[{"data":1,"prerenderedAt":194},["ShallowReactive",2],{"blog-\u002Fblog\u002Ftraffic-influenced-routing-in-public-preview\u002F":3,"related-blog-\u002Fblog\u002Ftraffic-influenced-routing-in-public-preview\u002F":155},{"id":4,"title":5,"abstract":6,"author":6,"body":7,"description":138,"excerpt":6,"extension":139,"head":6,"image":6,"keywords":140,"meta":147,"modified":6,"navigation":148,"path":149,"proficiencyLevel":6,"published":150,"rawbody":151,"schemaOrg":6,"schemaType":6,"seo":152,"stem":153,"__hash__":154},"blog\u002Fblog\u002Ftraffic-influenced-routing-in-public-preview.md","Traffic-Influenced Routing Is Here (Public Preview)",null,{"type":8,"value":9,"toc":130},"minimark",[10,14,18,23,57,60,77,80,84,87,91,94,122],[11,12,5],"h1",{"id":13},"traffic-influenced-routing-is-here-public-preview",[15,16,17],"p",{},"Routing without traffic data works for a lot of use cases.\nBut dispatch systems need ETAs that account for rush hour,\nride-hailing platforms need accurate pickup times,\nand telematics pipelines need traffic context to reconstruct accurate travel times.\nFor these use cases,\nrouting and ETAs that only reflect the road network,\nwithout accounting for what's happening on it,\nfall short.",[19,20,22],"h2",{"id":21},"available-today","Available Today",[15,24,25,26,34,35,34,40,34,45,50,51,56],{},"Starting today,\nStadia Maps customers on Standard and Professional plans can use traffic-influenced routing,\na public preview that brings live and historical traffic data into route calculations across\n",[27,28,33],"a",{"href":29,"rel":30,"target":32},"https:\u002F\u002Fdocs.stadiamaps.com\u002Frouting\u002Fstandard-routing\u002F",[31],"external","_blank","standard routing",",\n",[27,36,39],{"href":37,"rel":38,"target":32},"https:\u002F\u002Fdocs.stadiamaps.com\u002Frouting\u002Foptimized-routing\u002F",[31],"optimized routing",[27,41,44],{"href":42,"rel":43,"target":32},"https:\u002F\u002Fdocs.stadiamaps.com\u002Frouting\u002Fmap-matching\u002F",[31],"map matching",[27,46,49],{"href":47,"rel":48,"target":32},"https:\u002F\u002Fdocs.stadiamaps.com\u002Frouting\u002Fisochrones\u002F",[31],"isochrones",",\nand ",[27,52,55],{"href":53,"rel":54,"target":32},"https:\u002F\u002Fdocs.stadiamaps.com\u002Frouting\u002Ftime-distance-matrix\u002F",[31],"time\u002Fdistance matrices",".",[15,58,59],{},"The traffic data comes from TomTom and covers 80+ countries at launch,\nlayered onto the same OSM-based road network you already use.\nYou get two tiers to choose from,\nand you can pick per request,\nso you can use both in the same app:",[61,62,63,71],"ul",{},[64,65,66,70],"li",{},[67,68,69],"strong",{},"Adaptive"," balances accuracy and credit cost.\nA good fit for general routing, isochrones, and map matching.",[64,72,73,76],{},[67,74,75],{},"Premium"," combines real-time conditions with predictive data for the highest accuracy.\nIdeal where precise ETAs matter,\nlike live fleet routing and matrix requests.",[15,78,79],{},"Both tiers work across auto, bus, taxi, and truck profiles.\nAnd because this is Stadia Maps,\nyou can still tune all the same profile parameters you're used to.\nTraffic-influenced routing builds on the full Stadia Maps routing stack you already know:\nnot a locked-down replacement,\nand without the proprietary detour.",[19,81,83],{"id":82},"pricing-that-scales-with-you-not-against-you","Pricing That Scales With You, Not Against You",[15,85,86],{},"We built this the way we build everything:\nwith fair, transparent pricing and no gotchas.\nYou pick the routing profile and traffic tier per request,\nuse your existing credits with no surprise minimums,\nand upgrade with a single profile parameter change.