Foot Traffic Data Market Outlook

According to our latest research, the global foot traffic data market size reached USD 5.9 billion in 2024, reflecting robust adoption across various industries. The market is poised for substantial growth, projected to expand at a CAGR of 14.2% from 2025 to 2033. By the end of 2033, the foot traffic data market is forecasted to achieve a value of USD 18.5 billion. This impressive growth trajectory is primarily driven by the increasing demand for advanced analytics and real-time insights into consumer behavior, propelling the adoption of foot traffic data solutions across retail, transportation, and smart city initiatives worldwide.

A key growth factor for the foot traffic data market is the escalating need for actionable business intelligence in brick-and-mortar environments. Retailers, shopping malls, and real estate developers are leveraging foot traffic data to optimize store layouts, enhance customer experiences, and drive sales conversion rates. The proliferation of omnichannel retail strategies has further intensified the necessity for precise in-store analytics, allowing businesses to align their physical and digital operations seamlessly. The integration of foot traffic data with artificial intelligence and machine learning algorithms enables predictive analytics, empowering organizations to anticipate consumer trends and personalize marketing efforts. As competition intensifies in the retail sector, the adoption of foot traffic analytics is becoming a strategic imperative, driving sustained market growth.

Another significant driver is the expansion of smart city initiatives and the growing emphasis on urban mobility solutions. Governments and municipal authorities are increasingly deploying advanced sensors, cameras, and wireless networks to monitor pedestrian movement, optimize public transportation routes, and enhance urban planning. The use of foot traffic data in urban environments facilitates efficient crowd management, improves public safety, and supports infrastructure development. Additionally, the rise of large-scale events, stadiums, and transportation hubs has necessitated the implementation of sophisticated foot traffic monitoring systems to manage crowd flow and ensure seamless visitor experiences. The convergence of IoT technologies with foot traffic analytics is unlocking new opportunities for data-driven decision-making in public and private sector applications.

The rapid adoption of mobile devices and the proliferation of connectivity technologies such as Wi-Fi and Bluetooth have transformed the way foot traffic data is collected and analyzed. Mobile applications and connected sensors enable real-time monitoring of pedestrian movement, providing granular insights into dwell times, footfall patterns, and peak hours. This technological evolution has significantly reduced the barriers to entry for organizations seeking to implement foot traffic analytics, democratizing access to valuable data for businesses of all sizes. The ongoing advancements in edge computing and cloud-based analytics platforms are further enhancing the scalability and flexibility of foot traffic data solutions, supporting their widespread adoption across diverse industry verticals.

The implementation of a Foot Traffic Heatmap Sensor Grid is revolutionizing how businesses and urban planners understand and utilize pedestrian data. By deploying a network of interconnected sensors, organizations can visualize foot traffic patterns in real-time, enabling more precise and dynamic decision-making. This technology is particularly beneficial in retail environments, where understanding customer flow can lead to optimized store layouts and enhanced shopping experiences. In urban settings, sensor grids contribute to improved public safety and efficient crowd management by providing detailed insights into pedestrian movement. As the demand for real-time analytics grows, the adoption of sensor grids is expected to become a standard practice in both commercial and public sectors, driving further innovation and integration with other smart technologies.

Regionally, North America continues to dominate the global foot traffic data market, driven by the presence of leading technology providers, a highly developed retail sector, and early adoption of smart city solutions. However, the Asia Pacific regio

Leverage the most reliable and compliant mobile device location/foot traffic dataset on the market. Veraset Movement (Mobile Device GPS / Foot Traffic Data) offers unparalleled insights into footfall traffic patterns across North America.

Covering the United States, Canada and Mexico, Veraset's Mobile Location Data draws on raw GPS data from tier-1 apps, SDKs, and aggregators of mobile devices to provide customers with accurate, up-to-the-minute information on human movement. Ideal for ad tech, planning, retail analysis, and transportation logistics, Veraset's Movement data helps in shaping strategy and making data-driven decisions.

Veraset’s North American Movement Panel: - United States: 768M Devices, 70B+ Pings - Canada: 55M+ Devices, 9B+ Pings - Mexico: 125M+ Devices, 14B+ Pings - MAU/Devices and Monthly Pings

Uses for Veraset's Mobile Location Data: - Advertising - Ad Placement, Attribution, and Segmentation - Audience Creation/Building - Dynamic Ad Targeting - Infrastructure Plans - Route Optimization - Public Transit Optimization - Credit Card Loyalty - Competitive Analysis - Risk assessment, Underwriting, and Policy Personalization - Enrichment of Existing Datasets - Trade Area Analysis - Predictive Analytics and Trend Forecasting

This foot traffic dataset provides GPS-based mobile movement signals from across South America. It is ideal for retailers, city agencies, advertisers, and real estate professionals seeking insights into how people move through physical locations and urban spaces.

