A computer-implemented method comprising: receiving first map data including information about a first drivable surface in a first geographic region and one or more traffic features associated with the first drivable surface, the one or more traffic features comprising one or more of a number of traffic lanes, a traffic lane type, lane geometry, or traffic control information; determining, based at least in part on the one or more traffic features, a plurality of first segments of the first drivable surface; determining, for a first segment of the plurality of first segments and based at least in part on the one or more traffic features, a plurality of first segment parameters, wherein the first segment comprises a road segment including a plurality of lanes ; receiving second map data associated with a second geographic region different from the first geographic region and navigable by an autonomous vehicle, the second map data comprising information about a plurality of second segments of a second drivable surface in the second geographic region; determining , based at least in part on the plurality of first segment parameters and the second map data, a similarity metric indicative of a similarity between the first segment and one or more of the plurality of second segments, wherein the determining the similarity metric is based at least in part on comparing a subset of the plurality of lanes with lane combinations in the second map data; determining , based at least in part on the similarity metric, that the autonomous vehicle can navigate the first segment, wherein the determining that the autonomous vehicle can navigate the first segment comprises determining that the autonomous vehicle can navigate a portion of the first segment comprising the subset of the plurality of lanes; and controlling the autonomous vehicle to navigate the first segment. receiving first map data including information about a first drivable surface in a first geographic region and one or more traffic features associated with the first drivable surface, the one or more traffic features comprising one or more of a number of traffic lanes, a traffic lane type, lane geometry, or traffic control information; determining, based at least in part on the one or more traffic features, a plurality of first segments of the first drivable surface; determining, for a first segment of the plurality of first segments and based at least in part on the one or more traffic features, a plurality of first segment parameters, wherein the first segment comprises a road segment including a plurality of lanes ; receiving second map data associated with a second geographic region different from the first geographic region and navigable by an autonomous vehicle, the second map data comprising information about a plurality of second segments of a second drivable surface in the second geographic region; determining , based at least in part on the plurality of first segment parameters and the second map data, a similarity metric indicative of a similarity between the first segment and one or more of the plurality of second segments, wherein the determining the similarity metric is based at least in part on comparing a subset of the plurality of lanes with lane combinations in the second map data; determining , based at least in part on the similarity metric, that the autonomous vehicle can navigate the first segment, wherein the determining that the autonomous vehicle can navigate the first segment comprises determining that the autonomous vehicle can navigate a portion of the first segment comprising the subset of the plurality of lanes; and controlling the autonomous vehicle to navigate the first segment. <EOS>