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The Las Vegas Spaghetti Bowl is the downtown interchange where I-15 and US-95 meet, with connections to US-93 and I-515. A useful Mapbox model should show that network as a layered 3D explanation: roadway decks and ramps at their approximate elevations, surrounding buildings and terrain for context, and annotations that explain movements and historical operating conditions. It is not automatically a traffic simulation. Unless you calibrate it with validated demand, speed, and crash data, the finished scene is a geographic visualization.
This guide lays out a defensible workflow, from establishing the map footprint to choosing between extruded polygons and GLTF models, while keeping historical capacity and safety figures clearly separated from current conditions.
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Where is the Las Vegas Spaghetti Bowl?
The Spaghetti Bowl is in downtown Las Vegas at the I-15/US-95 system interchange. The Nevada State Library map identifies I-15, US-95, US-93, I-515, local streets, ramps, and numbered points around the interchange. Those route labels and the documented interchange footprint should be your geographic reference when you start a 3D scene.
US-95 runs through the interchange with I-15, while US-93 and I-515 connect into the same complex. Local streets and closely spaced ramps make it a system interchange rather than a single overpass. In a model, preserve the route designations from the source map and display them in project metadata so a reader can tell which roadway each deck represents.
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Why is it called the “Spaghetti Bowl”?
The exact origin of the nickname has not been established. A Review-Journal account reported that Nevada Department of Transportation spokesman Justin Hopkins could not identify a confirmed person who coined it; the name appears to describe the visual tangle of ramps, loops, and crossing roadways. Treat that as an unresolved nickname history, not as a story with a verified inventor.
What changed when the interchange was rebuilt?
The major reconstruction opened in March 2000 after a $99 million project. An archived Nevada Department of Transportation account described the old facility as handling about 330,000 vehicles per day and said the improved interchange could accommodate 500,000 vehicles per day. Those are historical planning-era figures associated with the 1999 report, not a live count for 2026.
The agency’s current Project NEON information places about 300,000 vehicles daily on the I-15 corridor and forecasts 25 percent growth by 2050. Project NEON widened 3.7 miles of I-15 between Sahara Avenue and the Spaghetti Bowl. The corridor figure covers the stated Project NEON segment context; it should not be silently substituted for a current count at every ramp or for the whole interchange.
| Figure | What it describes | Date or qualification |
|---|---|---|
| 330,000 vehicles per day | Traffic handled by the old facility | NDOT historical report, 1999 |
| 500,000 vehicles per day | Capacity cited for the improved interchange | NDOT historical report, 1999 |
| $99 million | Cost of the reconstruction that opened in March 2000 | NDOT historical report, 1999 project account |
| 300,000 vehicles daily | Traffic described for the I-15 corridor in Project NEON material | Current NDOT project page; corridor context |
| 25% growth by 2050 | Forecast increase for that corridor | NDOT Project NEON forecast |
| More than 200 truck-involved collisions | Collisions at the interchange used in goods-movement planning | RTC Southern Nevada plan, 2008–2012 historical period |
How do I establish a reliable 3D map footprint?
Start with the documented interchange map, not with an arbitrary camera view. The goal is to create a coordinate frame that another person can inspect and reproduce.
- Record the reference. Put the Nevada State Library map name, route designations, and source date in a project README or data catalog. Keep the same information in the figure caption.
- Define the area of interest. Include enough surrounding streets and buildings to explain where ramps enter and leave the interchange, but avoid loading an entire metropolitan area when the study concerns the downtown system.
- Separate geographic data from styling. Keep roadway centerlines, deck footprints, labels, and annotations in data sources. Let Mapbox style layers control color, opacity, extrusion height, and draw order.
- Check alignment before adding detail. Compare route shields, local street intersections, and ramp endpoints against the reference map. A beautifully lit model with a shifted coordinate frame is still wrong.
Do not imply survey-level accuracy unless you have survey or engineering geometry. For an explanatory scene, label the result as approximate where deck elevations, retaining walls, or ramp widths were inferred.
How can Mapbox show surrounding buildings in 3D?