Each record includes:

Device ID (IDFA or GAID) Timestamps (in milliseconds and readable format) GPS coordinates (lat/lon) Country code Horizontal accuracy (85%) Optional IP address, mobile carrier, and device model

Access the data via polygon queries (up to 10,000 tiles), and receive files in CSV, JSON, or Parquet, delivered hourly or daily via API, AWS S3, or Google Cloud. Data freshness is strong (95% delivered within 3 days), with full historical backfill available from September 2024.

This solution supports flexible credit-based pricing and is privacy-compliant under GDPR and CCPA.

Key Attributes:

Custom POI or polygon query capability Backfilled GPS traffic available across LATAM High-resolution movement with daily/hourly cadence GDPR/CCPA-aligned with opt-out handling Delivery via API or major cloud platforms

Use Cases:

Competitive benchmarking across malls or stores Transport and infrastructure planning Advertising attribution for outdoor/DOOH campaigns Footfall modeling for commercial leases City zoning, tourism, and planning investments Telecom & tower planning across developing corridors

Leading dollar stores in the United States, Dollar General and Dollar Tree, have sustained foot traffic growth during most months over the past two years, compared to July 2022. Each December and May, visits surged and, in July 2024, they increased by over ** percent at Dollar General and over ***percent at Dollar Tree, compared to the base month.

GapMaps Foot Traffic Data by Azira provides actionable insights on consumer travel patterns at a global scale empowering Marketing and Operational Leaders to confidently reach, understand, and market to highly targeted audiences and optimize their business results.

This foot traffic dataset provides real-time and historical visitation patterns across North America, derived from anonymized mobile GPS signals. Irys captures movement data around physical locations and delivers accurate, timestamped insights to power a variety of commercial and civic applications.

The data includes:

Latitude & longitude coordinates Timestamps (epoch and date) Device ID (MAID: IDFA/GAID) Horizontal accuracy Country code Optional IP address, device carrier, and metadata

Clients can query traffic around specific POIs or polygon areas, and receive results in CSV, Parquet, or JSON formats. Delivery is available via API or cloud (AWS S3 / GCP), with updates as frequent as hourly. Event freshness is strong, with 95% of pings delivered within 3 days, and historical data available since September 2022.

Technical and Qualitative Benefits:

Polygon query support (up to 10,000 tiles) Custom schema mapping and folder structuring Flexible, credit-based pricing per query (by area + duration) GDPR & CCPA compliant

For the week ended May 9, 2020, aggregate consumer foot traffic in the United States was up by **** percent when compared to the previous week. For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

Foot Traffic Data Market Outlook

According to our latest research, the global foot traffic data market size in 2024 stands at USD 5.9 billion, reflecting robust adoption across retail, real estate, and smart city applications. The market is experiencing a strong growth momentum, with a projected CAGR of 12.6% from 2025 to 2033, leading to a forecasted market value of USD 17.2 billion by 2033. This remarkable growth is primarily fueled by the increasing emphasis on data-driven decision-making, the proliferation of IoT devices, and the growing need for real-time analytics in both public and private sectors.

A primary growth driver for the foot traffic data market is the retail sector’s rapid digital transformation and the intensifying competition among brick-and-mortar stores and e-commerce platforms. Retailers are leveraging foot traffic analytics to optimize store layouts, personalize marketing campaigns, and enhance overall customer experiences. The integration of advanced technologies such as AI, machine learning, and cloud computing has empowered businesses to gain deeper insights into consumer behavior, dwell times, and conversion rates. Moreover, the rise of omnichannel retail strategies necessitates the synchronization of online and offline customer journeys, further boosting demand for comprehensive foot traffic data solutions. As retailers continue to invest in smart infrastructure, the need for actionable, real-time data to drive operational efficiency and profitability will only escalate, ensuring sustained market growth.

