
GITNUXSOFTWARE ADVICE
Business FinanceTop 10 Best Traffic Counting Software of 2026
Editorial roundup comparing traffic counting software tools like INRIX, Placer.ai, and Miovision for planning teams and traffic analysts.
How we ranked these tools
Vendors set the topic, but our editors set the inclusion criteria and the evaluation framework before research starts.
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Framework: Features 40% · Ease 30% · Value 30%
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INRIX is the best pick for GIS-first agencies doing recurring operational reporting because its roadway-referenced context keeps counts and speeds consistent across repeated segment and intersection outputs, while Countwise is a strong alternative for SMB survey teams since its validation-heavy intersection workflows help flag inconsistent entries before dependable exports.
Editor’s top 3 picks
Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.
INRIX
Roadway-segment and intersection context that keeps counts and speed aligned across repeated reporting cycles.
Best for: Fits when GIS-first agencies need consistent traffic volume and speed outputs for recurring operational reporting.
Placer.ai
Editor pickGeofence-based traffic estimates from mobile location signals mapped to road-adjacent count locations.
Best for: Fits when teams need recurring traffic estimates for many geographies without installing roadway sensors.
Miovision
Editor pickValidated intersection count workflows that convert raw detections into reviewable turning movement count outputs.
Best for: Fits when operations teams need repeatable intersection counts with validated traffic flow data exports.
Comparison Table
INRIX
enterpriseMobility data software provides traffic volumes, speeds, travel times, and roadway performance measures.
Roadway-segment and intersection context that keeps counts and speed aligned across repeated reporting cycles.
INRIX is built around traffic flow data products that combine vehicle count and speed measurement with roadway-referenced delivery, so teams can keep dashboards aligned to the same segments and intersections over time. The workflow supports time-of-day aggregation and peak-hour analysis outputs that can feed annual average daily traffic style reporting and ongoing count validation.
A key tradeoff is that INRIX is strongest when the use case accepts its established roadway coverage and data products rather than building custom count geometries from raw sensor feeds. INRIX fits situations where multiple stakeholders need consistent traffic count outputs for recurring operational decisions, especially when GIS alignment reduces manual reconciliation work.
- +Roadway-referenced outputs support consistent segment and intersection reporting
- +Time-of-day aggregation supports peak-hour analysis without manual reshaping
- +Count and speed outputs align for cross-checking traffic flow trends
- +GIS integration reduces reconciliation work across count locations
- –Custom count geometry creation from sensor feeds is limited
- –Integration depth can require technical ownership for automation and governance
- –Some workflows depend on accepting INRIX data product coverage
- –Rapid experimentation may be slower than tools built for survey-only counts
City transportation planning teams
Peak-hour and time-of-day reporting
Faster reporting cycles
Mobility analytics groups
Cross-checking count and speed
Lower data inconsistency
Show 2 more scenarios
Regional traffic operations
Operational monitoring by count location
Stable monitoring baselines
Maintain consistent traffic count locations for dashboarding and change tracking.
GIS administrators
Roadway mapping alignment
Less reconciliation work
Place outputs into GIS to reduce manual linkages between surveys and assets.
Best for: Fits when GIS-first agencies need consistent traffic volume and speed outputs for recurring operational reporting.
Placer.ai
enterpriseLocation analytics platform providing foot traffic and visitation counting for retail and commercial sites.
Geofence-based traffic estimates from mobile location signals mapped to road-adjacent count locations.
Placer.ai produces traffic volume measurement from mobile location signals and aggregates it onto count locations for retail, events, and venues. It supports roadway segment and intersection count use cases by mapping observed movement patterns to road-adjacent geofences and time windows.
The workflow centers on configuration of geographies and baselines, followed by time-of-day aggregation and export for analysis. API and automation features are geared toward recurring reporting and data validation across locations and periods.
- +Mobile-signal coverage enables counting without site-based detectors
- +API supports automated refresh across many count locations
- +Time-of-day aggregation supports peak-hour analysis workflows
- +Exports support downstream GIS and BI pipelines
- –Road mapping accuracy depends on geofence configuration discipline
- –Vehicle classification and speed measurement coverage is indirect
- –Audit-level data lineage across transformations can require extra work
- –Intersection turning movement count is not a direct native output
Transportation and GIS planning teams
Estimate roadway traffic time series
Adds historical traffic context
Mall owners and leasing teams
Assess catchment visitation and footfall
Evidence for leasing decisions
Show 2 more scenarios
Retail portfolio analytics teams
Benchmark visit trends across stores
Consistent cross-location comparisons
Teams compare performance changes across locations using standardized multi-site time aggregation.