\nYou can finally use traffic-influenced routing with no contract renegotiation,\nno new SDK,\nand no mandatory user tracking;\nyour users' privacy is still the default.",[19,88,90],{"id":89},"get-started","Get Started",[15,92,93],{},"Traffic-influenced routing is available now in public preview.",[61,95,96,105,114],{},[64,97,98,99,104],{},"See the ",[27,100,103],{"href":101,"rel":102,"target":32},"https:\u002F\u002Fstadiamaps.com\u002Fproducts\u002Frouting-navigation\u002Ftraffic-influenced-routing\u002F",[31],"Product page"," for an overview",[64,106,107,108,113],{},"Read the ",[27,109,112],{"href":110,"rel":111,"target":32},"https:\u002F\u002Fdocs.stadiamaps.com\u002Frouting\u002Fstandard-routing\u002F#traffic-influenced-profiles",[31],"Routing docs"," for profile details",[64,115,116,117],{},"Get started with the ",[27,118,121],{"href":119,"rel":120,"target":32},"https:\u002F\u002Fdocs.stadiamaps.com\u002Fguides\u002Fgetting-the-best-routes-with-valhalla-turn-by-turn-directions-apis\u002F#traffic-influenced-routing",[31],"Integration guide",[15,123,124,125,129],{},"Already on a Standard or Professional plan?\nYou can start using it right now.\nOn a different plan?\n",[27,126,128],{"href":127},"mailto:support@stadiamaps.com?subject=Traffic-Influenced%20Routing%20Trial","Reach out"," and we can set you up with a trial.",{"title":131,"searchDepth":132,"depth":132,"links":133},"",4,[134,136,137],{"id":21,"depth":135,"text":22},2,{"id":82,"depth":135,"text":83},{"id":89,"depth":135,"text":90},"Traffic-influenced routing is now available in public preview, bringing live and historical traffic data to standard routing, optimized routing, map matching, isochrones, and time\u002Fdistance matrices.","md",[141,142,143,144,145,146],"Traffic-Influenced Routing","Real-Time Traffic","Route Optimization","Fleet Routing","ETA Accuracy","Public Preview",{},true,"\u002Fblog\u002Ftraffic-influenced-routing-in-public-preview","2026-04-14","---\ndescription: >-\n  Traffic-influenced routing is now available in public preview,\n  bringing live and historical traffic data to standard routing,\n  optimized routing, map matching, isochrones, and time\u002Fdistance matrices.\npublished: 2026-04-14\nkeywords:\n  - Traffic-Influenced Routing\n  - Real-Time Traffic\n  - Route Optimization\n  - Fleet Routing\n  - ETA Accuracy\n  - Public Preview\n---\n\n# Traffic-Influenced Routing Is Here (Public Preview)\n\nRouting without traffic data works for a lot of use cases.\nBut dispatch systems need ETAs that account for rush hour,\nride-hailing platforms need accurate pickup times,\nand telematics pipelines need traffic context to reconstruct accurate travel times.\nFor these use cases, \nrouting and ETAs that only reflect the road network,\nwithout accounting for what's happening on it,\nfall short.\n\n## Available Today\n\nStarting today,\nStadia Maps customers on Standard and Professional plans can use traffic-influenced routing,\na public preview that brings live and historical traffic data into route calculations across\n[standard routing](https:\u002F\u002Fdocs.stadiamaps.com\u002Frouting\u002Fstandard-routing\u002F),\n[optimized routing](https:\u002F\u002Fdocs.stadiamaps.com\u002Frouting\u002Foptimized-routing\u002F),\n[map matching](https:\u002F\u002Fdocs.stadiamaps.com\u002Frouting\u002Fmap-matching\u002F),\n[isochrones](https:\u002F\u002Fdocs.stadiamaps.com\u002Frouting\u002Fisochrones\u002F),\nand [time\u002Fdistance matrices](https:\u002F\u002Fdocs.stadiamaps.com\u002Frouting\u002Ftime-distance-matrix\u002F).\n\nThe traffic data comes from TomTom and covers 80+ countries at launch,\nlayered onto the same OSM-based road network you already use.\nYou get two tiers to choose from,\nand you can pick per request,\nso you can use both in the same app:\n\n- **Adaptive** balances accuracy and credit cost.\n  A good fit for general routing, isochrones, and map matching.\n- **Premium** combines real-time conditions with predictive data for the highest accuracy.\n  Ideal where precise ETAs matter,\n  like live fleet routing and matrix requests.\n\nBoth tiers work across auto, bus, taxi, and truck profiles.\nAnd because this is Stadia Maps,\nyou can still tune all the same profile parameters you're used to.\nTraffic-influenced routing builds on the full Stadia Maps routing stack you already know:\nnot a locked-down replacement,\nand without the proprietary detour.