Ticon's research

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Traffic Monitoring As a Tool For Operation Excellence Control

Application of traffic data analytics is essential for both new business development and optimization of the underperforming locations, enabling businesses to assess operational performance and anticipate potential disruptions before they affect profitability. Leveraging multi-year expertise in business site analysis, Ticon has developed an advanced tool for operational excellence monitoring-the Traffic Load Heatmap-which incorporates a number of parameters, including annual average daily traffic (AADT), traffic volume fluctuations, travel behavior, driver demographics, and more. By utilizing this tool, businesses can align employee shifts with anticipated customer demand, optimize inventory, and improve customer expectations. This data-driven methodology is particularly crucial for businesses highly dependent on traffic flow, such as convenience stores, gas stations, roadside quick-service restaurants (QSRs), and other similar retail locations, enabling the management to make evidence-based decisions that enhance efficiency, reduce costs associated with labor, and drive profitability.

Reevaluating Trade Area Analysis with Accurate Traffic and Highly Granular Demographics Data

Proper delineation of a trade area is crucial for both site selection and effective store operations. Unlike traditional methods, Ticon reevaluates the process of trade area analysis, integrating recent studies of traffic visitor rates and traffic flow demographics, to provide a more comprehensive and accurate trade area assessment. This innovative methodology moves beyond the conventional reliance on static metrics such as distance rings or drive-time polygons which often fail to capture the dynamic nature of customer behavior, traffic flow, and demographic composition. Instead, it redefines trade area segmentation by incorporating three distinct trade area elements: (1) the Immediate Trade Area (1-2 miles), characterized by the local visitors' demographics; (2) the Extended Trade Area (5-20 miles), characterized by the specifics of regional customers whose visitation patterns depend on site accessibility and competition; and (3) Passing Traffic, characterized by the demographics of travelers, derived from traffic flow data. Notably, the third component captures the factual visitors while the prior two indicate the location potential. By integrating demographic description with traffic patterns, this approach allows one to develop a detailed customer profile, enhance market demand analysis, and effectively tailor the product offering.

Traffic Flow Demographics - an Innovative Tool for Enhancing Accuracy in Business Site Evaluation and Customer Visit Projections

This study introduces a novel methodology for identifying the customers demographics that offers improved target audience definition and more reliable customers visit projections for convenience stores and other entities in the retail sector. Traditional methods for determining target audience rely on trade area analysis, neglecting the demographics of passing traffic flow. That is why traditional methods often fail to capture the full scope of potential customers, as businesses such as quick-service restaurants, convenience stores and gas stations depend more on passing traffic than on local population for their customer base. The findings offer a practical tool for real estate professionals, retailers and convenience store operators, empowering them to make more informed choices in site selection, enabling refined financial forecasts, supporting operational insights and broader strategic planning.

Application of Cross-Verified Multisource Data to Remediation of Inaccurate Detector Readings

This article looks at the limitations of using specific traffic data metrics in location intelligence tasks, and stresses the importance of understanding their accuracy to prevent mistakes and misinformation. It presents a case study of a commercial site analysis revealing differences between traffic counts from detectors and algorithmic calculations. The study proves that the measured data should be treated with caution, taking into account not only the equipment-related error. But the level of actual temporal and spatial coverage as well, because it is quite often insufficient due to high traffic pattern volatility.

Investigating Longevity in the US Using High-Resolution Data and Location Intelligence Tool

This research investigates the relationship between life expectancy and commonly recognized influential factors - income and education. By utilizing high-resolution data of various levels of granularity for these factors, we aim to provide a fresh perspective on assessment of locations and well-being of their residents, moving beyond the limitations of a traditional macro-averaging approach. The methodology involves an analysis of correlations between residents' life expectancy and income and education factors in three major US cities: Atlanta, a key transportation hub; Boston, known as a tech capital; and Los Angeles, famous for its vibrant media industry. This granular approach offers a detailed view of neighborhoods, mitigating the pitfalls of over-averaged data by analyzing 429 one-mile cells within a 10-mile radius from city centers. Although the findings confirmed the positive correlation between life expectancy and both median income and high education, we observed notable outliers and considerable dispersion in some of the investigated areas. These findings lead to the detailed analysis of the whole US territory with the use of 1-mile granular data. Said analysis revealed unexpected outliers for life expectancy in mid-income groups of population and provided a comprehensive basis for future research aimed at unraveling the complex interplay between socio-economic factors and health.

Exploring the Visitor Rate in the US Convenience Store & Gas Station Industry

This research aimed to investigate the relationship between number of customer visits to convenience stores, mostly with gas stations (a.k.a. actual customer trips or actual trips) and various influence factors, including traffic data, demographic indicators, competition, store revenue, and more, in order to gain a comprehensive understanding of the dynamics influencing visitation patterns of Americans in the convenience store industry. The study harnesses datasets from various sources, including a study conducted by a State DOT, supplemented by additional data from US Census Bureau, as well as retail loyalty mobile apps data providers, and revenue financial modeling by private institutions. The methodology employed involves a comprehensive analysis of the correlation between measured actual trips to c-stores and average daily traffic data, as well as an exploration of the impact of non-traffic parameters. The findings revealed a robust positive correlation between number of customer visits (actual trips) and average daily traffic (ADT) volumes on the road network around a c-store. The study further reveals the significant influence of population and median income parameters on visitation patterns. In contrast to industry practice of site evaluation that usually considers demographic and other parameters just in 5-mile radius or less, a significant influence of population and income characteristics at larger distances, up to 20 miles, had been proven. The practical implications of this research encompass augmenting site selection strategies, optimizing operations and management practices, and enhancing revenue forecasting capabilities for convenience stores. Comprehensive analysis of multiple factors that impact visitation patterns, coupled with the integration of diverse datasets, ensured the accuracy of visitor estimations.