Out-of-home media planning teams
Plan proximity audiences and benchmarks
Location-aware campaign KPI analysis
Planners use visitation benchmarks and location footprints to pace and evaluate campaigns.
Best for: Fits when teams need recurring traffic estimates for many geographies without installing roadway sensors.
Miovision
enterpriseTraffic data software supports intersection counts, turning movements, signal analysis, and transportation planning.
Validated intersection count workflows that convert raw detections into reviewable turning movement count outputs.
Miovision supports end-to-end traffic counting workflows that combine field data capture, validation, and distribution into traffic flow outputs for operational teams. The tool handles intersection count workflows that include vehicle counts and turning movement counts, which helps teams analyze demand beyond total volume. Time-of-day aggregation outputs support peak-hour and period comparisons for roadway segment and intersection reporting.
A tradeoff is that the intersection-focused workflow can require more setup effort than simpler segment-only counting tools. Miovision fits best when agencies need consistent counting data across multiple sites and when turning movement detail and time-of-day summaries are required for traffic studies and operational review cycles.
- +Intersection count workflow supports turning movement capture and review
- +Count data exports support integration into external analysis pipelines
- +Configuration for count duration and time-of-day aggregation is straightforward
- +Validation workflows reduce errors before traffic count survey deliverables
- –Automation depth depends on how sensors and recorders are deployed
- –Modeling complex count plans across many count locations takes planning
- –Custom reporting requires more setup than basic hourly volume profiles
- –Governance controls can feel limited for multi-team administration
Traffic engineering analysts
Peak-hour turning movement analysis
Clear peak period insights
City transportation operations
Road segment and intersection reporting
On-schedule traffic reporting
Show 2 more scenarios
Intersection study project managers
Vehicle counts plus turning movements
More complete demand data
Run integrated intersection workflows that combine vehicle totals with turning movement outputs.
Data quality and validation leads
Consistent count validation
Higher data reliability
Apply built-in validation steps to reduce inconsistencies between captured and distributed traffic data.
Best for: Fits when operations teams need repeatable intersection counts with validated traffic flow data exports.
Rekor
enterpriseRoadway intelligence software uses computer vision to classify vehicles and measure traffic activity.
Automated count generation from video scenes mapped to specific roadway segment or intersection count locations.
Rekor is a traffic counting software solution built around video-based detection and automated count generation for roadway corridors and intersection count locations. It supports outputs that can be used for time-of-day aggregation and count duration reporting, which helps when programs need predictable hourly volume profiles. The integration and automation surface is most useful when multiple locations must follow similar processing logic and exports feed GIS and traffic analysis workflows.
- +Video-driven counting that produces consistent count outputs by count location
- +Repeatable processing steps reduce variability across similarly configured sites
- +Exports support downstream traffic flow data workflows and reporting
- +Detection configuration can be tuned for intersection and roadway segment use
- –Non-video sensor sources may require extra bridging work
- –Setup tuning is sensitive to camera placement and operating conditions
- –Advanced governance controls are limited compared with enterprise data platforms
Traffic engineering teams
Hourly volume reporting for intersections
More consistent peak-hour estimates
Transportation analytics teams
Roadway segment count program
Faster multi-site reporting
Show 1 more scenario
GIS and planning analysts
Seasonal comparisons by export data
Quicker seasonal trend reviews
Exports count data for validation steps and annual comparison workflows.
Best for: Fits when agencies need automated video-based vehicle counts feeding time-of-day reporting.
StreetLight Data
enterpriseMobility analytics software estimates vehicle, bicycle, and pedestrian volumes across road networks.
API-backed workflow for defining study geometries and running repeatable traffic count and speed outputs at scale.
StreetLight Data provides traffic flow data products built from aggregated mobility signals, which makes it distinct from systems that rely on fixed roadway sensors. The core workflow centers on defining roadway segment or intersection study areas, generating time-of-day traffic count and speed measures, and validating outputs with quality controls.