\n\n## Pricing That Scales With You, Not Against You\n\nWe built this the way we build everything:\nwith fair, transparent pricing and no gotchas.\nYou pick the routing profile and traffic tier per request,\nuse your existing credits with no surprise minimums,\nand upgrade with a single profile parameter change.\nYou can finally use traffic-influenced routing with no contract renegotiation,\nno new SDK,\nand no mandatory user tracking;\nyour users' privacy is still the default.\n\n## Get Started\n\nTraffic-influenced routing is available now in public preview.\n \n- See the [Product page](https:\u002F\u002Fstadiamaps.com\u002Fproducts\u002Frouting-navigation\u002Ftraffic-influenced-routing\u002F) for an overview\n- Read the [Routing docs](https:\u002F\u002Fdocs.stadiamaps.com\u002Frouting\u002Fstandard-routing\u002F#traffic-influenced-profiles) for profile details\n- Get started with the [Integration guide](https:\u002F\u002Fdocs.stadiamaps.com\u002Fguides\u002Fgetting-the-best-routes-with-valhalla-turn-by-turn-directions-apis\u002F#traffic-influenced-routing)\n \nAlready on a Standard or Professional plan?\nYou can start using it right now.\nOn a different plan?\n[Reach out](mailto:support@stadiamaps.com?subject=Traffic-Influenced%20Routing%20Trial) and we can set you up with a trial.",{"title":5,"description":138},"blog\u002Ftraffic-influenced-routing-in-public-preview","8lqNk71y8ioiK4madSH5qMHhMAS2FyPN7Bwbyg7B1pA",[156,170,182],{"title":157,"description":158,"path":159,"published":160,"keywords":161,"rawbody":169},"Why Basic OpenStreetMap Routing Needs Real-Time Traffic","OpenStreetMap is a world-class road network, but without real-time traffic it's a static dataset. Here's why algorithmic ETAs fall apart in production logistics and how Stadia Maps closes the gap with TomTom-powered routing.","\u002Fblog\u002Fwhy-osm-routing-needs-real-time-traffic","2026-05-12",[162,163,164,165,166,167,168],"Routing","Navigation","OpenStreetMap","Traffic Data","Matrix Routing","Logistics","TomTom","---\ndescription: >-\n  OpenStreetMap is a world-class road network, but without real-time traffic\n  it's a static dataset. Here's why algorithmic ETAs fall apart in production\n  logistics and how Stadia Maps closes the gap with TomTom-powered routing.\nexcerpt: >-\n  OpenStreetMap is great geography, but without real-time traffic it falls\n  short on ETAs. Stadia Maps closes the gap with TomTom-powered routing.\npublished: \"2026-05-12\"\nkeywords:\n  - Routing\n  - Navigation\n  - OpenStreetMap\n  - Traffic Data\n  - Matrix Routing\n  - Logistics\n  - TomTom\nauthor:\n  name: \"Ian Wagner\"\n  jobTitle: \"Founder & President \u002F COO\"\n  sameAs:\n    - \"https:\u002F\u002Fwww.linkedin.com\u002Fin\u002Fian-w-wagner\u002F\"\n---\n\n# Why Basic OpenStreetMap Routing Needs Real-Time Traffic\n\n> OpenStreetMap (OSM) provides a world-class geographic foundation, but it remains a static dataset. Without real-time traffic integration, routing engines must rely on algorithmic proxies—like road class and legal speed limits—which often lead to unreliable ETAs and logistics bottlenecks.\n\n## The Problem\n\n[OpenStreetMap (OSM)](https:\u002F\u002Fwww.openstreetmap.org\u002Fabout) is one of the world's leading road maps, but a persistent gap remains between fixed geographic data and a [live navigation experience](\u002Fproducts\u002Frouting-navigation\u002F). Without dedicated traffic data, Estimated Times of Arrival (ETAs) are essentially educated guesses. While OSM is excellent at mapping the world's road network, a static dataset cannot capture the actual driving conditions at this exact moment. In enterprise-grade logistics, the lack of live data is often the first significant technical hurdle.\n\n## The Limits of Algorithmic Guesswork\n\nIn the absence of real-time data, a routing engine must estimate travel speeds based on tags and a few common proxies:\n\n- **Road Class:** Assuming a motorway is always faster than a residential street.\n- **Tagged Speed Limits:** Using the legal maximum as the baseline (when the tag even exists).