Transport agencies around the Southeast Asian region should make use of the big data to transform network planning and daily commute, said Terry Bills, international smart transport specialist from Esri.
These big data are collected everyday from Global Positioning System (GPS) devices, smartphone apps and electronic ticketing.
Mapping and analysing big data can reveal previously hiding blind spots in transportation trends and traffic patterns that will enable better network planning and management.
"Location-based analytics is able to provide these insights in a highly visual and interactive narrative that simply can't be constructed from a table or standard database," said Bills. "This approach could assist transport agencies to predict the value of new routes and infrastructure and enable them to model various incentives and strategies on particular routes. [This will] reduce congestion and improve service delivery and reliability."
Singapore's LTA leverages analytics to improve public transport system
One example is Singapore's Land Transport Authority (LTA), which makes use of location-based analytics to establish a framework to analyse and manage the geographic information derived from its enterprise data warehouse Planning for Land Transport Network (PLANET).
Buses, trains and taxis in Singapore's public transport network are fitted with smart sensors that collect and transmit data daily to form BIG-DATA@LTA.
Deploying analytics on the data collected has allowed LTA's planners to map and analyse hotspots with persistent heavy-passenger loads during peak hours and to study commuter travel patterns.
The results are then used to engage town councils and community leaders to minimise differing views when assessing improvement measures.
In addition, the timely implementation of this technology enabled the government to roll out a S$1.1 billion bus service improvement programme. This has resulted in the deployment of an additional 1,000 buses to address over-crowding and frequency of service issues.
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