| Summary: | On-demand transportation has becoming very important as the number of tourists and population in Singapore continues to increases rapidly. As a first world country, the efficiency of our transportation is very vital to our economic as well as tourism. With the fast improvement of technology in the field of artificial intelligence, driverless vehicles and autonomous vehicles no longer only appear in the films. ST Engineering Group is the first in Singapore to have taken the initiative to set up its own autonomous vehicles as a public transportation system in different location of Singapore. This has triggered the use or the development of a simulation tool to replicate the specific scenarios suggested by ST Engineering. The purpose of the simulation tool was to provide evidence on the benefits of the autonomous vehicle deployment. It also allows us to find out the different methods to maximize the overall efficiency of the network without implementing the actual things out. Regardless of the problems face throughout the entire project, the final product will be able to simulate the actual scenario and provide solution when it comes to different situations.
The focus of this project is to increase the efficiency of Sentosa Express transportation system in Sentosa. The main objective is to develop an algorithm which improve the efficiency of the Sky train by reducing the waiting time of the passengers. Besides this, one of the other objectives is to replicate part of the architecture, model of buildings, gardens, sky train and other geometry in Sentosa using the simulation software PTV Vissim. PTV Vissim is equipped with many visualization and design models and an interface, called as COM to deploy and test customized algorithms written using Matlab. Another approach to address the waiting time reduction is achieved by varying the frequency of the sky train. Accompanied with various appropriate measurement techniques, the collected data will be helpful as it will equip organizations with better insights when it comes to decision-making through anticipating and behavioural analysis. Thus, it will improve the overall performance.
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