\n- **Network Density:** Adjusting for urban vs. rural environments.\n- **Time of Day:** Using low-granularity buckets like \"daytime\" and \"nighttime.\"\n\nReal-world data show wild variances compared to these static estimates. Road class is a blunt instrument for predicting speed. Missing speed limit tags in open datasets force routing engines to rely on broad averages, resulting in unreliable ETAs and logistics delays. Rule-based algorithms are also notoriously bad at predicting choke points because open datasets don't account for traffic light timings, congestion near specific exits, or the \"invisible\" friction of a busy intersection.\n\n## The Stadia Maps Difference\n\nTo move from guesswork to precision, we integrated [TomTom's global traffic data](https:\u002F\u002Fwww.tomtom.com\u002Fproducts\u002Ftraffic-apis\u002F) directly into the [Stadia Maps routing engine](https:\u002F\u002Fdocs.stadiamaps.com\u002Frouting\u002F). High-resolution historical profiles and live feeds allow for accurate, real-time routing. We provide this through three key technical pillars:\n\n1. **Global Coverage:** Access to consistent data across more countries than almost any other vendor.\n2. **Rapid Updates:** A traffic latency of approximately two minutes allows our API to suggest alternate routes almost as soon as a wreck occurs.\n3. **Historical Profiles:** Deep granularity forms the backbone of predictive routing. High-resolution historical data enables accurate, time-dependent routing in advance, allowing you to plan a route for Tuesday at 8:00 AM based on what might happen on Tuesdays at 8:00 AM.\n\n## Fleet Intelligence at Scale\n\nFor dispatch, optimization, and fleet operations, [matrix routing](https:\u002F\u002Fdocs.stadiamaps.com\u002Frouting\u002Ftime-distance-matrix\u002F) (calculating the time and distance between many origins and destinations) is the engine's most critical function.\n\nThe Stadia Maps infrastructure supports matrix requests that are significantly larger than most competitors allow on standard plans. By integrating traffic data directly into these large-scale requests, we eliminate the need for developers to split requests into smaller chunks, reducing unnecessary complexity and latency.\n\nDevelopers maintain full agency over their implementation. We provide the fastest route based on live conditions, but the frequency of re-routing remains entirely in your control. Choice of revalidation frequency puts you in charge of the trade-off between real-time accuracy and [scaling costs](\u002Fpricing\u002F), ensuring your bills remain as predictable as your ETAs.\n\n---\n\n[Create a free account](https:\u002F\u002Fclient.stadiamaps.com\u002Fsignup\u002F) to start building with real-time traffic and high-performance routing today. Our [documentation](https:\u002F\u002Fdocs.stadiamaps.com\u002Frouting\u002F) provides everything you need to integrate TomTom-powered precision into your existing OSM workflow.\n",{"title":171,"description":172,"path":173,"published":174,"keywords":175,"rawbody":181},"2026 Satellite Imagery Update: 37 Million km² at 30cm Resolution","The 2026 Alidade Satellite update expands 30cm-resolution coverage to 37 million km², adds seamless country-wide mosaics for Japan, Nigeria, Mexico, the UAE, and Eastern South Africa, and refreshes our global 1.5m baseline from the latest SPOT data.","\u002Fblog\u002F2026-satellite-imagery-update","2026-04-27",[176,177,178,179,180],"Satellite Imagery","Aerial Photography","Map Update","High Resolution","Alidade Satellite","---\ndescription: >-\n  The 2026 Alidade Satellite update expands 30cm-resolution coverage to 37 million km²,\n  adds seamless country-wide mosaics for Japan, Nigeria, Mexico, the UAE, and Eastern\n  South Africa, and refreshes our global 1.5m baseline from the latest SPOT data.