Mapbox Standard supplies 3D buildings and landmark models. The official building example uses addLayer with a fill-extrusion layer; heights come from the Streets vector tileset. This is an efficient context layer because the buildings are generated from mapped footprints and height attributes rather than individually modeled assets.
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Add the building layer beneath the interchange’s explanatory overlays and choose a neutral color. Context should establish scale and orientation without competing with the roadway decks. If the Standard style already contains building content, insert your study layers using the documented Standard-style insertion mechanism so later style updates do not unexpectedly cover them.
How should roadway surfaces, ramps, and bridges be represented?
Use a combination of 2D plan data and explicit vertical elements. A single thick line cannot explain which deck passes over another, so split the interchange into logical roadway surfaces.
Centerlines and deck polygons
Use line layers for route centerlines and narrow ramps when plan-view clarity matters. Use filled polygons for freeway decks, shoulders, gore areas, and broad pavement surfaces. Custom GeoJSON or vector sources let you control each feature’s identity, color, and height-related attributes.
A conceptual extruded deck layer can look like this:
map.addLayer({
id: 'interchange-decks',
type: 'fill-extrusion',
source: 'interchange-geojson',
paint: {
'fill-extrusion-color': ['get', 'deck_color'],
'fill-extrusion-height': ['get', 'top_elevation'],
'fill-extrusion-base': ['get', 'base_elevation'],
'fill-extrusion-opacity': 0.9
}
});The property names in this example are part of your own GeoJSON schema. Populate them consistently, document the vertical datum or assumed reference, and do not treat a visual height as a measured engineering elevation.
GLTF assets for structural detail
Use separate GLTF assets when a bridge, retaining structure, sign gantry, or distinctive ramp geometry needs more realistic shape than a polygon extrusion can provide. Mapbox’s style specification describes a model layer for 3D buildings and individual or instanced models, including GLTF model sources.
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Native model layers are usually simpler when you already have a correctly georeferenced GLTF asset. A custom three.js style layer is appropriate when you need your own rendering logic, material handling, or animation. It also creates more coordinate and performance work, so do not use it merely to replace a straightforward extrusion.
How do I make vertical separation readable?
Use geometry, color, and camera controls together. Give each deck a plausible base and top elevation, then use a restrained palette that distinguishes the major routes without turning the scene into a rainbow. Add thin edge or outline treatments where two decks are close in plan view.
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- Keep the camera pitched enough to reveal overpasses, but test a lower pitch to ensure the route remains understandable in plan.
- Use labels or callouts for movements that disappear behind higher decks.
- Give bridges and ramps separate feature identifiers so you can hide or isolate them during review.
- Show retaining walls or embankments only when they clarify why a deck sits at a particular level.
Terrain and lighting improve legibility, but both can mislead. Camera pitch, terrain exaggeration, and cast shadows can make a ramp appear steeper or more separated than it is. Record any vertical exaggeration in the figure caption and keep the same setting when comparing views.
What explanatory overlays belong in the scene?
Annotations should explain how the interchange functions, not suggest that the rendering itself measured traffic. Add route shields, directional arrows for major ramp movements, labels for weaving areas, and markers for freight-relevant paths.
The Regional Transportation Commission of Southern Nevada’s goods-movement plan reported more than 200 truck-involved collisions at the interchange during 2008–2012. The same planning material reported peak-hour speeds more than 20 mph below the posted 65 mph on two legs. Present both as historical planning evidence: place the period and source beside the annotation, and do not call either number a current crash rate or live speed reading.
A useful visual treatment is a small historical-context panel linked to the affected legs, rather than red coloring every roadway. That keeps the collision and speed findings tied to their documented locations and avoids implying that the model predicts risk.
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Which 3D representation should I choose?
