The large-scale application of autonomous driving: a new engine for social development
We have 21 routes by deploying 50 autonomous buses and eight remote operation platforms. By the end of October 2025, cumulative service had exceeded 1.23 million passenger journeys, with operational mileage surpassing 2.35 million kilometres, and no at-fault incidents had occurred.
About this Project
Under traditional transport models, labour costs account for as much as 60% of total expenditure. Achieving full automation is projected to reduce operational costs by approximately 60% in the future, driving a fundamental transformation in urban public service delivery.
Through high-precision sensors and algorithms, the vehicle perceives its surroundings in real time and makes rapid judgements, eliminating human factors such as fatigue driving, operational errors, or sudden illness.
This enhances driving stability and safety. Since the project’s testing phase commenced, it has achieved zero liability safety incidents.
Key Highlights
Guangzhou Public Transport has pioneered the exploration of an autonomous bus operation service model integrating ‘scenario-based operations with intelligent driving research and development’.
The Guangzhou Public Transport Group has adopted a dual-pronged approach centred on effectively managing and operating ‘AI drivers’, integrating autonomous buses into the city’s public transport system.
Under this framework, autonomous mobility service providers oversee scenario operations while autonomous driving technology firms focus on intelligent driving algorithm research, thereby achieving an integrated management upgrade for autonomous bus operations.
Facts & Figures
- People that were positively affected: By the end of October 2025, Guangzhou's public transport system had served over 1.23 million passengers, covered more than 2.35 million kilometres, and recorded no at-fault incidents.
- Modal shift: Public transport vehicles are shifting from traditional manual driving to autonomous operation, with conventional bus drivers transitioning to autonomous driving safety officers.
