compute_route

Compute a crash rate over an ordered sequence of interstate (route, milepost) segments. Available for route-capable regions: travis, ca_interstates, sw_interstates (check regions()).

HumanBaselines.compute_route(
    segment_ids: list[tuple[str, int]],
    selections: RouteSelections | dict | None = None,
    *,
    county: str | None = None,
    **filters,
) -> RouteComputeResult

segment_ids is an ordered list of (route_name, milepost) pairs. Route/depot modes count Class-8 combination trucks, so ego_vehicle defaults to ["combination"]. Filters work the same three ways as compute.

Example

hb.compute_route(
    segment_ids=[("I-35", 250), ("I-35", 251), ("I-35", 252)],
    ego_vehicle=["combination"],
    ci_method="fay_feuer",
)

Returns: RouteComputeResult

Field	Type	Description
N	float	Weighted crash count over all segments.
trip_miles	float	Sum of segment lengths.
rate	float	Incidents per million (combination-truck) miles.
rate_low / rate_high	float | None	95% CI bounds.
variance	float | None	Propagated Poisson variance.
segments	list[PerSegmentResult]	Per-milepost {route, milepost, count, vmt, length_mi}.

Multi-corridor trips

For ca_interstates / sw_interstates, segment_ids may span multiple interstates; the engine stitches them via a junction graph. Use the humanbaselines.com tool or the corridor segment lists to assemble valid sequences.