Determining the Target Audience in the US Retail Market

This research aims to analyze the target audience estimation process in the convenience store and gas station industry and introduce an innovative tool, the Ticon Target Audience Index (TAI), to assist companies in understanding the representation of their target audience within specific locations. The study employs a comprehensive methodology that incorporates demographic segmentation analysis and income features analysis using data from multiple sources, including the US Census Bureau and specialized market research reports. The results reveal significant variations in the target audience index across different locations, highlighting varying growth opportunities for companies. The findings provide actionable insights for site selection, product offerings, and marketing strategies, enabling businesses to effectively cater to the needs of potential customers. The research emphasizes the importance of accurate and granular data in target audience estimation to avoid estimation errors and flawed decision-making. The practical implications of this study extend beyond the convenience store industry, and the developed tool has applicability in other sectors, such as retail and drugstores. The originality and value of this research lie in the integration of demographic segmentation, income analysis, and the development of the TAI tool. The paper is unique because there are few similar empirical studies focused on the US retail sector.

Field Verification of Ticon Traffic Flow Volume Estimation Accuracy

Accurate traffic flow volume estimation is pivotal for modern traffic management, urban planning, and policy decisions. Ticon strives to continuously test the accuracy of its traffic flow volume estimation algorithm. This study takes an in-depth look at Ticon's ongoing verification of methods and algorithms used by the company to achieve accurate results that allow us to provide our clients with reliable traffic flow volume estimation for exact locations of interest at any road, large or small.

All-Directional Approach to Traffic Signal Optimization

Despite enormous resources spent on traffic management hardware, the quality of traffic signal control is still below current requirements, causing traffic delays, environmental damages and economic harm. This paper describes high-quality optimization of the traffic signal management that considers not only actual traffic volumes in conflicting directions, but also technical and topological essentials of the intersections, as well as the regional specifics of driver behavior. This approach makes it possible to achieve tangible improvement of signalized intersection performance solely by intellectual effort, without investment in hardware upgrades.

Before-After Analysis as a Mobility Improvement Tool for Smart Cities

To assure that costly mobility improvement measures deliver satisfactory results to the stakeholders, Ticon proposes its proprietary tool for Before-After Analysis: TrafficScope™ that is not only provides 100% temporal and spatial coverage, but also uses independent data sources and does not hinge on ITS contractors. Therefore, even sophisticated analysis can be easily accessible and objective, which is important not only for transportation professionals, but also for municipal authorities or the local communities.

TrafficZoom™ & Dashboard Features

The attempts to reduce traffic congestion in the cities by restrictive measures don’t seem to achieve the expected results, for a variety of reasons. The paper describes Ticon’s approach to this problem as based on a proprietary technology that closes gap in mobility improvement workflow and makes the process effective and continuous.

Most Efficient Methods of Mobility Improvement Using Adaptive Traffic Signal Control Concept

To assure that costly mobility improvement measures deliver satisfactory results to the stakeholders, Ticon proposes its proprietary tool for Before-After Analysis: TrafficScope™ that is not only provides 100% temporal and spatial coverage, but also uses independent data sources and does not hinge on ITS contractors. Therefore, even sophisticated analysis can be easily accessible and objective, which is important not only for transportation professionals, but also for municipal authorities or the local communities.

Ticon Approach to Traffic Data Collection and Analysis

The relevance of timely, accurate and available traffic data is generally understood by the industry. This article reviews a number of case studies comparing the outcomes of different traffic data collection technologies applied to ITS tasks, with a conclusion that the quality and quantity of traffic data needs to be drastically extended – a challenge that Ticon methodology helps to overcome.

Impact of Traffic Volume Variations on Travel Delays as Illustrated by Pandemic Period Data

With mobility improvement in the focus of attention of professionals and general public, it is important to understand the causes and effects of various restrictive measures vs. traffic control quality enhancement. This report summarizes the results of Ticon study based on a two-year observation of traffic flows in 9 states of the US East Coast, and provides important actionable insights.

New Traffic Data Collection Technologies Require New Verification Methods

Data is the most important commodity in the modern, digitized world. This article reviews several persistent misconceptions about traffic data and provides professional guidance on its proper collection, interpretation, cross-verification and application.

Ticon Intraday Volumes

This article describes hardware-free technology that provides intraday traffic volume estimation with high accuracy, extremely large time coverage and superior consistency. Provided case studies demonstrate the differences between traffic flow parameter measurements by traditional detectors vs. hardware-free technology. These differences should be taken into consideration for achieving the best results in traffic data applications.

AADT Estimation by Various Methods: Accuracy and Reliability

AADT is widely used in transportation industry and for business planning. Nowadays AADT may be estimated both by traditional counters/detectors and hardware-free technologies. The article describes real accuracy and limitations of use for AADT values, estimated by various technologies, for practical applications.