Recent and validated data inputs support robust traffic simulation and model development that reflects current conditions. Get readily available multimodal inputs to ensure a reliable transportation system with minimal strain on resources and costs.
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Gauge the performance of your transportation system with models that represent true mobility patterns
Update base year models with recent travel behavioral data for All Vehicles and Truck mode
Access traffic volume and speed for all roads, any hour of the day to inform route choices
Get granular Metrics by road segment, county, block group, TAZ, and more
Many Cities and MPOs do not have access to regular traffic counts on low-activity corridors such as local roads. StreetLight is a next-generation data source, offering a more comprehensive traffic picture than we’ve ever had before. The applications are endless.
City of Edmonton, Canada
TRAVEL DEMAND MODELING
Fill traffic count gaps and validate travel demand models
The pandemic impacted the City of Edmonton’s typical active, annual traffic count program, leaving traffic data gaps for the city. StreetLight’s Metrics helped planners obtain historical and current data for analysis, providing a view of the entire mobility landscape.
READ CASE STUDY
No more outdated assumptions: Build better baseline models and travel demand simulations with recent trip inputs
TRIP ATTRIBUTES
Obtain traffic volume travel time, speed, trip length, origin and destination and more
TRAVELER ATTRIBUTES
Get inferred trip purpose, demographics, and household characteristics
MODE BASED INPUTS
Split the trips results by All Vehicles or Truck modes
GRANULAR VISUALIZATIONS
Predict routes with select link, 15-minute granularity, peak hour, and more
Develop solutions that will work now and in the future
Explore other transportation solutions
VIDEO
Analyzing Regional Transportation Plans with Big Data
Madison Area Transportation Planning Board applies StreetLight’s Metrics to various analyses, including environmental justice studies, bicycle and pedestrian analyses, origin-destination studies, and calibrating travel demand models.
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Developing Microsimulation Models and Measuring Bike and Pedestrian Demand
HNTB uses StreetLight for regional travel demand modeling in Cedar Rapids, Iowa; microsimulation modeling in Milwaukee; and measuring bike/pedestrian demand for MnDOT, saving time and costs to make data-based decisions.
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How Travel Demand Modeling Gets a Boost from On-Demand Traffic Data Analytics
Travel demand models are often complex and require data inputs from household surveys, land use data, counters, and ridership reports. Learn how Big Data can augment transportation models reducing the need to integrate various data sets and reflect recent and true mobility patterns - saving time and cost.
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Power your traffic simulation and travel demand models with robust trip data and inform creative ways to solve mobility challenges.
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