- +Mobility-signal derived traffic flow outputs for roadway segments and intersections
- +Repeatable results via an automation-first workflow with API access
- +Quality controls and validation steps for count and speed measures
- +Export options for feeding GIS and analytics pipelines
- –Not a physical sensor management system for inductive loops or radar detectors
- –Turn-by-turn turning movement detail is limited versus intersection-focused TMC workflows
- –Roadway geometry setup can require iteration to match count locations
- –Governance needs rely on customer process for access control and change review
Transportation planning consultants
Estimate volumes across large roadway networks
Historical volume estimates for studies
Road safety analysts
Prioritize safety reviews using mobility evidence
GIS-ready evidence for prioritization
Show 2 more scenarios
Corridor operations teams
Compare speed and volume trends over time
Consistent corridor performance views
Run repeatable count surveys across recurring windows to monitor corridor performance and movement patterns.
Retail real estate strategists
Analyze movement trends around store zones
Store-network comparisons for planning
Use exported mobility counts to compare foot-traffic patterns across stores and catchment areas.
Best for: Fits when agencies or consultancies need fast traffic flow data coverage without installing sensor hardware.
Countwise
SMBPeople and vehicle traffic counting software using overhead thermal and video sensors.
Count session validation that highlights inconsistencies before exporting roadway segment and turning movement outputs.
Countwise targets traffic count survey workflows that need repeatable data collection across roadway segments and intersections. It focuses on field capture to produce vehicle count and time-of-day aggregation outputs, with validation to flag inconsistencies during review.
- +Field workflow built around intersection and count location setup
- +Validation checks help catch missing or inconsistent count entries
- +Time-of-day aggregation supports peak-hour analysis prep
- +Exports stay aligned to typical traffic flow data analysis pipelines
- –Vehicle classification coverage can be limited depending on sensor or capture mode
- –Turning movement count configuration requires careful mapping discipline
- –Audit trails and governance controls are not as granular as enterprise RBAC needs
- –Automations and API surface are thin for fully custom aggregation logic
Municipal traffic engineering teams
Run repeatable intersection turning counts
More consistent counts
Transportation planning consultants
Produce segment counts for studies
Faster study deliverables
Show 2 more scenarios
Roadway survey managers
Collect pedestrian and bicycle tallies
Cleaner field verification
Count location configuration ties non-vehicle tallies to defined survey points and review checks.
Data analysts for traffic models
Export structured flow datasets
Less cleanup work
Exported traffic flow formats feed downstream analysis pipelines without manual reformatting.
Best for: Fits when traffic count survey teams need repeatable intersection workflows and dependable exports for analysis.
Voxel51 FiftyOne
API-firstOpen-source computer vision toolkit supporting custom object and vehicle counting model evaluation.
View-based dataset filtering and evaluation ties detection results back to specific frames and metadata for count validation.
Voxel51 FiftyOne ingests and labels vehicle and road-scene data, then turns it into analytics-ready datasets for counting workflows. The core capability centers on multimodal dataset management, view-based filtering, and evaluation tooling that connects detection outputs to vehicle count and traffic flow data products.
- +Python API supports custom ingestion and transform pipelines
- +View and filter workflow accelerates iterative count QA on subsets
- +Dataset-centric operations keep frames, detections, and metadata aligned
- +Built-in evaluation tooling supports validation of detection outputs
- –Does not provide a native hardware counting stack like loop or radar integrations
- –Traffic counting outputs require custom mapping from detections to counts
- –Large video datasets can stress local storage and indexing throughput
- –Operational governance like RBAC and audit logs is not a primary focus
Traffic analytics engineers
Convert detections into vehicle count reports
Repeatable counting metrics across sites
Computer vision QA teams
Audit detection errors affecting counts
Fewer counting discrepancies
Show 2 more scenarios
Road safety research groups
Evaluate models on traffic scenes
More reliable traffic behavior studies
Evaluation tooling links model outputs to counting targets for consistent traffic flow comparisons.
Systems integrators
Automate ingestion from sensors and videos
Faster integration to analytics
A Python-first API ingests multimodal data and transforms it into analytics-ready datasets for counting pipelines.
