ST Autonomous Mini-Bus (Autobus)

ST Autobus
ST Autobus featured during the Singapore Airshow 2018
ST Autobus featured during the Singapore Airshow 2018
Manufacturer ST Engineering Land Systems
Years in operation 2019
Operators Sentosa Development Corporation (Future)
Technical Data
Length 6.8 metre
Motor TBC
Accessibility Low Floor & Wheelchair-accessible
Emission Standard NA (Zero tailpipe emissions)

The Singapore Technologies (ST) Autonomous Mini-bus, or the ST Autobus, is an autonomous, low-floor, battery-electric single-deck city bus built by ST Engineering Land Systems (formerly known as ST Kinetics).

2 units of the ST Autobus will be trialled for 3 months in 2019, operating a 5 km route within Sentosa Island (likely the Sentosa Beach Tram Route), alongside another 2 units of Navya Autonom Shuttle.

Background Information:

On 10 April 2017, ST Kinetics (presently ST Engineering Land Systems) announced that it will develop four Mobility-on-Demand-Vehicles (MODVs) with Sentosa Development Corporation (SDC) and the Ministry of Transport (MOT). These vehicles are the ST Autobus and Navya Autonom Shuttle.

The ST Autobus was put on static display during the Singapore Airshow 2018 as part of a booth by ST Engineering.

The buses are registered under Research and Development, with one unit bearing the plate number RD3153M.

Autonomous Technologies:

The Mini-Bus is fitted with an array of sensors which enables it to navigate on its own in urbanised areas with or without the aid of GPS. It is also able to sense and recognise its surroundings and obstacles such as vehicles and pedestrians in a safe and reliable way, without compromising passengers’ safety.

Charging System:

Plug-in Charging System

See Also: Autonomous Buses in Singapore

ST Autobus:

Basic Technical Specifications
Size 6.8m (Length)  x  2.3m (Width)  x  3m (Height)
Weight Curb Weight: 6,600kg | Gross Vehicle Weight: 9,900kg
Motor / Battery Electric Motor paired with Lithium Titanate Oxide batteries, 46 kWh
Bodywork Not Applicable (Integral bodywork)
Seating Capacity Configurable
Standard: 10 Seated, 12 Standing, 1 Wheelchair
Door 1 Door; 1 emergency door
Maximum Operating Speed Up to 40 km/h
Operating Range 30 – 50 km, depending on operating scenarios
Autonomous Capability
  • Manoeuvres in both GPS and GPS-deprived environments
  • Navigates under both normal and wet weather conditions
  • Detects vehicles and pedestrians up to 150m

The Mini-Bus can be summoned through a Ride-on-Demand app, which uses a back-end Robotics Management System to calculate the best route.

Once a request is confirmed, the commuter can make his way to the predetermined stop, and wait for the ride.

Complementing this with other transit services, commuters can cut down on transfers.

The autonomous bus trial:
AV Testing Sign at Sentosa (Tanjong Beach Walk)
AV Testing Sign at Sentosa (Tanjong Beach Walk)

On 5 June 2018, in a joint press release with MOT, SDC, and STE, a three-month operational trial was announced for 2019, with commuters being able to hail the autonomous buses via their smartphones or at designated kiosks set up along the 5 km route on Sentosa Island. The 5 km route is believed to the be Sentosa Beach Tram route, plying from Beach Station to Siloso Point, Palawan Beach, and Tanjong Beach.

The trial was mentioned back in April 2017, as part of a partnership between Ministry of Transport and Sentosa Development Corporation for a two-year trial involving MODVs. Routes identified back then for the autonomous vehicles were between Tanjong Beach – Siloso Point, Palawan East – Siloso Point & Sentosa Golf Club – Imbiah Lookout.

From 5 June 2018, the autonomous shuttles were tested along a 1 km stretch of service road at Tanjong Beach to iron out their operational systems and safety protocols. The testing would be progressively extended to a 2km route linking Palawan and Siloso beaches by the end of 2018. During the testing phase, the autonomous vehicles will not ferry commuters.

As part of the trial, ST Kinetics developed a platform agnostic fleet management system which will analyse passenger demand planning and optimise route management in ride-sharing services.

Corporate Video:
External Links & References:

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