\npublished: 2026-04-27\nkeywords:\n  - Satellite Imagery\n  - Aerial Photography\n  - Map Update\n  - High Resolution\n  - Alidade Satellite\n---\n\n# 2026 Satellite Imagery Update: 37 Million km² at 30cm Resolution\n\nIf you've built anything on top of satellite imagery, you know the pain of inconsistent resolution. You zoom into one region and get crisp rooftops. Pan over to the next and it's a blurry patchwork from three years ago. That inconsistency isn't just cosmetic: it erodes trust in whatever you're building on top of it.\n\nWe regularly refresh our [Alidade Satellite](https:\u002F\u002Fstadiamaps.com\u002Fproducts\u002Fmaps\u002Fmap-styles\u002Fsatellite-imagery\u002F) imagery as new high-resolution data becomes available from Airbus. This update is one of our most significant, expanding both the depth and freshness of our coverage.\n\n::cross-platform-map{id=\"map\" style=\"height: 400px;\"}\n---\ncenter: [139.6934, 35.6857]\nscroll-zoom: true\nzoom: 16.5\ntheme: alidade_satellite\nuse-theme-switcher: false\nuse-search: true\n---\n::\n\n## 30cm Coverage, Scaled\n\nWe now offer 37 million km² of 30cm-resolution satellite imagery, enough detail to distinguish individual vehicles, building footprints, and infrastructure at high zoom levels. For applications like urban planning tools, insurance assessments, or logistics platforms, this is the difference between useful and decorative.\n\nThis release also adds seamless 30cm country-wide mosaics for Japan, Nigeria, Mexico, the UAE, and Eastern South Africa. \"Seamless\" matters here: no visible tile boundaries, no abrupt shifts in color or season. Just consistent, high-resolution coverage across the entire country.\n\n## A Fresher Global Baseline\n\nBeyond the 30cm expansion, we've completed a full refresh of our 1.5m-resolution dataset covering the Earth's landmasses, derived from the latest SPOT Global layer. Even at lower zoom levels, you're working with current data rather than imagery that's aging out.\n\nFreshness matters as much as resolution. Across our entire dataset, the area-weighted average age is roughly 1.6 years. Nearly two-thirds of our coverage is less than a year old, and only 7% is older than three years. That share continues to shrink with each refresh.\n\nCombined with our [2025 satellite imagery refresh](https:\u002F\u002Fstadiamaps.com\u002Fblog\u002F2025-satellite-imagery-refresh\u002F), every pixel in our dataset is still 1.5m or better, with 37 million km² at 30cm and another 7 million km² at 50cm.\n\n## What This Means for Your Stack\n\nIf you're using Alidade Satellite, these updates are already live. No API changes, no migration. The same tile endpoints now serve fresher, sharper data. Integration works the same way it always has via MapLibre, Leaflet, OpenLayers, or any other mapping library that supports raster tiles.\n\nWe don't track or profile your end users. The imagery is delivered directly, with no behavioral tracking layer between your application and the tiles.\n\n## Try It\n\nThe updated satellite imagery is available now for all Stadia Maps customers. If you're new, [create a free account](https:\u002F\u002Fclient.stadiamaps.com\u002Fsignup\u002F) and see the difference at zoom level 18.\n",{"title":183,"description":184,"path":185,"published":174,"keywords":186,"rawbody":193},"75 Million More Addresses: Expanding Geocoding Precision","Our largest geocoding dataset expansion yet: 75 million new addresses from OpenAddresses, 3 million new POIs from Foursquare OS Places, smarter intent recognition, and new structured address fields (house_number, street, unit) on the v1 search API.","\u002Fblog\u002F75-million-more-addresses-geocoding-precision",[187,188,189,190,191,192],"Geocoding","Addresses","OpenAddresses","Foursquare OS Places","Structured Search","Points of Interest","---\ndescription: >-\n  Our largest geocoding dataset expansion yet: 75 million new addresses from OpenAddresses,\n  3 million new POIs from Foursquare OS Places, smarter intent recognition, and new\n  structured address fields (house_number, street, unit) on the v1 search API.