广东省公路建设有限公司深中通道管理中心,广东 广州 510699
[ "马二顺(1975‒ ),男,广东省公路建设有限公司深中通道管理中心高级工程师,主要研究方向为高速公路交通工程建设管理。" ]
[ "童威(1997‒ ),男,广东省公路建设有限公司深中通道管理中心助理工程师,主要研究方向为高速公路交通工程营运。" ]
收稿:2024-12-01,
修回:2025-01-01,
纸质出版:2025-09-10
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马二顺,童威.特殊隧道环境中的车辆定位关键技术研究[J].物联网学报,2025,09(03):152-160.
MA Ershun,TONG Wei.Research on key technologies of vehicle positioning in special tunnel environment[J].Chinese Journal on Internet of Things,2025,09(03):152-160.
马二顺,童威.特殊隧道环境中的车辆定位关键技术研究[J].物联网学报,2025,09(03):152-160. DOI: 10.11959/j.issn.2096-3750.2025.00451.
MA Ershun,TONG Wei.Research on key technologies of vehicle positioning in special tunnel environment[J].Chinese Journal on Internet of Things,2025,09(03):152-160. DOI: 10.11959/j.issn.2096-3750.2025.00451.
精准定位性能是保障汽车安全驾驶的重要条件。尽管现有全球导航卫星系统(GNSS
global navigation satellite system)在露天场景中表现出色,但在如隧道等GNSS拒止环境下实现高精度定位仍是一个挑战。特别是在钢壳沉管隧道这种全金属环境中,卫星信号极其不稳定,甚至完全无法接收。针对这一挑战,提出了一种隧道内路侧单元使能的协同定位架构(CAE-RSU
co-localization architecture for enabling roadside unit),旨在解决卫星信号无法穿透的问题,从而实现无缝、连续且高精度的定位服务。具体来说,利用隧道内设置的路测单元(RSU
roadside unit),建立车联网(V2X
vehicle-to-everything)无线通信定位系统,并采用无迹卡尔曼滤波算法以进一步提升定位的可靠性和精度。仿真结果表明,即使在高速运动和高噪声环境下,所提定位算法仍能实现优越的定位效果。
Accurate positioning performance is an important requirement for safe driving of automobiles. While existing global navigation satellite system (GNSS) performs well in open-air scenarios
achieving high-precision positioning in GNSS resistant environments such as tunnels remains a challenge. Especially in the all-metal environment of the steel shell immersed tube tunnel
the satellite signal is extremely unstable
or even completely unable to receive. To address this challenge
a co-localization architecture for enabling roadside unit (CAE-RSU) in tunnels was proposed
which aimed to solve the problem of impenetrability of satellite signals. Seamless
continuous and highly accurate positioning services were enabled. Specifically
the RSUs set up in the tunnel were used to establish the vehicle-to-everything (V2X) positioning system
and the traceless Kalman filter algorithm was used to further improve the reliability and accuracy of positioning. Simulation results show that the proposed positioning algorithm can achieve superior localization performance even under high-speed motion and high-noise environments.
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