Detectable Design
Methodology

How route checks work

Detectable Design reads a planned GPX route in your browser, matches it to available road data, highlights intersections with crash history or other risk factors, and adds clothing color guidance where local street-scene profiles overlap the route.

Route guidance is directional. It is not a crash prediction or safety guarantee.
Route first The page starts from the route you plan to run or ride, not from a city selector.
Attention index Crossings are scored from road context, scene complexity, and nearby crash history.
Color guidance The route card returns two high-vis colors and two regular clothing colors to start with.

What happens to a GPX file

  • The GPX file is parsed locally in the browser.
  • The route is sampled into points at regular distance intervals.
  • Those points are matched to nearby road-network tiles.
  • Matched road segments provide road type and available safety features.
  • Nearby intersections are ranked and the top five are shown on the route card.

Signals used by the route check

  • Road class: local streets, arterials, highways, and active paths.
  • Intersection context: crossings, road complexity, and nearby route geometry.
  • Crash history: federal or local crash records where available.
  • Street-scene profiles: local backdrop and color guidance where imagery exists.
  • Season and light condition: season-specific profiles are used where available; otherwise the route uses all-year guidance.

How the attention index is built

The attention index is designed to make the route card easy to share: one route-level label plus a short list of places to notice. It intentionally avoids pretending to know the exact risk of a future trip.

Intersection score

Local comparison

Each matched crossing is compared with other crossings in the same local context. More complex crossings, or crossings near crash records, receive higher scores.

Route score

Average attention

The route score summarizes the crossings along the uploaded GPX file rather than ranking the whole city.

Route labels

Readable output

High, moderate, light, and easy attention labels are based on how the route compares with nearby intersections in the available dataset.

Top five points

Actionable scan

The route card limits the watch list to five intersections so the output stays usable before a run or ride.

How color guidance fits in

Color guidance is now a route output, not the main navigation model. When the route overlaps local street-scene profiles, the page weights those profiles by the matched route segments and recommends colors that separate from the local backdrop.

High-vis colors

The route card shows two high-vis colors to start with. These are still usually the strongest visibility choices when someone owns high-vis gear.

Regular clothing colors

The route card also shows two regular clothing colors for cases where someone is choosing from clothing they already own.

Colors to avoid

Avoid colors are the colors most likely to blend into the matched local backdrop profiles.

Fallback guidance

If the route has road coverage but not local street-scene profiles, the page uses general visibility guidance instead of pretending the local color model is complete.

Current limitations

Coverage varies by data source

Road coverage and local street-scene coverage are separate. A route can have road matching without local color profiles for every segment.

Crash data is historical

Crash records describe what has been recorded nearby. They do not predict what will happen on a specific trip.

Lighting is incomplete

Low-light guidance uses available route and scene data, but comprehensive streetlight coverage is not available everywhere yet.

Season is available where data supports it

Seasonal profiles are used where there is enough image metadata. Otherwise the route card uses all-year profiles.

Visibility research behind the color guidance

The route tool uses these studies to shape the color component of the recommendation. They support the general structure of the visibility model, not every constant in the implementation.

  1. Targoutzidis, A., et al. Selecting effective colors for high-visibility safety apparel. Safety Science, 2021. doi.org/10.1016/j.ssci.2020.104978
  2. Sayer, J., & Mefford, M. The effect of color contrast on daytime and nighttime conspicuity of roadworker vests. UMTRI, 2000. hdl.handle.net/2027.42/49418
  3. Sayer, J., & Buonarosa, M. The roles of garment design and scene complexity in the daytime conspicuity of high-visibility safety apparel. Journal of Safety Research, 2008. doi.org/10.1016/j.jsr.2007.12.004
  4. Wood, J., Tyrrell, R., et al. Limitations in Drivers' Ability to Recognize Pedestrians at Night. Human Factors, 2005. doi.org/10.1518/001872005774859980
  5. Babić, D., et al. Factors affecting pedestrian conspicuity at night: Analysis based on driver eye tracking. Safety Science, 2021. doi.org/10.1016/j.ssci.2021.105257

Bottom line

Detectable Design is an information tool for planning routes and choosing more visible clothing. It should be used alongside normal judgment, local conditions, lights, reflective details, and route planning.

Check a route