摘要
随着城市化进程的加速，交通拥堵、环境污染和资源浪费等问题日益突出，优化城市公共交通规划与管理成为解决上述问题的关键途径。本研究旨在通过系统分析城市公共交通现状及存在的问题，提出科学有效的优化策略，以提升公共交通系统的运行效率和服务水平。研究采用多源数据分析、仿真建模和实地调研相结合的方法，从网络布局优化、运营调度改进以及政策支持体系构建三个维度展开深入探讨。结果表明，基于大数据技术的动态需求预测模型能够显著提高线路规划的精准性，而智能化调度算法的应用则有效降低了车辆空驶率和乘客等待时间。此外，研究还提出了融合多模式交通协同发展的政策建议，为实现公共交通资源的高效配置提供了理论依据。本研究的创新点在于将数据驱动与智能技术引入传统规划方法，并结合实际案例验证了方案的可行性和优越性，其主要贡献在于为城市公共交通的可持续发展提供了可操作性强的优化路径和决策参考。
关键词：城市公共交通；优化策略；大数据技术；智能化调度；多模式交通协同
Abstract
With the acceleration of urbanization, issues such as traffic congestion, environmental pollution, and resource wastage have become increasingly prominent, making the optimization of urban public transportation planning and management a critical approach to addressing these challenges. This study aims to analyze systematically the current status and problems of urban public transportation and propose scientifically effective strategies to enhance the operational efficiency and service quality of public transit systems. By integrating multi-source data analysis, simulation modeling, and field surveys, the research explores three dimensions: network layout optimization, operational scheduling improvement, and the construction of a policy support system. The findings indicate that dynamic demand prediction models based on big data technology can significantly improve the accuracy of route planning, while the application of intelligent scheduling algorithms effectively reduces vehicle idling rates and passenger waiting times. Furthermore, the study puts forward policy recommendations for the integrated development of multimodal transportation, providing theoretical justification for the efficient allocation of public transportation resources. The innovation of this research lies in incorporating data-driven approaches and intelligent technologies into traditional planning methodologies, with the feasibility and superiority of the proposed solutions verified through practical case studies. Its primary contribution is offering actionable optimization pathways and decision-making references for the sustainable development of urban public transportation systems.
Keywords：Urban Public Transportation; Optimization Strategy; Big Data Technology; Intelligent Scheduling; Multi-Mode Traffic Coordination
目 录
摘要 I
Abstract II
一、绪论 1
(一) 城市公共交通规划与管理的背景 1
(二) 研究城市公共交通优化的意义 1
(三) 国内外研究现状分析 1
(四) 本文研究方法与结构安排 2
二、城市公共交通需求分析 2
(一) 公共交通需求特征研究 2
(二) 数据采集与分析方法 3
(三) 影响需求的关键因素探讨 3
三、公交系统规划优化策略 4
(一) 公交线路布局优化研究 4
(二) 车辆调度与资源配置分析 4
(三) 智能化技术在规划中的应用 5
四、公共交通管理效率提升研究 6
(一) 管理模式创新与实践 6
(二) 运营绩效评估体系构建 6
(三) 政策支持与实施保障 7
结 论 8
参考文献 9
