Use Case Walkthroughs

View end-to-end examples of how to apply Altitude modules to solve real-world planning problems. Each walkthrough is organized by scenario and includes contextual explanations and links to interactive demo videos.

Truck Stop Demand Analysis: End-to-End Walkthrough

This walkthrough shows how to use Altitude to assess truck parking demand along Illinois’ I-80 corridor. While focused on parking, the approach is applicable to a wide range of corridor-based planning needs.

Use this three-step workflow to move from broad freight patterns to site-level insights:

Start wide: Use Origin & Destination to map truck movement across corridors.
Zoom in: Use Stop Analytics to detect pressure zones.
Go micro: Use Custom Zones + Stop Analytics to analyze behavior at specific sites

This method applies to use cases such as: freight bottleneck detection, EV charging site planning, Rest area performance evaluation, Ramp parking and safety risk analysis, Infrastructure funding justification

This use case is presented in three stages:

Stage 1: Corridor Demand and Routing Patterns.
Stage 2: Stop Clustering Along Freight Corridors.
Stage 3: Site-Level Stop Behavior at Rest Areas.

Stage 1: Corridor Demand and Routing Patterns

Begin by understanding which corridors carry the highest freight volumes, where trips start and end, and which road segments are most used. This stage sets the geographic and operational context for any corridor-level planning effort.

Learn to define corridor geographies, apply filters for heavy-duty and long-haul vehicles, and run an OD analysis to trace observed movement. This forms the foundation for any corridor-focused use case by revealing how trucks are using the network.

Learn how to interpret journey volumes, vocations, and OD matrices, then drill into top journey pairs to analyze route patterns. Route-level insights help prioritize specific highway segments or connectors for deeper analysis—relevant for parking, safety, or capacity studies.

Stage 2: Stop Clustering Along Freight Corridors

Next, determine where trucks are stopping—legally or not—along the corridor. This method applies equally to parking, staging, curbside behavior, or idling analyses.

Use hex grid aggregation to detect where long-haul trucks stop along major corridors. Apply stop duration filters to isolate overnight or dwell behaviors. Enables planners to identify unmet infrastructure needs, staging bottlenecks, or emerging informal zones.

Learn to visualize stop density, durations, and idle time across different times of day. Reveals patterns useful for both truck parking and operational performance evaluations such as curb access or staging conflicts.

Stage 3: Site-Level Stop Behavior at Rest Areas

Finally, drill into specific sites—such as rest areas, truck stops, or industrial zones—to assess real-world use. This methodology supports site selection, capacity evaluation, or safety assessments.

Learn to draw precise zones around specific facilities, intersections, or informal locations. Custom zones enable highly targeted analysis for infrastructure planning, redesign, or monitoring.

Run a high-resolution analysis within these zones to evaluate stop counts, durations, and parking behavior. Helps validate whether a site is meeting demand, exceeding capacity, or experiencing overflow—useful for any site planning scenario.

Identify overflow conditions (e.g., ramp or shoulder parking), peak usage times, and site utilization patterns. Supports capital project decisions, operational design, enforcement strategies, or grant funding applications.

Market Scan: Identify Fuel Demand with Regional Travel Metrics

Identify regions or counties where commercial vehicle fuel demand (diesel/gasoline) is strongest—based on real-world movement and stop behavior, not assumptions.

This initial step in the site selection strategy uses regional travel data to focus efforts on markets with proven, high commercial activity.

Scan across national or regional corridors to identify areas with high Commercial Vehicle Miles Traveled (VMT).
Prioritize counties or corridors with growing freight intensity for future focus.
Use this analysis to shortlist where your network is overperforming, underpenetrated, or needs expansion.
Create a focused, defensible list of target markets based on actual commercial demand.

Set up a Market Demand Analysis

Learn how to configure a market-level demand analysis using the Regional Travel Metrics (RTM) module. This setup demonstrates how to segment movement data by vehicle class, vocation, and fuel type across a defined geographic area (like counties or regions) to pinpoint the most active commercial markets for fuel planning.

Exploring, scaling, and prioritizing markets based on observed customer demand

Learn how to translate the results of a market demand analysis into actionable forecasts. This step guides you in reviewing core movement metrics (VMT, Vehicle Count) and applying Expansion Factors to estimate the full market size and prioritize high-potential, underserved regions before moving to site-specific evaluations.

Analyze Frontage Exposure for Prospective Development Sites

Identify the precise volume and mix of commercial vehicle traffic passing directly in front of a prospective or existing fuel site—based on real-world movement and routing, not general AADT estimates.

This second step in the site selection strategy uses site-level pass-through data to validate investments and benchmark exposure at competing locations.

Draw a custom zone along the roadway frontage of a candidate site.
Filter movement to isolate the fleet segments relevant to your forecourt (e.g., light- and medium-duty vehicles).
Measure observed journeys that cross the site’s frontage without stopping.
Use this analysis to justify investments, compare competing locations, and capture untapped demand at specific addresses.
Get a precise, segment-specific view of the daily commercial vehicle traffic flowing directly past a specific site—using observed journeys, not modeled counts.

Set up a frontage exposure analysis

Learn how to configure a site-level exposure analysis using the Origin & Destination (O/D) module. This setup demonstrates how to measure commercial traffic flow for specific vehicle classes and trip behaviors (pass-through only) across a defined, small geographic area (like a roadway frontage) to pinpoint precise, site-level opportunity.

Explore your frontage exposure analysis to quantify site-level commercial opportunity

Datasets and Expansion Factors

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