Another significant growth factor is the increasing adoption of smart city initiatives and the deployment of IoT infrastructure across urban centers. Municipalities and public authorities are turning to foot traffic data to optimize urban planning, improve public safety, and enhance transportation systems. By analyzing pedestrian flows and congestion points, city planners can make informed decisions regarding infrastructure investments, event management, and emergency response strategies. The integration of foot traffic data with other urban datasets, such as traffic, weather, and public transport usage, enables the creation of holistic, data-driven solutions that improve the quality of urban life. This trend is particularly strong in regions with high urbanization rates, such as Asia Pacific and parts of Europe, where governments are prioritizing smart city development as part of their digital transformation agendas.

The proliferation of mobile devices and advancements in sensor technologies are further accelerating the growth of the foot traffic data market. With the widespread adoption of smartphones, Wi-Fi, Bluetooth beacons, and camera-based systems, businesses and public entities can now collect granular, location-based data at an unprecedented scale. This technological convergence has significantly lowered the barriers to entry for organizations seeking to implement foot traffic analytics, enabling even small and medium-sized enterprises to harness the power of location intelligence. Furthermore, the growing availability of cloud-based analytics platforms ensures that data can be processed and visualized in real-time, supporting agile decision-making and rapid response to changing footfall patterns. As sensor technologies continue to evolve, offering greater accuracy and lower power consumption, the market is expected to witness further innovation and expansion.

From a regional perspective, North America currently leads the global foot traffic data market, driven by early technology adoption, the presence of major market players, and significant investments in smart infrastructure. However, the Asia Pacific region is emerging as a high-growth market, fueled by rapid urbanization, expanding retail sectors, and ambitious smart city projects in countries such as China, Japan, and India. Europe also demonstrates strong demand, particularly in retail analytics and transportation management, while the Middle East & Africa and Latin America are gradually catching up, supported by digital transformation initiatives and increasing awareness of the benefits of foot traffic analytics. As market penetration deepens across these regions, the competitive landscape is expected to intensify, with local and global players vying for market share through product innovation and strategic partnerships.

Component Analysis

The component segment o

Leverage the most reliable and compliant mobile device location/foot traffic dataset on the market!

Veraset Movement (GPS Mobility Data) offers unparalleled insights into foot traffic patterns for dozens of countries across the Middle East.

Covering 14+ countries for the Middle East alone, Veraset's foot traffic Data draws on raw GPS data from tier-1 apps, SDKs, and aggregators of mobile devices to provide customers with accurate, up-to-the-minute information on human movement. Ideal for ad tech, planning, retail, and transportation logistics, Veraset's Movement data (footfall) helps shape strategy and make impactful data-driven decisions.

Veraset’s Africa Footfall Panel includes the following countries: - bahrain-BH - iran-IR - iraq-IQ - israel-IL - jordan-JO - kuwait-KW - lebanon-LB - oman-OM - palestinian territories-PS - qatar-QA - saudi arabia-SA - syria-SY - united arab emirates-AE - yemen-YE

Common Use Cases of Veraset's Foot Traffic Data: - Advertising - Ad Placement, Attribution, and Segmentation - Audience Creation/Building - Dynamic Ad Targeting - Infrastructure Plans - Route Optimization - Public Transit Optimization - Credit Card Loyalty - Competitive Analysis - Risk assessment, Underwriting, and Policy Personalization - Enrichment of Existing Datasets - Trade Area Analysis - Predictive Analytics and Trend Forecasting

The dataset contains all traffic counters in Hamburg for vehicle, cycling and foot traffic. A distinction is made between permanent counting points, annual counting points, levels and demand counting points.

At “permanent counting points”, motor vehicle traffic is automatically recorded by means of induction loops 24 hours a day and 365 days a year. At ‘Annual Counting Points’, traffic was usually recorded at least once a year from 6 a.m. to 7 p.m. by a manual traffic count until and including 2020. Since 2021, these manual traffic counts have largely been replaced by the use of infrared sensors. From the permanent counting points and from the annual counting points, “levels” are derived, at which the average daily traffic strengths (DTV, DTVw) determined for each year are included in the traffic statistics (observation of long-term traffic developments). At “requirement counting points” traffic is recorded irregularly and exclusively on occasion (e.g. in connection with traffic planning or investigations), usually by a manual traffic count, usually from 6 am to 7 pm. The content of the data is the counting point number, the location designation and the date of the last count. The results of the census (traffic strengths) will not be published through this service. For the research of traffic strengths, the services can be used under the keyword search “Traffic strength”.

This dataset gives the numbers of foot traffic counts by branches in a given quarter. Updated annually.

