It can be hard to hail a cab in Singapore when you need it the most. Taxis seem to disappear during the frequent tropical showers, and this was proven when MIT researchers compared rainfall data with taxi locations: drivers are less likely to pick up passengers for fear of having an accident.
Transport data can reveal plenty about people’s behaviour and preferences. Which is why this week GovInsider explores how Singapore’s open data on taxis can be used.
The data, published by the city’s Land Transport Authority, shows how many taxis are available for hire and where they are located. The best part is that the data is in real-time. It can be used with an Application Programming Interface (API) – a tool that lets apps directly access the data.
No other city in the region is currently publishing this data. Officials in Jakarta and Kuala Lumpur, where transport is a key challenge, could benefit from releasing this data for citizens to come up with new ways of using it.
Combining taxi data with other datasets and using machine learning can help predict where and when taxis might be needed the most in the future, allowing transport officials to prepare for this in advance. For example, this data together with flight and train arrival schedules can be used to predict taxi queues at airports and stations. Officials can use this to make sure there are enough taxis available to pick up passengers and minimise their waiting times.
Singapore’s real-time taxi data can be accessed from here.