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Pavelink Costruttore Stradale Intelligente by Yan Zhang and Jialu Hou
Pavelink Costruttore Stradale Intelligente by Yan Zhang and Jialu Hou
Pavelink Costruttore Stradale Intelligente by Yan Zhang and Jialu Hou
Pavelink Costruttore Stradale Intelligente by Yan Zhang and Jialu Hou
Pavelink Costruttore Stradale Intelligente by Yan Zhang and Jialu Hou

Ferro Futuristico · 2025

Pavelink Costruttore Stradale Intelligente

by Yan Zhang and Jialu Hou

  • A' Design Award di Ferro 2025 in Futuristico
  • CLIENT: Shandong University of Art & Design
  • Estimated Number of Design Views: 71,246
  • Verification code 10986AC0FB · Verify this award
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About Pavelink Costruttore Stradale Intelligente

Pavelink è una macchina modulare intelligente per la costruzione stradale progettata per migliorare l'efficienza, la sicurezza e l'accessibilità nello sviluppo delle infrastrutture. È dotata di un sistema a forma di camion che traina quattro moduli staccabili che si trasformano in compattatori, caricatori, bulldozer ed escavatori autonomi. Un drone alimentato dall'IA fornisce un'analisi del terreno in tempo reale, ottimizzando le strategie di pavimentazione. Integrando automazione, adattabilità modulare e coordinamento intelligente, PaveLink non solo accelera la costruzione stradale, ma contribuisce anche a ridurre le disparità infrastrutturali, rendendo le strade sicure e affidabili più accessibili

About the A' Design Award di Ferro

Pavelink Costruttore Stradale Intelligente ha vinto l'A' Design Award di Ferro, un riconoscimento prestigioso conferito a buoni design che soddisfano i requisiti professionali e industriali attesi da creazioni ben progettate. I vincitori di Ferro dimostrano la grande abilità, l'elevata specializzazione, la comprensione esperta e la capacità creativa dei loro creatori. Ci si aspetta che Pavelink Costruttore Stradale Intelligente sia una creazione molto apprezzata, ammirata e amata, pratica e innovativa. Questo design vincitore dell'A' Design Award di Ferro integra le migliori pratiche del settore e ha caratteristiche tecniche competenti legate a know-how e talento. Pavelink Costruttore Stradale Intelligente è rispettato per la sua accuratezza ed è progettato per offrire miglioramenti della qualità della vita che aiutano a rendere il mondo un posto migliore.

Press Kit

Unique Properties
PaveLink is a next-generation intelligent road builder, designed to enhance efficiency and safety in disaster relief and infrastructure projects. Unlike traditional road machinery, it features a modular architecture, allowing its components to detach and function autonomously for excavation, loading, bulldozing, and compacting. The truck head serves as the central control hub, managing all modules and processing real-time aerial drone data for optimized decision-making. This AI-enhanced system redefines the future of road construction.
Dimensions & Packaging
17000mm x 4210mm x 3890mm
Tags
Autonomous Road Construction, Modular Heavy Machinery, AI-driven Paving System, Smart Road Builder, IoT in Construction, Disaster Relief Equipment, Smart Construction Technology, Unmanned Machinery, Collaborative Fleet
Production Technology
The design follows a human-centered approach, addressing inequalities in infrastructure development while enhancing safety in road construction. A modular design strategy improves efficiency and functionality, integrating cutting-edge technologies such as IoT, autonomous driving, and AI-assisted automation to minimize labor dependency. Powered by electricity, PaveLink utilizes drone inspections and backend data analysis for multi-module collaboration. It is not just an improvement of existing machinery but a new category of heavy machines.
Design Challenge
PaveLink is not a traditional construction vehicle but a new category of heavy machinery, making it a pioneering design with no direct reference models. The challenge was to integrate multiple functions while ensuring practicality and efficiency. Setting high design standards required continuous validation. Through multiple iterations, expert consultations, and prototype testing with industry partners, we developed a modular and intelligent collaborative system to meet real-world construction demands.
Research
This research is a collaborative project between academia and industry, exploring how emerging technologies can be integrated into large-scale machinery to solve real-world challenges in infrastructure development and unequal access to construction resources. The study combined academic creativity with industrial expertise, where universities contributed design innovation, and companies provided technical support and operator insights through interviews and feedback. This collaboration ensured PaveLink’s feasibility, advancing smart construction solutions that promote efficiency, safety, and inclusivity in future infrastructure development.
Inspiration
Road construction is the backbone of local development, yet many underdeveloped regions, disaster-affected areas, and rugged terrains face immense challenges in building and maintaining roads. High construction complexity and safety risks remain persistent issues. Inspired by emerging technologies, PaveLink integrates AI-driven automation and IoT connectivity to address disparities in infrastructure development, making road construction smarter, faster, and more resilient.
Project Duration
The project was launched in Shandong in February 2024 and concluded in Shandong in June 2024. It was recognized by the Shandong provincial government and participated in the 14th National Art Exhibition of China in 2024.
Operation Flow
Initially, PaveLink appears as a single truck, with all road-building modules connected. Upon reaching the construction site, the truck head acts as the command center, operated by technicians. The modules detach and transition into autonomous operation, optimizing workflow through AI-coordinated control. Powered by electricity, all units remain linked via cables, receiving real-time power and instructions. Aerial drones detach to provide precise terrain mapping and safety monitoring, ensuring optimal performance in complex environments.
Image Credits
Project Assistant Lulu Zhang, Wenyi Qin

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