Best for: Fits when traffic counting depends on video detection results that need dataset QA and automated reporting.
Axis Communications Camera Station
enterpriseVideo management software with integrated people and vehicle counting analytics for Axis network cameras.
Traffic-focused video workflows built around Axis camera and recorder control for repeatable count collection.
Axis Communications Camera Station pairs video management features with traffic use through its support for Axis video devices and analytics-oriented workflows. It enables roadway scene setup that turns camera views into vehicle count outputs for operational traffic monitoring and reporting.
- +Works directly with Axis camera ecosystems for unified camera and recording control
- +Video scene configuration supports repeatable vehicle count collection per roadway segment
- +Reporting outputs fit CSV handoff workflows for standard traffic count survey processing
- +Centralized management reduces operational overhead for multi-camera intersections
- –Traffic detection and classification quality depends heavily on camera placement and lighting
- –Extensibility is limited compared with platforms that offer direct API access to counts
- –Setup time rises when tuning detection across multiple intersections and turning movements
- –Audit and governance controls for count data are less granular than enterprise workflow systems
Traffic operations analyst team
Configure roadway scenes for vehicle counts
Consistent traffic count outputs
Regional security administrators
Manage traffic monitoring across sites
Centralized multi-site oversight
Show 2 more scenarios
Physical security IT managers
Onboard ONVIF cameras with Axis
Shared monitoring workflow
Teams add compatible third-party cameras through ONVIF to unify live monitoring and recording workflows.
Compliance and investigation teams
Share traffic clips for reviews
Portable evidence for review
Teams export selected clips to document incidents and support stakeholder handoff.
Best for: Fits when teams already standardized on Axis cameras and need configuration-based vehicle count reporting.
Eco-Counter
vertical specialistCounting systems and software measure pedestrian, bicycle, and vehicle traffic at outdoor sites.
Session-based count management that ties device data to count location and duration settings for controlled surveys.
Eco-Counter is traffic counting software focused on field devices and count sessions tied to specific count locations and time windows. It handles vehicle count workflows with configuration for data validation and repeatable setup across surveys.
- +Count sessions map cleanly to count locations and predefined durations
- +Configuration supports repeatable surveys across multiple field deployments
- +Export outputs fit common downstream analysis workflows
- +Validation tooling reduces obvious collection errors during review
- –Automation depth is limited for custom analytics pipelines
- –Extensibility depends on how device integrations are packaged
- –GIS workflows require consistent coordinate hygiene before import
- –Admin governance for multi-team sharing is not as granular as enterprise needs
Municipal traffic engineers
Plan site counts across time windows
Cleaner datasets for planning models
Consulting survey teams
Run recurring surveys with consistent setups
Faster survey turnaround
Show 2 more scenarios
GIS analysts and planners
Export traffic flows for spatial analysis
Quicker mapping and reporting
Produces exports that support spreadsheet review and GIS-oriented workflows tied to count locations.
Road safety data managers
Validate vehicle counts before sharing
More reliable traffic statistics
Applies data validation steps to reduce errors from field collection and organize outputs for review.
Best for: Fits when roadway teams need managed count sessions from device collection to validated exports.
GoodVision Video Insights
vertical specialistAI video analytics software counts vehicles, pedestrians, cyclists, and traffic movements from camera footage.
Detection-zone configuration for intersection-style counting from video scenes, with scheduled interval exports for traffic analysis.
GoodVision Video Insights is built around video traffic detection workflows that map detection regions to count outputs. Configurations cover vehicle presence over time, per-interval volume profiles, and structured results intended for downstream traffic analysis. Automation is centered on repeating the same camera setup across scheduled count windows to reduce manual rework.
- +Video detection zones map directly to roadway and intersection counting
- +Repeatable count windows support recurring traffic count surveys
- +Time-of-day volume outputs fit peak-hour analysis workflows
- +Exports integrate with GIS and reporting pipelines
- –Scene illumination and camera angle can require frequent zone tuning
- –Accuracy validation workflows take effort when scenes change
- –Advanced classification depth can lag specialized axle or LPR systems
- –Multi-site governance needs careful configuration standards
Transportation planners
Peak-hour analysis from fixed cameras
Faster peak-hour reporting
Traffic survey coordinators
Recurring count duration studies
Consistent survey timelines
Show 2 more scenarios
GIS and reporting teams
Roadway segment aggregation exports
Reduced manual data wrangling
Outputs structured counts that can be merged into GIS layers and time-of-day reporting formats.
