Understanding Ride-Hailing Traffic Patterns in Greater Jakarta

Ride-hailing apps have significantly transformed transportation in Indonesia, enabling more convenient pick-ups and drop-offs at affordable rates. Pulse Lab Jakarta in partnership with Grab, a ride-hailing, ride sharing, food delivery and logistics services technology company, has been investigating how anonymised data generated from customers’ use of these services can be leveraged to improve efficiency in the transportation system.

The visualization below show traffic patterns (inflows and outflows) in Greater Jakarta as inferred from Grab’s anonymised GPS data to better understand Greater Jakarta's traffic flows at macroscopic level.

Traffic Patterns in Greater Jakarta Area

This visualization shows traffic patterns in Greater Jakarta as inferred from Grab’s anonymised GPS data. A dot represents total traffic flow for a sub-district: the green dot indicates higher traffic flow into the destination (inflow) and the purple dot represents higher traffic flow going out of the destination (outflow) or equal inflow and outflow.


Higher inflow


Higher outflow or Equal inflow/outflow

Differences in Traffic Flows during Weekdays and Weekends

This visualisation compares traffic flows during weekdays and weekends. Differences in traffic patterns in several sub-districts are observed. For example sub-district Menteng, one of the busiest office and business areas in Jakarta, shows higher traffic during weekdays compared to weekends. An opposite trend is seen in commercial and tourist areas, like Bekasi Selatan and Bogor Tengah sub-districts. The colour maps the intensity of traffic in a given sub-district. The purple colour indicates lower traffic and gradually changes to green for higher traffic flows.


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We have used open source data features in developing the visualisation, making it easy for the approaches to be replicated in other cities. Our ambition is to further collaborate with other partners to investigate areas of urban dynamics through the use of data from ride-hailing services. Do you have ideas of how we can leverage transportation data to address a challenge in your city? Get in touch with us!

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