Singapore is tackling a public transport labor shortage by rolling out driverless electric buses and AI-powered traffic systems. As young people in Singapore are no longer interested in driving buses, transport authorities are partnering with technology firms to deploy autonomous vehicles designed to handle unpredictable tropical rainfall and congested urban corridors.
The push toward automation comes as demographic pressures mount on the island nation’s public transit network. Government figures released in July 2026 revealed that Singapore maintained 9,900 bus captains, with foreign workers making up 60 percent of the workforce. The aging demographic of these workers compounds the issue, as 57 percent of the captains were between 41 and 60 years old, and 13 percent were above the age of 60.
Why are young workers turning away from bus driving?
Harold Teng, chief project coordinator at Singapore technology firm MKX Technologies, pointed to shifting labor preferences during the Singapore Urban Mobility Week 2026, held from Wednesday to Friday at the Suntec Singapore Convention and Exhibition Center. “Many young people in Singapore are no longer interested in driving buses. A lot of the drivers come from overseas,” Teng said.
To counter this talent drain, MKX Technologies teamed up with China’s autonomous driving company MOGOX and carmaker BYD to secure an autonomous-bus pilot project awarded by Singapore’s Land Transport Authority. Six buses previously procured by the authority arrived in Singapore, where the three companies unveiled a new 8.5-meter right-hand-drive Level 4 autonomous electric bus.
How do autonomous buses handle Singapore’s heavy rain?
Adapting heavy machinery to Singapore’s climate and traffic rules required extensive localized software training. Lyu Bin, vice president of MOGOX, noted that the vehicles utilized locally collected road data to train their guidance systems.
“It rains frequently in Singapore, and the rainfall can be quite unpredictable,” Lyu said.
To manage these conditions, the new bus model incorporates rain sensors that adjust vehicle speed to changing conditions. In extreme weather events, such as torrential rain, the system disengages autonomous driving and hands control back to a safety operator.
Chinese firms showcase vehicle road cloud integration technologies
Beyond individual vehicles, artificial intelligence is reshaping how entire road networks operate. More than 200 companies took part in the exhibition, including 30 firms from China showcasing technologies centered on “vehicle-road-cloud integration,” where vehicles, road infrastructure, and cloud platforms exchange information to improve traffic management.
Chinese video surveillance provider Hikvision demonstrated its Guanlan large-scale AI models, which analyze traffic conditions using feeds from roadside cameras mounted on lamp posts. Lin Hongxun, product manager at Hikvision Singapore, explained how the system monitors vehicle speeds and traffic density.
For example, the system could detect a high volume of automobiles showing up within a brief timeframe inside a single camera view on a highway. Mitigation strategies can then be proposed by the software, such as suggesting alternative routes to motorists, swapping a reversible lane’s orientation, or repositioning barriers to reroute traffic. Human traffic managers decide whether to act on the recommendations.
At an intersection, Lin noted, the system might detect congestion in the east-west direction while north-south lanes are nearly empty, prompting a suggestion to extend the east-west green light by ten or 20 seconds. Parts of this system are already in use on some roads in Singapore, alongside deployments in the Philippines, Malaysia, Indonesia, Vietnam, and several Central Asian countries.
Signaling systems reduce train intervals and wait times
“There are no drivers anymore. Everything is controlled by software,” Zhang said, noting additionally that achieving a seamless journey relies heavily on precise timing regarding acceleration, deceleration, and the exact magnitude of those adjustments.
