scheduling Optimization;Cross-Modal Data Analysis;Adaptive Decision-Making Mechanism;Passenger Behavior Prediction

摘要 I

Abstract II

1 绪论 1

1.1 公共交通智能化创新的背景与意义 1

1.2 国内外研究现状分析 1

2 智能化技术在公共交通中的应用 2

2.1 数据驱动的运营优化技术 2

2.2 人工智能在调度管理中的作用 2

2.3 物联网技术提升服务效率 3

3 智能化运营管理的关键问题与挑战 4

3.1 数据安全与隐私保护策略 4

3.2 技术实施中的成本与效益平衡 4