Traffic count data downloaded from GDOT public map here: https://gdottrafficdata.drakewell.com/publicmultinodemap.aspRetrieved Annual Statistics Reports: "All Station AADT and Truck Percent Statistics." Mapped by Lat/Long field.Retrieved and rehosted for staff use and overlay on city maps on 12/14/2018."The Georgia Department of Transportation’s Traffic Analysis and Data Application (TADA!) website presents data collected from the Georgia Traffic Monitoring Program located on the public roads in Georgia. The Website uses a dynamic mapping interface to allow the User to access data from the map as well as in a variety of report, graph, and data export formats."

This application serves as an index for traffic counts and provides some basic information; however, full reports and details of counts can be requested by Open Records Requests for a given location. Email questions about the application to GIS@Sandyspringsga.gov

Important Note: This item is in mature support as of June 2023 and will be retired in December 2025.This layer shows traffic counts in the United States in a multiscale map. Traffic counts are widely used for site selection by real estate firms and franchises. Traffic counts are also used by departments of transportation for highway funding. This map is best viewed at large scales where you can click on each point to access up to five different traffic counts over time. At medium to small scales, comparisons along major roads are possible. The Business Basemap has been added to provide context at medium and small scales. It shows the location of businesses in the United States and helps to understand where and why traffic counts are collected and used. The pop-up is configured to display the following information:The most recent traffic countThe street name where the count was collectedThey type of count that was taken. See the methodology document for definitions of count types such as AADT - Average Annual Daily Traffic. Traffic Counts seasonally adjusted to represent the average day of the year. AADT counts represent counts taken Sunday—Saturday.A graph displaying up to five traffic counts taken at the same location over time. Permitted use of this data is covered in the DATA section of the Esri Master Agreement (E204CW) and these supplemental terms.

Georgia_Average_Annual_Daily_Trafffic_2022: Traffic data for selected Georgia road segments between 2020-222. Data obtained from GDOT in 2022 and updated in late 2023. Data attributes include AADT (average annual daily traffic), single-unit truck AADT, combo-unit truck AADT, peak % single-unit AADT, peak % combo-unit AADT. https://www.dot.ga.gov/DS/DataRegional Traffic Counts 2019-2022: This layer shows traffic counts in the greater Chattanooga region compiled by ESRI. Traffic counts are widely used by departments of transportation for highway funding or planning purposes.GaRoad Network Truck 2020: Traffic data for selected Georgia road segments in 2020. Data obtained from GDOT in May 2022. Data attributes include AADT (average annual daily traffic), single-unit truck AADT, combo-unit truck AADT, peak % single-unit AADT, peak % combo-unit AADT. https://www.dot.ga.gov/DS/DataTN Road Network Traffic 2022: Traffic data for selected TN road segments in 2020-2022. Data obtained from TDOT in May 2022 and updated in late 2023. Data attributes include AADT (average annual daily traffic), single-unit truck AADT, combo-unit truck AADT, peak % single-unit AADT, peak % combo-unit AADT.

Georgia_Average_Annual_Daily_Trafffic_2022: Traffic data for selected Georgia road segments between 2020-222. Data obtained from GDOT in 2022 and updated in late 2023. Data attributes include AADT (average annual daily traffic), single-unit truck AADT, combo-unit truck AADT, peak % single-unit AADT, peak % combo-unit AADT. https://www.dot.ga.gov/DS/DataRegional Traffic Counts 2019-2022: This layer shows traffic counts in the greater Chattanooga region compiled by ESRI. Traffic counts are widely used by departments of transportation for highway funding or planning purposes.GaRoad Network Truck 2020: Traffic data for selected Georgia road segments in 2020. Data obtained from GDOT in May 2022. Data attributes include AADT (average annual daily traffic), single-unit truck AADT, combo-unit truck AADT, peak % single-unit AADT, peak % combo-unit AADT. https://www.dot.ga.gov/DS/DataTN Road Network Traffic 2022: Traffic data for selected TN road segments in 2020-2022. Data obtained from TDOT in May 2022 and updated in late 2023. Data attributes include AADT (average annual daily traffic), single-unit truck AADT, combo-unit truck AADT, peak % single-unit AADT, peak % combo-unit AADT.

