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Autonomous Vehicles & ADAS

ST Engineering accelerating Singapore’s use of AVs for urban mobility issues

Tom StoneBy Tom StoneApril 11, 20173 Mins Read
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Following yesterday’s (April 11) news that it will be developing autonomous buses with the Land Transport Authority (LTA), Singapore Technologies Engineering (ST Engineering) has announced several other initiatives to advance Singapore’s Smart Mobility 2030 vision of a smart transportation network and strengthen the city-state’s leadership in the development of autonomous vehicle (AV) technologies.

As well as the 40-seater autonomous buses that will be developed over 42 months to run on fixed and scheduled routes by 2020, ST’s Kinetics division will also develop four Mobility-on-Demand Vehicles (MODVs), and will be working together with government-owned Sentosa Development Corporation (SDC) and the Ministry of Transport (MOT) to deploy them for trials at the Sentosa Island resort. This follows the completion of a front-end engineering study, which started in July 2016, on technical requirements, such as the feasibility of routes for autonomous vehicles to navigate seamlessly around Sentosa. The development of these AV technologies will draw from ST Kinetics’ engineering expertise in developing military robotics and systems integration capabilities using existing vehicle platforms, sensors and computers to effectively deploy autonomous, commuter-friendly, mass transport modes for intra-town and first-mile/last-mile travel.

In early 2019, the four MODVs, each with seating capacities ranging from 15 to 20 passengers, will be deployed in a pilot public trial to provide autonomous mobility-on-demand service to visitors to serve their intra-island travel needs in Sentosa. A key feature of the trials is a platform agnostic fleet management system, developed by ST Kinetics’ team of software engineers that analyzes passenger demand planning and optimizes route management in these types of ride-sharing services. Visitors will be able to call for the MODV via their smartphones or information kiosks located across the island. Another indigenous development is in the field of artificial intelligence (AI), based on deep learning algorithms, which will enable the MODVs to learn and emulate the behavior of an expert human driver.

ST Engineering has also launched the Singapore Autonomous Vehicles Consortium (SAVC) to facilitate and strengthen collaboration between industry partners and academic institutes to develop AV standards, as well as accelerate the application and adoption of AV technologies in Singapore. These efforts will support the development of testing requirements for AVs undertaken by the Center of Excellence for Testing & Research of AVs at the Nanyang Technological University (NTU). Led by its land systems arm ST Kinetics, the consortium includes: A*STAR’s Institute for Infocomm Research (I2R), National University of Singapore’s Faculty of Engineering, Singapore University of Technology & Design, NTU through the ST Engineering-NTU Corporate Lab, and Singapore Institute of Technology.

The consortium will focus on two core areas based on their respective domain expertise: to identify protocols and standards for the adoption of AVs in real-world scenarios; and to develop niche AV technologies, such as automotive cybersecurity, advanced autonomy and platform-agnostic AV kits, through a build-test-deploy spiral approach. This spiral developmental approach ensures that AV technologies are tested and demonstrated at different stages of development to reduce risk, and enhance reliability and readiness for deployment.

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Tom Stone

Tom has edited Traffic Technology International (TTi) magazine and its Traffic Technology Today website since May 2014. During his time at the title, he has interviewed some of the top transportation chiefs at public agencies around the world as well as CEOs of leading multinationals and ground-breaking start-ups. Tom's earlier career saw him working on some the UK's leading consumer magazine titles. He has a law degree from the London School of Economics (LSE).

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