Open Data & Analytics For Urban Transportation
Enhancing Public Transport Using Data
Did you know that our public buses are installed with sensors?
The Land Transport Authority (LTA) has been using these sensors to gather information on buses’ real-time location and arrival times at various stops to improve their transport planning.
LTA has also been collecting anonymised data from commuters’ fare cards to help identify commuter hotspots, which enables them to better manage bus fleets and commuter demand.
As a result of this data collection and analysis, LTA has seen improvements on these fronts:
- 92% reduction in the number of bus services with crowding issues, despite a year-on-year increase in average daily bus ridership
- 3- to7-minute reduction in the average waiting time on popular bus services
This is just one example of how insights from data can help LTA improve policy planning to provide a better commuter experience for residents. Read on to find out how else.
Singapore Traffic Watch
SG Traffic Watch uses a combination of real-time data and historical analysis to provide insights to help manage our road traffic.
It pulls data from LTA’s Land Transport DataMall and NEA weather service, providing analytical charts that plot current traffic conditions against past trends. Their real-time map lets users explore how the different data sources can help to explain congestion and other traffic situations.
Why is Open Data Important?
Open transport data provides useful information that both the public and third-party developers can easily tap on to create efficient transport solutions.
Currently, users are free to access LTA’s Land Transport DataMall transport data sets for:
- Real-time data on bus arrival timings
- Taxi availability
- Traffic conditions
- Carpark availability
The data is well-accessed: Statistics show that downloads of this data have increased from an average of 4 million to 600 million per month since April 2015.
This data has also been put to good use, with several third-arty transport apps developed as a result. One example is the Bus Uncle chatbot, a helpful bus guide app with a well-loved grumpy “uncle” persona who speaks swee Singlish.
Check out other apps that use the Land Transport DataMall open data.
Beyond Collecting Data
As technology improves, we find even more innovative ways to leverage data analytics to improve our transport system.
For instance, LTA has a next-generation Electronic Road Pricing (ERP) system in the works to collect comprehensive, real-time, aggregated traffic data. This will enable LTA to intervene more effectively, such as by adjusting traffic light timings and providing priority for buses.
Another example is the Fusion AnalyticS for public Transport Emergency Response (FASTER) system, which crunches data collected from various sources to:
- Help authorities and public transport operators visualise commuting patterns to improve transport planning
- Trigger early alerts for surge in crowds
- Predict the impact of incidents such as transport delays and the number of commuters affected
- Recommend measures such as the injection of additional trains and buses to respond to transport incidents quickly