\npublished: 2026-04-27\nkeywords:\n  - Geocoding\n  - Addresses\n  - OpenAddresses\n  - Foursquare OS Places\n  - Structured Search\n  - Points of Interest\n---\n\n# 75 Million More Addresses: Expanding Geocoding Precision\n\nInaccurate geocoding breaks the user experience. If your query returns a street-level guess instead of a rooftop coordinate, a user might be on the right street but the wrong block, or a delivery driver gets routed to an approximate centroid instead of a front door. The coordinates are \"close enough\" until they aren't, and your application takes the blame.\n\nWe continuously update our geocoding dataset as new address and POI data becomes available. This release is our largest expansion yet: 75 million new addresses, 3 million new points of interest, improved intent recognition, and a new way to query with structured address fields.\n\n## Rooftop-Level Accuracy at Scale\n\nThe bulk of this expansion comes from OpenAddresses, one of the largest open datasets of address-level coordinates. These aren't interpolated guesses along a road segment. They're rooftop-level points tied to individual parcels, which matters for any application that depends on precise placement: routing, last-mile logistics, property lookup.\n\nThe gains aren't spread evenly. France and the US lead with roughly 25 million new addresses each, followed by Germany with 3 million and notable expansions across Brazil, Australia, and Mexico. If you've been hitting street-level fallbacks in these regions, you should see noticeably better results.\n\n## Fresher Points of Interest\n\nPOI data goes stale quickly. A restaurant opens, a shop closes, a business moves across the street, and suddenly your search results are sending users to the wrong place. We've added 3 million POIs from Foursquare OS Places, bringing our dataset more in line with what's actually on the ground. Better coverage for the kinds of searches your users actually run: finding a specific restaurant, locating the nearest pharmacy, or navigating to a business that opened last month.\n\n## Smarter Search, Fewer Misses\n\nBeyond raw data, we've improved how our [\u002Fsearch APIs](https:\u002F\u002Fstadiamaps.com\u002Fproducts\u002Fgeocoding-search\u002Fgeocoding\u002F) interpret what users actually mean. The changes focus on intent recognition: better handling of queries for larger geographic areas, complex or compound place names, and cases where the most obvious textual match isn't the right result.\n\nYour users should find more of what they're looking for on the first try.\n\n## Structured Address Input, Now on v1\n\nFor developers working with structured address data, this release adds `house_number`, `street`, and `unit` as first-class fields on the geocoding API. Previously, structured queries supported country, region, and postal code, but the address itself arrived as a single text field that we had to parse before running a match.\n\nIf your dataset is already structured that way, you can now pass it through directly. This is common for shipping, CRM, and property data. Queries with the new fields skip the parsing step entirely, which typically means better match quality and faster responses.\n\nThe free-text `address` field isn't going anywhere. If you only have a single string, we'll still parse it for you. The new fields are available on v1 today. Adopt them at your own pace.\n\n## No Tracking Required\n\nA common assumption in the industry is that better geocoding requires more user data: search history, device location, behavioral signals. We don't work that way. These improvements come from better source data and smarter algorithms, not from profiling your end users. Your users' queries are yours, not ours.\n\nAs with everything we build, these updates are available through standard APIs and SDKs, including MapLibre and Leaflet. Technical precision, fair pricing, and privacy are baked in from the start.\n\n## Get Started\n\nThe expanded dataset, structured address fields, and search improvements are live now for all Stadia Maps customers. New here? [Create a free account](https:\u002F\u002Fclient.stadiamaps.com\u002Fsignup\u002F) and start geocoding.\n",1778676026603]