Our dataset provides detailed and precise insights into the business, commercial, and industrial aspects of any given area in the USA (Including Point of Interest (POI) Data and Foot Traffic. The dataset is divided into 150x150 sqm areas (geohash 7) and has over 50 variables. - Use it for different applications: Our combined dataset, which includes POI and foot traffic data, can be employed for various purposes. Different data teams use it to guide retailers and FMCG brands in site selection, fuel marketing intelligence, analyze trade areas, and assess company risk. Our dataset has also proven to be useful for real estate investment.- Get reliable data: Our datasets have been processed, enriched, and tested so your data team can use them more quickly and accurately.- Ideal for trainning ML models. The high quality of our geographic information layers results from more than seven years of work dedicated to the deep understanding and modeling of geospatial Big Data. Among the features that distinguished this dataset is the use of anonymized and user-compliant mobile device GPS location, enriched with other alternative and public data.- Easy to use: Our dataset is user-friendly and can be easily integrated to your current models. Also, we can deliver your data in different formats, like .csv, according to your analysis requirements. - Get personalized guidance: In addition to providing reliable datasets, we advise your analysts on their correct implementation.Our data scientists can guide your internal team on the optimal algorithms and models to get the most out of the information we provide (without compromising the security of your internal data).Answer questions like: - What places does my target user visit in a particular area? Which are the best areas to place a new POS?- What is the average yearly income of users in a particular area?- What is the influx of visits that my competition receives?- What is the volume of traffic surrounding my current POS?This dataset is useful for getting insights from industries like:- Retail & FMCG- Banking, Finance, and Investment- Car Dealerships- Real Estate- Convenience Stores- Pharma and medical laboratories- Restaurant chains and franchises- Clothing chains and franchisesOur dataset includes more than 50 variables, such as:- Number of pedestrians seen in the area.- Number of vehicles seen in the area.- Average speed of movement of the vehicles seen in the area.- Point of Interest (POIs) (in number and type) seen in the area (supermarkets, pharmacies, recreational locations, restaurants, offices, hotels, parking lots, wholesalers, financial services, pet services, shopping malls, among others). - Average yearly income range (anonymized and aggregated) of the devices seen in the area.Notes to better understand this dataset:- POI confidence means the average confidence of POIs in the area. In this case, POIs are any kind of location, such as a restaurant, a hotel, or a library. - Category confidences, for example"food_drinks_tobacco_retail_confidence" indicates how confident we are in the existence of food/drink/tobacco retail locations in the area. - We added predictions for The Home Depot and Lowe's Home Improvement stores in the dataset sample. These predictions were the result of a machine-learning model that was trained with the data. Knowing where the current stores are, we can find the most similar areas for new stores to open.How efficient is a Geohash?Geohash is a faster, cost-effective geofencing option that reduces input data load and provides actionable information. Its benefits include faster querying, reduced cost, minimal configuration, and ease of use.Geohash ranges from 1 to 12 characters. The dataset can be split into variable-size geohashes, with the default being geohash7 (150m x 150m).

This product provides daily, aggregated visit counts at the Point of Interest (POI) level, with historical coverage commencing on January 1, 2019. In addition to extensive historical data, it uniquely features visit forecasts for the upcoming 90 days. These forecasts are updated monthly using proprietary modeling techniques to ensure accuracy and relevance.

Leveraging the unique nature of the underlying data, this product is capable of accurately measuring individual stores even within challenging multi-level and densely built-up urban environments, a common limitation for many other data providers.

Each POI is meticulously mapped to a standardized two-level retail category hierarchy, facilitating structured and comparative analysis across diverse retail formats and sectors.

The data is fully aggregated and anonymized, with no device-level records included, ensuring privacy and compliance. Delivered as a daily feed, it supports a wide array of critical business use cases, including precise trend analysis, accurate demand forecasting, competitive benchmarking, and continuous location performance monitoring.

According to Cognitive Market Research, the global Foot Traffic and Customer Location Intelligence Solution market size will be USD 7812.9 million in 2025. It will expand at a compound annual growth rate (CAGR) of 5.00% from 2025 to 2033.

