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Credit: SMART FM
E-scooters as a new micro-mobility service: SMART researchers explore the potential of e-scooter sharing as a replacement for short-distance transit in Singapore
SMART researchers found that e-scooters are not only a last-mile solution to complement transit services, but also provide a mobility service for short-distance transit trips
- Through a stated preference survey and mixed logit models, SMART researchers found that fare, transit transfer, and transit walking distance are significant factors driving the use of e-scooters as an alternative means of transit. The uncertainty is higher in predicting e-scooter usage preferences of male, young and high-income groups.
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IMAGE: Spatial distribution changes in PT supply during the competition: (left) Routes with supply decrease; (right) Routes with supply increase view more
Credit: Zhejing Cao and Baichuan Mo
Singapore, 5 May 2021 - The rapid advancement of Autonomous Vehicles (AV) technology in recent years has changed transport systems and consumer habits globally. As countries worldwide see a surge in AV usage, the rise of shared Autonomous Mobility on Demand (AMoD) service is likely to be next on the cards. Public Transit (PT), a critical component of urban transportation, will inevitably be impacted by the upcoming influx of AMoD and the question remains unanswered on whether AMoD would co-exist with or threaten the PT system.
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SMART breakthrough in materials discovery enables twistronics for bulk systems
The findings allow manipulation of materials for the first time by stacking films at a twist angle, allowing a new way to control light emitting from materials
Recent discoveries focused on manipulation of atomically-thin 2D materials, while the new breakthrough can be used to stack technologically-relevant 3D materials at a twist angle
Method allows continuous, systematic control of optical emission intensity and energy, and can produce ultraviolet emissions at room temperature for bulk systems
The discovery can be significant for applications in medicine, environmental or information technologies.
Researchers from the Low Energy Electronic Systems (LEES) Interdisciplinary Research Group (IRG) at Singapore-MIT Alliance for Research and Technology (SMART), MIT’s research enterprise in Singapore together with Massachusetts Institute of Technology (MIT) and National University of Singap
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IMAGE: A comparison summary of deep neural networks (DNNs) and discrete choice models (DCMs) characteristics view more
Credit: Singapore-MIT Alliance for Research and Technology (SMART)
Singapore, 19 April, 2021 - Researchers at the Future Urban Mobility (FM) Interdisciplinary Research Group (IRG) at Singapore-MIT Alliance for Research and Technology (SMART), MIT s research enterprise in Singapore, have created a synthetic framework known as theory-based residual neural network (TB-ResNet), which combines discrete choice models (DCMs) and deep neural networks (DNNs), also known as deep learning, to improve individual decision-making analysis used in travel behaviour research.
In this research paper, Theory-based residual neural networks: A synergy of discrete choice models and deep neural networks, recently published in established transportation science journal