On November 7, Shanghai put out its innovation action plan for "AI + transportation." The launch took place at the National Exhibition and Convention Center, part of the 9th China International Import Expo, and Shangguan News and Jiefang Daily were there for it. The plan rests on three technical foundations — transportation large models and agents, high-quality industry datasets, and computing clusters — with compute support anchored on the Yangtze River Delta national computing hub.
The flagship projects read like a checklist of what the city actually wants to run. MaaS integrated mobility, digital twins of tunnel clusters, unmanned port collection-and-distribution, and intelligent government services for transportation all made the list. The plan also asks for a trusted transportation data space, mechanisms for scenario opening and evaluation iteration, talent development, and stronger cross-department governance with full-chain algorithm security. What Shanghai wants out of all this, eventually, is a replicable "Shanghai experience" in smart transport.
Two platform initiatives were unveiled at the same event. The Yangtze River Delta coordination center of the Transportation Large Model Innovation and Industry Alliance was inaugurated, with its secretariat sitting in Shanghai. Construction of an AI pilot-testing base for shipping and logistics hubs also got underway. That one builds on serious pedigree — the Port of Shanghai has held the title of world's busiest container port for 16 consecutive years. SIPG, for its part, is assembling a "1331X" capability system that manages 54 business agents across three core scenarios: in-port handling, collection-and-distribution, and multimodal transport.
Universities got their turn in the same session. Tongji University, Shanghai Jiao Tong University and Shanghai Maritime University jointly released "AI + transportation" outcomes covering transportation large models, vehicle-road cooperation, intelligent ship navigation and port digital twins. Zhu Xingyi, vice dean of Tongji's College of Transportation, walked through a virtual-real fusion simulation platform. It maps real vehicle trajectories into a virtual environment, which neatly gets around the problem that extreme scenarios simply cannot be staged on real roads.
From action plan to pilot base to campus results, Shanghai is pinning AI-transport convergence on verifiable lists of scenarios.