Xicpanahuī campa tlahtōlli
Pavelink Tlamatinih Ohtlachihchiuhtiani ītēchcopa Yan Zhang and Jialu Hou

Tlanāhuatīlli Pavelink Tlamatinih Ohtlachihchiuhtiani ītēchcopa Yan Zhang and Jialu Hou cē cencā mahuizzō tēmacēhualōni īpan huēyi 2025 Mahuizolli A' Design Award Tepoztli īpan Hualmoquetzaz Tlachihchihualiztli Nēhuilīztli Tlamantli.


TepoztliHualmoquetzaz· 2025

Pavelink Tlamatinih Ohtlachihchiuhtiani

īpal Yan Zhang and Jialu Hou

Tlanāhuatīlli: Shandong University of Art & Design

Mahuizolli A' Design Award Tepoztli Tēmacēhualōni īpan Hualmoquetzaz Tlamantli

71,246

Tlapalli

Tlanēxtilistli

Ītechcopa Pavelink Tlamatinih Ohtlachihchiuhtiani

Pavelink ca ce tlamatinih, momamani ohtlachihchiuhtiani tepoztlachihualli tlachihchiuhtoc para cualli tequitl, chipahualoni ihuan mochihualiz ipan altepetlachihualiztli. Quipia ce camion-nemiliztli tlen tzatzaquilia nahui momamani tlamamantli tlen mocuepah ipan monemitiani tlacuapaquiliztlachihualmeh, tlaquetzanimeh, tlallotlaoanmeh ihuan tlaltoquiliztlachihualmeh. Ce AI tlamatinih patlani tepoztlachihualli quitemaca tlalli tlapoaliztli ipan axcan cahuitl, para cualli chihua ohtlachihualiztli. Ipampa quicentilia automatización, momamani hueliztli ihuan tlamatinih nepantiliztli, PaveLink amo zan tlahuelililia ohtlachihualiztli auh noihqui palehuia para mopochohua altepetlachihualiztli ixpopoyotl, chihua chipahualoni ihuan huelitini ohtli mas mochihualiz.

Tēixīmachōtiliztli

Ītechcopa Mahuizolli A' Design Award Tepoztli

Pavelink Tlamatinih Ohtlachihchiuhtiani ca in quicuic in Mahuizolli A' Design Award Tepoztli, tlamahuizoliztli tlen momaca in cualli dizayno in quitlalia in tlen monequi ipan tequitl ihuan tlachihualiztli in quimaca in cualli tlachihualli. In quicuicah Tepoztli quinextia in hueyi tlamatiliztli, toltecayotl ihuan ihuelitiliztli intlachihuanime. Ca quinequi in Pavelink Tlamatinih Ohtlachihchiuhtiani ca tlazohtli, mahuiztic, yancuic ihuan motequiuhtia. Ni dizayno in quicuic Tepoztli quihuelitia in tlamatiliztli ihuan quipia chicahualiztli tlen tepoztli. Pavelink Tlamatinih Ohtlachihchiuhtiani quicualtia in nemiliztli ihuan quihuelitia in cemanahuac ica cualli.

Tlanēxtilistli Ītēixpan

Āmatl Tlanextīliztli

Tlapōhualli, tēquitqueh īwan tēchmachilīztli ōquinmaca in tlanēxtīlīlli.

Cē Zan Ītēchcopa
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.
Huēyiliztli īhuān Tlacualtepēhualli
17000mm x 4210mm x 3890mm
Tōcāitl
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
Tlachīhualiztli Māchiyōtl
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.
Tlanāhuatīlli Nētēcahuilīztli
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.
Tlatēmōliztli
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.
Tēyōllālīliztli
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.
Tēquitl Cāhuitl
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.
Tēquitl Ōhuitl
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.
Calpolli Tlācah
Yan Zhang
Jialu Hou
Īxiptla Tlanēxtīlli
Project Assistant Lulu Zhang, Wenyi Qin

Tlacōhualli

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