Intelligent Networked Vehicle Sensor Synthesis Experiment Box

Zeyuan Li; Shuyan Ren; Hailong Duan; Yin Huang

doi:10.6919/ICJE.202511_11(11).0006

Intelligent Networked Vehicle Sensor Synthesis Experiment Box

Zeyuan Li, Shuyan Ren, Hailong Duan, Yin Huang

International Core Journal of Engineering, (2025), Vol.11, No.11, pp.59-66

Published: November 22, 2025

DOI: 10.6919/ICJE.202511_11(11).0006

PDF: Download Full Text PDF

Abstract

The diversity of sensor technologies plays a critical role in intelligent connected vehicles (ICVs), yet existing educational platforms face challenges in cost and accessibility. This paper presents a low-cost, modular sensor synthesis experiment box tailored for ICV pedagogy. By integrating heterogeneous sensors (e.g. LiDAR, ultrasonic) with an STM32-based control system, the platform enables hands-on experiments on sensitivity analysis and multi-sensor fusion. Experimental results demonstrate a temperature measurement accuracy of ±1°C, while the user-friendly host computer interface improves operational efficiency by 40% compared to traditional setups. This work provides a scalable solution for sensor education in intelligent transportation systems.

Keywords: Intelligent Connected Vehicles (ICVs); Multi - sensor Fusion; Sensor Technologies.

APA Citation: Zeyuan Li, Shuyan Ren, Hailong Duan, Yin Huang (2025). Intelligent Networked Vehicle Sensor Synthesis Experiment Box. International Core Journal of Engineering, 11(11), 59-66. https://doi.org/10.6919/ICJE.202511_11(11).0006

References

D. YU Duo,WANG Yaonan,MAO Jianxu,et al. Vision-based target tracking method for mobile robots[J]. Journal of Instrumentation,2019,40(01):227-235.
FAN Yibiao,LU,FU Zhihe. Robust vehicle detection in autonomous driving scenarios[J]. Journal of Electronic Measurement and Instrumentation, 2018,32(12):60-65.
ZHANG Yanhui,XU Kun,ZHENG Chunhua,et al. Research progress of information sensing technology for intelligent electric vehicles[J]. Journal of Instrumentation ,2017,38(04):794-805.
Jiang Baiping. Application of sensors in driverless cars[J]. Times Automotive,2024,(24):189-191.
DU Kaibin,GUO Junjun. Research on motion trajectory tracking algorithm of intelligent vehicle[J]. Journal of Electronic Measurement and Instrumentation,2020,34(06):131-137.
ZHAO Peng,ZHANG Yan,JIANG Liling. Research on design scheme and control of intelligent vehicle with multi-sensor fusion[J]. Industrial Instrumentation and Automation Device,2024,(06):81-87+108.
TONG Zhongsheng. Research on the application of environment sensing system in intelligent networked vehicles[J]. Internal Combustion Engines and Accessories,2024,(12):111-113.
Lian Tianyu. Research on lane-changing decision-making of driverless cars in urban environment[D]. Shenyang university of technology,2021.
Lv Pin,Li Kai,Xu Jia,et al. Optimisation technique of cooperative sensing information transmission load for driverless cars[J]. Journal of Computing,2021,44(10):1984-1997.
Li Xuchuan. Research on lane changing trajectory planning method for driverless cars in multi-vehicle environment[D]. Chang'an University,2021.