人工智能赋能城市公交未来发展路径探析——以重庆公交实践为例

Exploring the Future Development Path of Urban Public Transportation Empowered by Artificial Intelligence—Taking Chongqing Public Transportation Practice as an Example

摘要: 数字技术与交通行业的深度融合，推动城市公交进入数智化转型升级关键阶段。传统公交依赖人工经验运营的模式，存在运力匹配失衡、维保成本偏高、安全管控被动、服务同质化等痛点，难以适配超大城市精细化治理与市民高品质出行需求。重庆作为典型山地超大城市，路网碎片化、地形复杂、客流潮汐特征显著，常规平原城市智能公交模型与算法适配性不足。本文以重庆公交数智化实践为样本，立足山地公交特殊运营场景，梳理人工智能赋能公交发展的核心价值与现实基础，结合国内外现有研究成果，对比优化智能调度、车辆故障预测核心模型的技术路径，明确本土场景创新优势。同时系统剖析AI转型过程中数据治理、技术集成、成本管控、合规体系、组织人才五大维度挑战，提出针对性落地对策，探索人工智能赋能城市公交高质量发展的可行路径，为国内山地城市智慧公交建设提供实践参考与理论支撑。

Abstract: The deep integration of digital technology and the transportation industry has propelled urban public transportation into a critical stage of digital and intelligent transformation and upgrading. The traditional public transportation model, relying on manual experience, suffers from pain points such as capacity mismatch, high maintenance costs, passive safety management, and homogenized services, making it difficult to adapt to the refined governance and high-quality travel needs of megacities. Chongqing, as a typical mountainous megacity, has a fragmented road network, complex terrain, and significant tidal passenger flow characteristics, making conventional intelligent public transportation models and algorithms for plains cities insufficiently adaptable. This paper takes Chongqing’s digital and intelligent public transportation practice as a sample, focusing on the special operating scenarios of mountain public transportation, outlining the core value and practical basis of artificial intelligence empowering public transportation development, combining existing research results at home and abroad, comparing and optimizing the technical paths of core models for intelligent scheduling and vehicle fault prediction, and clarifying the innovative advantages of local scenarios. This system also systematically analyzes the challenges of AI transformation across five dimensions: data governance, technology integration, cost control, compliance systems, and organizational talent. It proposes targeted implementation strategies and explores feasible paths for AI-enabled high-quality development of urban public transportation, providing practical reference and theoretical support for the construction of smart public transportation in mountainous cities in China.