North America held the major market share for more than 40% of the global revenue with a market size of USD 2890.77 million in 2025 and will grow at a compound annual growth rate (CAGR) of 3.8% from 2025 to 2033.
Europe accounted for a market share of over 30% of the global revenue with a market size of USD 2265.74 million.
APAC held a market share of around 23% of the global revenue with a market size of USD 1875.10 million in 2025 and will grow at a compound annual growth rate (CAGR) of 7.5% from 2025 to 2033.
South America has a market share of more than 5% of the global revenue with a market size of USD 296.89 million in 2025 and will grow at a compound annual growth rate (CAGR) of 5.3% from 2025 to 2033.
The Middle East had a market share of around 2% of the global revenue and was estimated at a market size of USD 312.52 million in 2025 and will grow at a compound annual growth rate (CAGR) of 5.5% from 2025 to 2033.
Africa had a market share of around 1% of the global revenue and was estimated at a market size of USD 171.88 million in 2025 and will grow at a compound annual growth rate (CAGR) of 4.7% from 2025 to 2033.
Hardware category is the fastest growing segment of the Foot Traffic and Customer Location Intelligence Solution industry

Market Dynamics of Foot Traffic and Customer Location Intelligence Solution Market

Key Drivers for Foot Traffic and Customer Location Intelligence Solution Market

Rise in Demand for Personalized Consumer Experiences to Boost Market Growth

As businesses increasingly prioritize delivering personalized experiences, the demand for foot traffic and customer location intelligence solutions is growing. By tracking and analyzing customer movements, businesses can gain real-time insights into consumer behaviour and preferences. These solutions help retailers, malls, and other businesses tailor their marketing efforts, promotional strategies, and product placements to meet specific consumer needs. For example, stores can use data to send personalized offers or promotions based on a customer’s location within a store or mall. This enhances customer engagement, increases sales opportunities, and improves the overall shopping experience. In an era where customer satisfaction is a key competitive advantage, businesses are increasingly adopting location-based intelligence tools to enhance customer loyalty and drive revenue.

Growth of Omnichannel Retail Strategies To Boost Market Growth

The growth of omnichannel retail strategies is another key driving factor for the market of foot traffic and customer location intelligence solutions. Modern retailers and service providers are striving to create seamless experiences for customers across multiple touchpoints, including physical stores, websites, and mobile apps. Location intelligence solutions allow businesses to integrate data from different channels, enhancing both in-store and online interactions. For instance, retailers can track foot traffic in physical stores and combine this with online shopping data to understand consumer preferences, predict demand, and optimize inventory. By leveraging location-based insights, retailers can drive more effective cross-channel strategies, improve customer retention, and better allocate resources.

Restraint Factor for the Foot Traffic and Customer Location Intelligence Solution Market

High Data Privacy and Security Concerns Will Limit Market Growth

Data privacy and security remain significant concerns for businesses and consumers in the Foot Traffic and Customer Location Intelligence (FTCLIS) market. These solutions rely heavily on the collection and analysis of location data, often obtained from mobile devices and other tracking technologies. While this data provides valuable insights into customer behaviour, it raises questions about the safety and privacy of personal information. Governments worldwide are implementing stricter regulations like the GDPR in Europe and CCPA in California to protect consumers' data, creating challenges for companies in terms of compliance. Businesses may face high costs to ensure their systems adhere to privacy laws and safeguard against data breaches. Additionally, consum...

This dataset contains hourly pedestrian counts since 2009 from pedestrian sensor devices located across the city. The data is updated on a monthly basis and can be used to determine variations in pedestrian activity throughout the day.The sensor_id column can be used to merge the data with the Pedestrian Counting System - Sensor Locations dataset which details the location, status and directional readings of sensors. Any changes to sensor locations are important to consider when analysing and interpreting pedestrian counts over time.Importants notes about this dataset:• Where no pedestrians have passed underneath a sensor during an hour, a count of zero will be shown for the sensor for that hour.• Directional readings are not included, though we hope to make this available later in the year. Directional readings are provided in the Pedestrian Counting System – Past Hour (counts per minute) dataset.The Pedestrian Counting System helps to understand how people use different city locations at different times of day to better inform decision-making and plan for the future. A representation of pedestrian volume which compares each location on any given day and time can be found in our Online Visualisation.Related datasets:Pedestrian Counting System – Past Hour (counts per minute)Pedestrian Counting System - Sensor Locations

At Echo, our dedication to data curation is unmatched; we focus on providing our clients with an in-depth picture of a physical location based on activity in and around a point of interest over time. Our dataset empowers you to explore the “what” by allowing you to dig deeper into customer movement behaviors, eliminate gaps in your trade area and discover untapped potential. Leverage Echo's Activity datasets to identify new growth opportunities and gain a competitive advantage.

This sample of our Area Activity data provides you insights into the estimated total unique visitors and visits in an area. This helps you understand frequentation dynamics over time, identify emerging trends in people movements and measure the impact of external factors on how people move across a city.