Georgia: Number of 20-foot containers passing through the ports: The latest value from 2021 is 0.4 million containers, a decline from 0.49 million containers in 2020. In comparison, the world average is 8.14 million containers, based on data from 102 countries. Historically, the average for Georgia from 2007 to 2021 is 0.34 million containers. The minimum value, 0.18 million containers, was reached in 2007 while the maximum of 0.6 million containers was recorded in 2019.

This layer contains points that highlight traffic counting locations with their associated traffic count observations over several years since 2013 within the City of Johns Creek, GA.Data Note: In 2020, only one direction of traffic was recorded for locations #19, 28, and 34. In the data contained in this layer, that single direction count was duplicated to make year to year comparisons more accurate.

This dataset contains traffic counts along major roads in Cobb County, Georgia.

Abstract

The evaluation uses three methodologies to rigorously evaluate the causal impact of the program on outcomes. The first is a difference-in-difference methodology, whereby the project roads are matched to a set of similar comparison roads where no intervention has taken place. These comparison roads are chosen from a number of potential candidates using a propensity score matching technique. The difference-in-difference analysis thus compares traffic counts as well as socioeconomic outcomes for residents of communities located near the project roads to those of residents of communities located near the comparison roads. Secondly, the evaluation incorporates a continuous treatment approach. Project impact is modeled in a dose-response framework, so that communities nearer the project roads are assumed to experience greater impacts than those more distant. Finally, the evaluation estimates a matched difference-indifference model, using propensity score matching to improve the comparability between the treatment and comparison groups. Combining these three approaches allows for results from each to be compared in order to ensure a robust set of findings that is not dependent on the assumptions of one particular modeling approach.

Geographic coverage

The Samtskhe-Javakheti region

Analysis unit

Individuals, households

Universe

To collect the data, enumerators travelled to each settlement and worked with local authorities to identify a small group of individuals who were identified as knowledgeable about conditions in the settlement.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample for the first round used the 2002 Census to identify a sampling frame of 732 settlements around either the project or comparison roads, of which 690 were surveyed. The sample size was increased for the second and third rounds, which conducted surveys in all settlements that met at least one of the following criteria: settlements along the SJ Road; settlements along comparison roads where traffic counts are conducted; settlements included in the Integrated Household Survey (IHHS) that the evaluation uses to evaluate household-level outcomes, and any other village that was included in the baseline. The second and third rounds each included 960 settlements.

Our approach to selecting the comparison roads uses the technique of Propensity Score Matching (PSM) to identify eight comparison road segments to be included in the analysis. The comparison roads were selected from an inventory of 117 road segments for which data on a variety of characteristics was available from RDMED, the Georgian government roads agency. Our application of PSM in this case is to estimate a logistic regression model of the probability that a road is part of the treatment group as a function of observable characteristics. We then calculate the predicted probability (or propensity score) that a road segment is part of the treatment group for each of the eight treatment roads and 117 potential comparison roads using these estimated regression coefficients. Finally, each of the eight treatment roads is matched to a single comparison road for which the propensity score is the closest in value from among the 117 potential comparison roads.

GE: Road Fatalities: 30 days data was reported at 444.000 Person in 2024. This records an increase from the previous number of 434.000 Person for 2023. GE: Road Fatalities: 30 days data is updated yearly, averaging 505.500 Person from Dec 1995 (Median) to 2024, with 24 observations. The data reached an all-time high of 867.000 Person in 2008 and a record low of 430.000 Person in 2022. GE: Road Fatalities: 30 days data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Georgia – Table GE.OECD.ITF: Road Traffic and Road Accident Fatalities: Non OECD Member: Annual. [COVERAGE] Number of road fatalities is defined as the number of road deaths in the 30 days following the accident. [STAT_CONC_DEF] In 1994 and between 2001Q4 and 2006, data are not available. In 1995 and since 2009, monthly data are not available.

