Good news for all Google Maps users. We could’ve only imagined something that would let us know about the crowd in the bus or vehicle we are going to ride. Now we are going to get an app that would instantly tell us about the crowdedness in our public transport.It is announced that this new feature will be rolled out in about 200 cities around the globe. Further expansion in other cities will be carried out later. However, the list of the 200 cities is yet not revealed. These new features will take into account different mass transits like buses, trains, subways, and metros. Android and iOS users will be able to use this feature.
Google Maps launching its new featureGoogle is rolling out its new feature very soon that will let its users know about the crowd in the bus or train they are going to ride. Recently Google announced that its Maps application is now ready to launch its new feature very soon. The application will report about the crowdedness in public transits. Until now we could only know about the crowdedness in the public transport at the time we got into it. But now with the introduction of this new feature, we can know about the crowdedness of the transport at our homes before we head out to commute.
Another feature that will make it more useful than beforeBesides this, another feature is also being rolled out by the company that will report its users about the traffic delay for buses in many cities. This feature previously did not have any live updates. It will let you know how long will it take for your bus to arrive and other details like delays etc. Google Maps will provide this information even when other local agencies fail to do so.
Google has been on it working for a long timeSome sources claim that Google has been working on this feature for quite a long time. Some stated that the company employees were spotted at different bus stations doing a survey or collecting data. The company also asked the commuters about their ride’s information. They asked questions about the vacant seats and also the level of the standing area in their ride. Later, all the collected data was assumed to develop models which can easily predict crowd on public transits at different times of the day.
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