Abstract: To provide navigation directions for a scenic route, a machine learning model is trained using (i) characteristics of road segments that have been assigned a scenic metric and (ii) the scenic metrics for the road segments. In response to a request for navigation directions, a set of candidate routes for navigating from the starting location to the destination location is identified. Then for each road segment within each candidate route, characteristics of the road segment are applied to the machine learning model to generate the scenic metric for the road segment. A route is then selected from the set of candidate routes based at least in part on the scenic metrics of the road segments within the route. A set of navigation directions is provided for presentation on a client device for navigating from the starting location to the destination location via the selected route.

Abstract: The present disclosure is directed towards systems and methods for receiving environmental data from device sensors. A computing system stores environmental data in an environmental feature database at the computing system for a plurality of geographic locations. The computing system receives, from one or more remote systems, data indicating one or more environmental features for a particular geographic location. The computing system accesses stored environmental data for the particular geographic location to determine whether the environmental features are included in the environmental feature database. In response to determining that the environmental features are included in the environmental feature database, the operations further comprise, updates a confidence value associated with the environmental features.

Abstract: To provide navigation directions for a scenic route, a machine learning model is trained using (i) characteristics of road segments that have been assigned a scenic metric and (ii) the scenic metrics for the road segments. In response to a request for navigation directions, a set of candidate routes for navigating from the starting location to the destination location is identified. Then for each road segment within each candidate route, characteristics of the road segment are applied to the machine learning model to generate the scenic metric for the road segment. A route is then selected from the set of candidate routes based at least in part on the scenic metrics of the road segments within the route. A set of navigation directions is provided for presentation on a client device for navigating from the starting location to the destination location via the selected route.