Operations analysts
Traffic flow data validation cycles
Lower data rework
Supports repeatable output generation that teams can review and adjust when video conditions drift.
Best for: Fits when traffic teams need repeatable video counts for fixed camera locations and interval reporting.
Conclusion
After evaluating 10 traffic counting software, INRIX stands out as our overall top pick — it scored highest across our combined criteria of features, ease of use, and value, which is why it sits at #1 in the rankings above.
Use the comparison table and detailed reviews above to validate the fit against your own requirements before committing to a tool.
Frequently Asked Questions About Traffic Counting Software
Which traffic counting software is best for video-based intersection counts?
How do API and automation capabilities differ across traffic counting tools?
What integrations support GIS and downstream reporting?
What is the tradeoff between fixed sensors and mobility-signal data?
When should a team use dataset tooling instead of a field-counting platform?
What breaks if detection settings are not recalibrated for new sites?
Do these tools provide SSO, RBAC, audit logs, or compliance controls?
How can teams migrate existing traffic count data into a new platform?
Tools reviewed
Primary sources checked during evaluation.
Referenced in the comparison table and product reviews above.
How to Choose the Right Traffic Counting Software
What separates traffic counting software is how each tool turns raw site inputs into dependable counts and how much control you get over configuration, output, and repeatability. In practice, the biggest differences show up in data import and validation, configuration transparency, and export formats.
Import and validation behavior
Why it matters
Import and validation behavior decides whether you trust counts after moving projects between sites or after changing devices. If the tool quietly repairs issues, you may never know what changed in your results.
How to check
Ask for a sample import workflow using a provided file, then check whether it flags gaps, time mismatches, or malformed rows instead of silently accepting them. In the output, look for an audit-style summary of what was corrected or rejected.
Counting configuration transparency
Why it matters
Counting configuration transparency matters because small setting changes can shift totals across hours and days. You need to reproduce counts when seasons or site conditions change.
How to check
During a demo, request to set up two similar counts with one variable changed (for example time window or detection method) and compare the resulting totals. Then ask where those settings are stored and how you can review the exact configuration later.
Time granularity output options
Why it matters
Time granularity output options determine whether the software matches how your team consumes results, from hourly views to daily summaries. If the tool over-aggregates early, it can limit later QA and reporting.
How to check
Export the same count for at least two time views and confirm the timestamps and rollups match what the interface shows. Ask whether you can re-export the same site data with a different time aggregation without reprocessing everything manually.
Quality review and exception handling
Why it matters
Quality review and exception handling affects how quickly you locate bad periods and how consistently you exclude them. This is where confidence is won or lost for long-running counts.
How to check
Request a workflow that marks or filters problematic intervals, then verify what changes in the exports. Look for a way to review exceptions by date/time and see the before/after impact on totals.
Export formats and field mapping
Why it matters
Export formats and field mapping matter when you need traffic counting software to fit into an existing reporting pipeline. Missing fields or inconsistent naming forces manual cleanup and increases error risk.
How to check
Export results from a demo project and inspect the column names, timestamp fields, and unit conventions. Ask if the mapping can be customized and whether exports stay consistent after edits to configuration.
Red flags
- Validation accepts problematic imports without a clear change log.
- Configuration can’t be reviewed later, so counts can’t be reproduced.
- Exports hide or remap time fields in a way that doesn’t match the screen.
Fit by situation
- If you regularly move count projects between sites, prioritize import and validation behavior.
- If your team needs to reproduce totals after changing site settings, prioritize counting configuration transparency.
- If your reporting depends on hourly-to-daily rollups, prioritize time granularity output options.
Funding and competing interests
This study was co-funded by several of the vendors assessed in it. No single vendor funded it. Funders could propose the market studied.
They had no role in selecting vendors, setting or weighting criteria, analysing data or drawing conclusions, and they received the same factual-accuracy check as every other vendor assessed.
Market definition, inclusion rules and criteria weights were fixed by an editor before research began and did not change afterwards. Editorial process →
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