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A Vehicle-to-Everything (V2X) Interaction System for Intelligent Transportation Based on Energy Harvesting–Sensing Cooperation Triboelectric Nanogenerator

  • Xinmao Zhao
  • , Long Liu
  • , Dezhi Yin
  • , Yifeng Su
  • , Tong Hu
  • , Yusheng Zheng
  • , Tao Yang
  • , Qiongfeng Shi
  • , Kai Tao
  • Northwestern Polytechnical University Xian
  • Southeast University, Nanjing

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

The convergence of advanced sensing and wireless communication technologies has transformed vehicles into multifunctional platforms with personalized features while reshaping transportation systems through enhanced environmental perception and vehicle–road coordination. Onboard sensors face critical limitations in achieving sustained perception of on-road driving conditions, whereas triboelectric nanogenerators (TENGs) harness synergistic vibration energy and collect vibration information to enhance intelligent vehicle integration within smart transportation ecosystems. Herein, we present a vehicle-to-everything (V2X) interaction system fused with energy harvesting–sensing cooperation TENG (EHSC-TENG) device. The nested orthogonal structure enables simultaneous energy capture from road vibrations and high-precision road condition detection. Integrated wireless modules ensure reliable communication in complex road environments, supporting real-time data exchange between vehicles and the infrastructure. A deep-learning-powered interface achieves accurate recognition of diverse vehicles and road conditions, validated through field tests under various scenarios. Experimental results demonstrate the system’s effectiveness in collision prevention and road information sharing while autonomously powering onboard electronics. This work establishes a self-sustained framework for a next-generation intelligent transportation system (ITS), featuring intelligent vehicles with integrated V2X interaction systems and dual-functional devices that combine energy harvesting and environmental sensing. This architecture directly addresses the dual challenges of onboard sensor power autonomy and road perception reliability in vehicular environments.

Original languageEnglish
Pages (from-to)7419-7431
Number of pages13
JournalACS Applied Electronic Materials
Volume7
Issue number15
DOIs
StatePublished - 12 Aug 2025

Keywords

  • deep learning
  • energy harvesting–sensing cooperation
  • intelligent transportation system
  • triboelectric nanogenerators
  • vehicle-to-everything

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