基于物联网与大数据融合的城市公交实时调度优化研究

Research on real-time scheduling optimization of urban public transportation based on the integration of Internet of Things and big data

摘要

随着城市交通系统日趋复杂与客流波动性增强，传统公交调度机制已难以满足实时性与灵活性要求，亟需引入新兴技术予以优化。物联网技术具备高频率、多维度感知能力，大数据技术则提供多源异构信息的高效整合与深度挖掘能力，两者融合为城市公交调度提供智能化解决路径。本文以西安市公交6公司18路汽车调度为案例，构建融合物联网与大数据的公交实时调度优化模型，系统分析当前研究现状，论证调度优化的现实价值，并结合实际调度场景，提出基于机器学习算法的调度模型构建路径与系统实现策略，为城市公交精准调度、资源动态配置提供技术支撑与模型范式。

Abstract

With the increasing complexity of urban transportation systems and growing passenger flow volatility, traditional bus dispatching mechanisms can no longer meet real-time and flexible requirements, making it imperative to introduce emerging technologies for optimization. IoT technology’s high-frequency, multi-dimensional sensing capabilities, combined with big data’s ability to efficiently integrate and deeply mine heterogeneous information sources, provide an intelligent solution for urban public transport scheduling. Taking Xi ‘an Bus Company 6’s Route 18 dispatching as a case study, this paper constructs a real-time dispatch optimization model integrating IoT and big data. The research systematically analyzes current industry practices, demonstrates the practical value of dispatch optimization, and proposes machine learning-based model construction strategies and system implementation approaches through real-world scenarios. These contributions provide technical support and model paradigms for precise urban public transport scheduling and dynamic resource allocation.

关键词

物联网 / 大数据 / 融合 / 西安市 / 城市公交 / 实时调度 / 优化 / 研究

Key words

IoT / Big Data / Integration / Xi’an City / Urban Public Transport / Real-Time Dispatching / Optimization / Research

参考文献

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[2] 王增鑫, 孙锐. 城市公共交通智能调度系统设计与实现——基于物联网与大数据技术[J]. 人民公交, 2024(13): 89-93.

[3] 王成杰, 徐九韵, 朱兰芳, 等. 物联网数据融合的动态队列感知CSMA调度方案[J]. 计算机与数字工程, 2023, 51(1): 181-185.

[4] 公维杰, 黄钰婷. 基于物联网的公共交通客流预测研究[J]. 人民公交, 2024(11): 77-82.

[5] 张聪. 智慧城市多维感知数据预测与公共资源调度技术研究[D]. 北京邮电大学, 2022.

基金资助

基于物联网与大数据融合的城市公交实时调度优化研究(300102365821)