Georgia_Average_Annual_Daily_Trafffic_2022: Traffic data for selected Georgia road segments between 2020-222. Data obtained from GDOT in 2022 and updated in late 2023. Data attributes include AADT (average annual daily traffic), single-unit truck AADT, combo-unit truck AADT, peak % single-unit AADT, peak % combo-unit AADT. https://www.dot.ga.gov/DS/DataRegional Traffic Counts 2019-2022: This layer shows traffic counts in the greater Chattanooga region compiled by ESRI. Traffic counts are widely used by departments of transportation for highway funding or planning purposes.GaRoad Network Truck 2020: Traffic data for selected Georgia road segments in 2020. Data obtained from GDOT in May 2022. Data attributes include AADT (average annual daily traffic), single-unit truck AADT, combo-unit truck AADT, peak % single-unit AADT, peak % combo-unit AADT. https://www.dot.ga.gov/DS/DataTN Road Network Traffic 2022: Traffic data for selected TN road segments in 2020-2022. Data obtained from TDOT in May 2022 and updated in late 2023. Data attributes include AADT (average annual daily traffic), single-unit truck AADT, combo-unit truck AADT, peak % single-unit AADT, peak % combo-unit AADT.

This layer contains all aspects of the physical traffic signal infrastructure present in the City of Johns Creek, GA.Traffic signal heads: actual traffic signals in the CityLight sign locations: locations of all lighted signsSignal masts and wires: locations of all mast arms and wires that hold traffic signal heads and other signagePedestrian controls and signals: locations of all pedestrian controls and signalsTraffic cameras: locations of all traffic camerasSignal cabinets: locations of all signal cabinets containing ITS infrastructureTraffic counting locations: locations of all traffic counting infrastrucutureTraffic signal pucks: locations of all traffic pucks that have been installed

Georgia GE: Mortality Caused by Road Traffic Injury: per 100,000 People data was reported at 11.600 Number in 2015. This records a decrease from the previous number of 16.600 Number for 2010. Georgia GE: Mortality Caused by Road Traffic Injury: per 100,000 People data is updated yearly, averaging 12.050 Number from Dec 2000 (Median) to 2015, with 4 observations. The data reached an all-time high of 16.600 Number in 2010 and a record low of 10.800 Number in 2000. Georgia GE: Mortality Caused by Road Traffic Injury: per 100,000 People data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Georgia – Table GE.World Bank: Health Statistics. Mortality caused by road traffic injury is estimated road traffic fatal injury deaths per 100,000 population.; ; World Health Organization, Global Status Report on Road Safety.; Weighted average;

Container port traffic (TEU: 20 foot equivalent units) in Georgia was reported at 401269 in 2021, according to the World Bank collection of development indicators, compiled from officially recognized sources. Georgia - Container port traffic (TEU: 20 foot equivalent units) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Georgia GE: Container Port Traffic: TEU (20 Foot Equivalent Units) data was reported at 222,000.000 TEU in 2017. This stayed constant from the previous number of 222,000.000 TEU for 2016. Georgia GE: Container Port Traffic: TEU (20 Foot Equivalent Units) data is updated yearly, averaging 222,000.000 TEU from Dec 2007 (Median) to 2017, with 11 observations. The data reached an all-time high of 256,000.000 TEU in 2014 and a record low of 181,613.000 TEU in 2009. Georgia GE: Container Port Traffic: TEU (20 Foot Equivalent Units) data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Georgia – Table GE.World Bank.WDI: Transportation. Port container traffic measures the flow of containers from land to sea transport modes., and vice versa, in twenty-foot equivalent units (TEUs), a standard-size container. Data refer to coastal shipping as well as international journeys. Transshipment traffic is counted as two lifts at the intermediate port (once to off-load and again as an outbound lift) and includes empty units.; ; UNCTAD (http://unctad.org/en/Pages/statistics.aspx); Sum;