Choose the least complicated representation that answers your communication question. The following comparison separates geometric realism from explanatory reliability.
| Representation | Geometric fidelity | Vertical separation and weaving | Source provenance | Browser performance | Best use |
|---|---|---|---|---|---|
| Lines and flat fills | Low for elevation | Weak when decks overlap | Easy to inspect in GeoJSON or vector data | Usually light | Route orientation and early data checks |
| Extruded deck polygons | Moderate, depending on elevation attributes | Clear for most overpasses and ramps | Transparent if each polygon has documented attributes | Generally efficient | Primary explanatory interchange model |
| Native GLTF model layer | High for prepared assets | Strong for bridge structure and distinctive forms | Depends on asset provenance and georeferencing | Heavier than simple polygons | Detailed structures already available as GLTF |
| Custom three.js layer | Potentially highest | Can express custom geometry and behavior | Requires careful coordinate and asset documentation | Most demanding | Specialized rendering or interaction requirements |
A simple extruded network is easier to explain and audit. GLTF and custom layers can show bridge structure more realistically, but they require asset preparation, coordinate checking, and a stronger performance budget.
Is a Mapbox interchange model a traffic simulation?
No. A layered 3D scene shows spatial relationships; it does not establish vehicle demand, lane-changing behavior, travel times, queue formation, or crash probability. The historical counts, capacity statements, collision totals, and speed differences are context that you can annotate, not outputs generated by the rendering.
To claim simulation, you would need a separate calibrated model with defined demand inputs, network rules, time periods, validation data, and documented error measures. Keep that analytical model distinct from the Mapbox presentation layer. If you later connect simulated results, label the scenario, calibration period, and assumptions directly in the interface.
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How do I keep the model reproducible and honest?
Create a small data dictionary for every feature class. At minimum, record route name, feature type, source, source date, assumed elevation method, and whether the geometry is measured, digitized, or illustrative.
- Store the source date with traffic and safety annotations.
- Keep the 1999 NDOT capacity figures separate from the current Project NEON corridor information.
- Mark the 2008–2012 collision total as historical and truck-involved.
- Document camera pitch, terrain settings, light direction, and any vertical exaggeration used in published images.
- Version the GeoJSON, vector tiles, GLTF files, and style configuration together.
Before publication, inspect the scene from both a pitched 3D view and a near-plan view. Confirm that labels do not hide ramp junctions, that deck ordering is consistent, and that every safety or traffic claim has its period and geographic scope visible.
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What commonly goes wrong, and how can I fix it?
Ramps appear to float
This usually means the deck’s base elevation does not meet the adjacent surface or terrain. Correct the base/top relationship, check the vertical reference used by every feature, and reduce terrain exaggeration before changing the geometry.
Overpasses merge into one surface
Separate the overlapping polygons and assign distinct elevations. If the decks are only a few pixels apart at the chosen zoom, adjust the camera or add a subtle edge treatment rather than exaggerating the real separation without documenting it.
Buildings obscure the interchange
Lower building opacity or height emphasis, move the building layer beneath the roadway explanation, and use a clip or study-area extent. Context should orient the viewer, not bury the infrastructure.
The browser becomes slow
Reduce polygon detail outside the interchange, simplify GLTF meshes, avoid loading duplicate assets, and prefer an extrusion for repetitive decks. Test on the least powerful device you expect readers to use; a desktop workstation can hide a poor mobile experience.
Readers mistake historical statistics for live conditions
Put the year range or report year in the same label as every number. Use wording such as “NDOT historical report, 1999” or “RTC plan, 2008–2012,” and reserve present-tense language for data that has actually been updated.
Frequently Asked Questions
Can I animate vehicles on the 3D interchange map?
You can animate illustrative markers or a separately modeled flow, but motion alone does not validate traffic behavior. Label any animation as a scenario and identify its demand, time period, and assumptions rather than presenting it as observed traffic.
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GeoJSON is a practical starting point for centerlines, deck polygons, labels, and annotations because each feature can carry route and elevation attributes. Convert to vector tiles when the dataset becomes large enough that browser download and rendering time are a problem.
Do I need surveyed bridge elevations to publish the visualization?
Not for an explanatory map, provided you clearly identify inferred or approximate elevations. Survey-grade claims require an appropriate engineering source and a documented vertical reference; do not imply that visual separation proves construction dimensions.
How often should the Las Vegas model be updated?
Review route designations, construction status, traffic counts, and Mapbox style or API behavior whenever you republish. Historical figures can remain useful, but current conditions should carry a new observation date and source instead of inheriting an old label.
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