Whereas at a stop sign, if the intersection is backed up, you tend to stop, move forward about car length, stop again, move forward again, etc. If cars do stop at a traffic light, they will typically stay in one position for an extended period of time while waiting for the light to change. This shouldn't happen (very often) at stop signs.
Google maps traffic full#
If the intersection has a traffic light, it'll be green sometimes, so you will see significant numbers of cars going through at full speed without stopping. This example creates a map that uses a traffic layer to show real-time.
If you have the Google Maps app on your smartphone (or any other electronic device), you can access info on the current traffic conditions on any given road/highway. The motion of a car is different at an intersection with a stop sign than at a traffic light: Google has a special built-in feature called Google Traffic on its Maps app that shows traffic conditions in real-time on major roads in particular geographic locations. It offers satellite imagery, aerial photography, street maps, 360 interactive panoramic views of streets (Street View), real-time traffic conditions, and route. I could even imagine street lights can be inferred from the GPS / accelerometer data that the Google Maps mobile app uploads. I don't know if they have (or have added) the capability to detect street lights, but it definitely seems possible. When you turn on Location History, you may see a number of benefits across Google products and services, including personalized maps, recommendations based on places you’ve visited, help finding. "Stop signs are trivial, they're made to stick out," McClendon said. Those algorithms borrow methods from computer vision and machine learning to extract features like street numbers painted on curbs, the names of businesses and other points of interest, speed limits and other traffic signs. They already have the capability to use machine vision to automatically detect certain types of features in street view imagery. For example, one pattern may show that the 280 freeway in Northern California typically has vehicles traveling at a speed of 65mph between 6-7am, but only at 15-20mph in the late afternoon.
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It's possible they crowd-source some of it like that, but it's also possible they're doing a lot of it automatically. To predict what traffic will look like in the near future, Google Maps analyzes historical traffic patterns for roads over time.
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