This study aimed to fill a void in the research regarding police behavior by focusing on the formation and creation of cognitive suspicion by officers. The study also examined formal actions (stops) taken by the police pursuant to that suspicion. The study was conducted using observational research methods and collected quantitative and qualitative data on officer suspicion. Data were collected by observers who rode along with patrol officers from April 2002 to November 2002. Field observers used three major data collection instruments in order to gather as much relevant information as possible from a variety of sources and in diverse situations. The Officer Form was an overall evaluation of the officer's decision-making characteristics, Suspicion Forms captured information each time an incident occurred, and a Suspect Form was a compilation of data from the citizen who had the encounter with the officer. Additional documents included informed consent forms, a card detailing the language to be used for the initial contact with citizens, and hourly activity forms. Anytime a suspicion was formed or a formal action was taken after a suspicion was formed, the observer debriefed the officer as to his or her thoughts and elicited the officer's overall rating of the encounter. Data in this collection include general demographic characteristics of the officer and the suspect, as well as the area in which the suspicion was formed. Data was also gathered regarding what led the officer to form a suspicion, and why a person was or was not stopped.

Georgia Imports: HS: Locomotives, Traffic Signalling Equipment data was reported at 3,387.620 USD th in Jun 2018. This records a decrease from the previous number of 3,851.152 USD th for Mar 2018. Georgia Imports: HS: Locomotives, Traffic Signalling Equipment data is updated quarterly, averaging 2,419.305 USD th from Mar 1995 (Median) to Jun 2018, with 94 observations. The data reached an all-time high of 37,588.392 USD th in Mar 2013 and a record low of 0.000 USD th in Jun 1996. Georgia Imports: HS: Locomotives, Traffic Signalling Equipment data remains active status in CEIC and is reported by National Statistics Office of Georgia. The data is categorized under Global Database’s Georgia – Table GE.JA007: Imports: by Commodity Group: Harmonised System: Quarterly.

Freight Traffic: International: To India: Georgia data was reported at 0.400 Ton in 2014. This records a decrease from the previous number of 6.200 Ton for 2013. Freight Traffic: International: To India: Georgia data is updated yearly, averaging 3.300 Ton from Mar 2013 (Median) to 2014, with 2 observations. The data reached an all-time high of 6.200 Ton in 2013 and a record low of 0.400 Ton in 2014. Freight Traffic: International: To India: Georgia data remains active status in CEIC and is reported by Directorate General of Civil Aviation. The data is categorized under India Premium Database’s Transportation, Post and Telecom Sector – Table IN.TA038: Aviation Statistics: Freight Traffic: International: by Country: To India.

Georgia Exports: HS: Locomotives, Traffic Signalling Equipment data was reported at 958.295 USD th in Oct 2018. This records an increase from the previous number of 125.654 USD th for Sep 2018. Georgia Exports: HS: Locomotives, Traffic Signalling Equipment data is updated monthly, averaging 119.019 USD th from Jan 1995 (Median) to Oct 2018, with 286 observations. The data reached an all-time high of 12,600.543 USD th in Nov 2013 and a record low of 0.000 USD th in Jun 2016. Georgia Exports: HS: Locomotives, Traffic Signalling Equipment data remains active status in CEIC and is reported by National Statistics Office of Georgia. The data is categorized under Global Database’s Georgia – Table GE.JA001: Exports: by Commodity Group: Harmonised System.

This dataset contains the raw traffic data from sensors located on I-95 at two locations in Georgia as well as analysis of the raw data for trends key perofrmance measures such as speed and flow rate. These data were used in the research for STRIDE Project P2 "Development of Guidance for Scheduling of Freeway Work Zones to Minimize Congestion Impacts" and described in the STRIDE Final Project for this project.