Research and Application of Key Technologies for an Intelligent Transportation Digital Infrastructure Integrating BeiDou and AI

LI Jixin, TENG Delin, LIU Ling, HU Wenhui

Abstract: With the growing demand for high precision, low-latency operation, and intelligent decision-making in intelligent transportation systems, current digital infrastructures face limitations in real-time data processing, multisource heterogeneous information coordination, and traffic situational awareness. This paper proposes an integrated architecture leveraging the BeiDou Navigation Satellite System and artificial intelligence (AI). Aiming to overcome the limitations of single-technology approaches through the deep integration of “BeiDou and AI”, the architecture enables high-precision spatiotemporal information acquisition and collaborative optimization of intelligent decisionmaking. First, a four-layer architecture is constructed to establish its foundational role in integrating spatiotemporal data and supporting traffic data analysis and applications. On this basis, key breakthroughs are achieved in multidimensional fusion technology for multi-source heterogeneous spatiotemporal data, addressing challenges related to data diversity, complexity, and standardization to achieve efficient fusion. Ultra-precise BeiDou spatiotemporal positioning analysis technology is developed to provide high-precision positioning guarantees for traffic information. AI-based spatiotemporal intelligence analysis technology is introduced to enable traffic flow prediction and intelligent scheduling, thereby improving management efficiency. Application cases in the Xixian New Area demonstrates demonstrate that this digital platform significantly enhances infrastructure monitoring accuracy and traffic scheduling efficiency, establishing both a technical paradigm and implementation methodology for the construction of intelligent transportation systems.

Keywords: BeiDou Navigation Satellite System; artificial intelligence (AI); intelligent transportation; digital infrastructure; spatiotemporal intelligent analysis for transportation

融合北斗与人工智能的智慧交通数字底座关键技术研究与应用

李继新，滕德麟，刘玲，胡文慧

摘要：随着智慧交通系统对高精度、低时延运行与智能决策能力的需求持续增长，现有数字基础设施在实时数据处理、多源异构信息协同、交通态势感知等方面短板日益凸显。本文提出一套融合北斗卫星导航系统与人工智能（AI）的一体化技术架构。该架构通过北斗与人工智能的深度耦合，突破单一技术方案的固有局限，实现高精度时空信息获取与智能决策的协同优化。首先，本文搭建四层体系架构，夯实其在时空数据融合、交通数据分析与行业应用层面的基础支撑能力。在此基础上，攻克多源异构时空数据多维融合关键技术，解决数据多样性、复杂性与标准化难题，实现数据高效融合；研发北斗超高精度时空定位解析技术，为交通全域信息感知提供高精度定位保障；引入基于人工智能的时空智能分析技术，实现车流精准预测与智能调度，全面提升交通运行管理效能。西咸新区的落地实践案例表明，该数字化平台可显著提升交通基础设施监测精度与交通调度运行效率，为智慧交通体系建设构建了全新技术范式与落地实施路径。

关键词：北斗卫星导航系统；人工智能（AI）；智能交通；数字基础设施；交通时空智能分析

来源：中国知网

Source: https://link.cnki.net/urlid/10.1797.N.20260127.1628.002

发表时间：2026年1月28日

Date: January 28, 2026

检索：范薇

翻译：王烨

一审：王建秀

二审：彭莉

三审：罗玲娟

上传发布：姜浩