Additional Information: - Understand the actual movement patterns of consumers without using PII data, gaining a 360-degree consumer view. Complement your online behavior knowledge with actual offline actions, and better attribute intent based on real-world behaviors. - Echo collects, cleans and updates its footfall on a daily basis. Normalization of the data occurs on a monthly basis. - We provide data aggregation on a weekly, monthly and quarterly basis. - Information about our country offering and data schema can be found here:

1) Data Schema: https://docs.echo-analytics.com/activity/data-schema
2) Country Availability: https://docs.echo-analytics.com/activity/country-coverage
3) Methodology: https://docs.echo-analytics.com/activity/methodology

Echo's commitment to customer service is evident in our exceptional data quality and dedicated team, providing 360° support throughout your location intelligence journey. We handle the complex tasks to deliver analysis-ready datasets to you.

Business Needs: 1. Site Selection: Leverage footfall data to identify the best location to open a new store. By analyzing areas with high footfall you can select sites that are likely to attract more customers. 2. Urban Planning Development: City planners can use footfall data to optimize the layout and infrastructure of urban areas, guide the development of commercial areas by indicating where pedestrian traffic is heaviest, and aid in traffic management and safety measures. 3. Real Estate Investment: Leverage footfall data to identify lucrative investment opportunities and optimize property management by analyzing pedestrian traffic patterns.

We provide foot traffic data across mobile apps with 30+ enriched attributes, including demographics, devices, app activity, intent and foot traffic insights. We help marketers, agencies, and platforms build precise foot traffic segments, optimize foot traffic targeting, attribute locations, and understand cross-device journeys. Our continuously updated foot traffic datasets deliver real-time foot traffic insights that power smarter location-based campaigns and future-ready strategies.

Leverage our foot traffic data solutions for the following use cases: - Foot Traffic Data Validation & Model Building - Cultural & Seasonal Foot Traffic Insights - Targeted, Data-Driven Foot Traffic Advertising - Foot Traffic & Location-Based Targeting - Trial & Partnership Transparency

With AdPreference, expect the following key benefits through our partnership: - Augment Foot Traffic Data Attributes - Enrich CRM - Personalize Foot Traffic Audiences - Fraud Prevention - Foot Traffic Audience Curation

Access the largest and most customizable foot traffic data segments with AdPreference today. Supercharge your needs with unique and enriched foot traffic data not found anywhere else.

For more information, please visit https://www.adpreference.co/

Count data recorded during the 2019 Walk & Bike Count. Includes those walking, biking, riding motorized scooters, and using other active travel modes.

In September 2024, Walgreens was the drug store with the highest number of average visits in the United States, at over ** thousand. CVS was the second most visited, with about ** thousand visits.

Traffic-related data collected by the Boston Transportation Department, as well as other City departments and State agencies. Various types of counts: Turning Movement Counts, Automated Traffic Recordings, Pedestrian Counts, Delay Studies, and Gap Studies.

~_Turning Movement Counts (TMC)_ present the number of motor vehicles, pedestrians, and cyclists passing through the particular intersection. Specific movements and crossings are recorded for all street approaches involved with the intersection. This data is used in traffic signal retiming programs and for signal requests. Counts are typically conducted for 2-, 4-, 11-, and 12-Hr periods.

~_Automated Traffic Recordings (ATR)_ record the volume of motor vehicles traveling along a particular road, measures of travel speeds, and approximations of the class of the vehicles (motorcycle, 2-axle, large box truck, bus, etc). This type of count is conducted only along a street link/corridor, to gather data between two intersections or points of interest. This data is used in travel studies, as well as to review concerns about street use, speeding, and capacity. Counts are typically conducted for 12- & 24-Hr periods.

~_Pedestrian Counts (PED)_ record the volume of individual persons crossing a given street, whether at an existing intersection or a mid-block crossing. This data is used to review concerns about crossing safety, as well as for access analysis for points of interest. Counts are typically conducted for 2-, 4-, 11-, and 12-Hr periods.

~_Delay Studies (DEL)_ measure the delay experienced by motor vehicles due to the effects of congestion. Counts are typically conducted for a 1-Hr period at a given intersection or point of intersecting vehicular traffic.

~_Gap Studies (GAP)_ record the number of gaps which are typically present between groups of vehicles traveling through an intersection or past a point on a street. This data is used to assess opportunities for pedestrians to cross the street and for analyses on vehicular “platooning”. Counts are typically conducted for a specific 1-Hr period at a single point of crossing.