Tech, ExplainedIndustrial tech and mobility
Part

Ride dispatch and matching

The nearest driver, chosen in a second.

INSIDE: RIDE-HAILING APPHOW IT WORKS · A REQUEST IN ANDHERI, MUMBAI, AT 6:40 PMA rider asks fora cab to themetro stationThe softwarefinds 12availabledriverswithin 3 kmIt estimateseach driver'sarrivaltime usinglive trafficIt picks thedriver with a4-minute arrivalIt offers theride to thatdriver, whohas 15 secondsto acceptIf the driverdeclines, itoffers theride to thenext best oneALSO TALKS TOLocation APIs↗ GEOSPATIAL DATAINSIDE: RIDE-HAILING APPHOW IT WORKS · A REQUEST IN ANDHERI, MUMBAI, AT6:40 PMA rider asks for a cab tothe metro stationThe software finds 12available drivers within3 kmIt estimates eachdriver's arrival timeusing live trafficIt picks the driver witha 4-minute arrivalIt offers the ride tothat driver, who has 15seconds to acceptIf the driver declines,it offers the ride to thenext best oneALSO TALKS TOLocation APIs↗ GEOSPATIAL DATAINSIDE: RIDE-HAILING APP · A REQUEST INANDHERI, MUMBAI, AT 6:40 PMA rider asks for a cabto the metro station↓The software finds 12 available driverswithin 3 km↓It estimates each driver's arrival timeusing live traffic↓It picks the driverwith a 4-minute arrival↓It offers the ride to that driver, whohas 15 seconds to accept↓If the driver declines, it offers theride to the next best oneALSO TALKS TOLocation APIs↗ GEOSPATIAL DATA
A ride request arrives, the software scores nearby drivers by the time they would take to arrive, and offers the ride to the best one, who has a few seconds to accept.
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Ride dispatch and matching is the part of a ride-hailing app that finds the nearest suitable driver for each ride request, and predicts demand minute by minute so that drivers are in the right place. Dispatch is the industry's word for choosing which driver gets which ride.

The choice is not only about distance. The software estimates the time each driver needs to reach the rider, using maps and live traffic from location APIs. It also considers whether the vehicle fits the request, for example a cab, an auto or a bike taxi, and whether the driver is likely to accept. A driver who often declines or cancels is less likely to be offered the ride.

Consider two drivers near a railway station in Chennai. One is 500 metres away, but the road between them and the rider is cut by a flyover with no turn, so the drive is 6 minutes. The other is 1.2 kilometres away on the same road as the rider, and needs 3 minutes. A simple "nearest driver" rule would pick the first. A dispatch system that estimates the time of arrival picks the second.

When many requests arrive at once, a good system does not serve them one by one. It looks at all the waiting riders and all the free drivers together, and chooses the set of matches that gives the lowest total waiting time. This is called batching.

The second job is prediction. The software uses past trips, the weather and events to forecast where requests will rise in the next few minutes. This is demand forecasting. It then shows drivers where the demand is, or raises the fare there with dynamic pricing, so that more drivers move into the area.

The quality of dispatch decides how long riders wait and how much drivers earn without driving empty. It is also what makes the network effect work.

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