In 2019, the Chinese marketplace Alibaba was the leading worldwide B2B e-commerce in terms of online traffic. The Alexa tool assessing the online traffic of websites put it on the top of the ranking, with a score of ***. The Russian Rosfirm and the U.S. platform Vinsuite followed in the ranking with a score of ***** and *****, respectively.

As of the second quarter of 2022, Shopee Philippines, an online department store and marketplace for retailers to sell their products, registered estimated monthly traffic of about ** million on its e-commerce website. Following by a considerable margin was Lazada, with an estimated online website traffic of roughly ** million visitors. Both companies lead the e-commerce market in the Philippines.

Annualized, Hourly and Classification count data for the TPB modeled region. Data are collected from state DOTs and processed by TPB staff.Layers IncludedAnnualized Traffic Volumes Historic AADT by Count Station This database contains the Annual Average Daily Traffic (AADT) estimates reported at permanent and short term counting stations in the TPB modeled region. Please note: Interstates in Virginia are typically represented by two stations (one in each direction) while Interstates in the other states are represented by one station. Therefore, the AADT estimates displayed for the stations on Virginia Intestates will be around half of the total for the directional roadway. The AADT estimates for recent years in this file are based on counts taken at the actual count station locations that are indicated by the station points. The AADT estimates for earlier years are based on volumes reported along roadway segments that the station points currently represent. Specific data sources for each state are listed below:District of ColumbiaAADT estimates since 2006 are based on counts taken at the station locations in the file for purpose of Federal HPMS reporting.AADT estimates prior to 2006 are based on Traffic Volume maps produced by DDOT (Formerly DC DPW).MarylandAADT estimates since 2000 are based on counts taken at the station locations in the file and reported by MD SHA.AADT estimates prior to 2000 are based on volumes reported by MD SHA in the Highway Location Reference documents and matched to links in the COG/TPB highway network. The volumes are shown at the count locations that currently represent those network links.VirginiaAADT estimates since 1997 are based on counts taken at the station locations in the file and reported by VDOT.AADT estimates prior to 1997 are based on volumes reported by VDOT in the Average Daily Traffic Volumes documents and matched to links in the COG/TPB highway network. The volumes are shown at the count locations that currently represent those network links.West VirginiaAADT estimates since 1999 are based on counts taken at the station locations in the file and reported by WV DOT.Traffic Counts by Network LinkThis layer was created by assigning the state DOT traffic counting station locations to their corresponding COG/TPB network links. Facility names and route numbers were added to the network. AADT Average Annual Daily Traffic (2010 - 2021), AAWDT Average Annual Weekday Daily Traffic (2010 - 2021) and Count Type (2010 - 2021) are included as well as Count Year (last year the link was counted). Count Type denotes the source of the count. Please note: for bi-directional roads, the AADT and AAWDT values for each location were divided in two and assigned to both network links that represent the Anode-Bnode direction and the Bnode-Anode direction. Therefore, in most cases the AADT/AAWDT values associated with an individual link in this network will be half of the AADT/AAWDT values reported at the associated individual count station point. Traffic Counts by External StationThis layer was created by placing points where major facilities cross the TPB Modeled Area boundary. In some cases, the external station represents more than one facility. The facility field indicates which road or roads the station represents. AADT and AAWDT estimates at external stations are provided for 2007 through 2023. Each external station is assigned to a state DOT traffic counting station(s). An effort was made to assign stations or combinations of stations that would come closest to measuring the traffic volume on each facility as it enters/exits the region. In some cases, these volumes are measured just inside the modeled area; in other cases, the volumes are measured just outside the modeled area. The external stations around the Baltimore Beltway are exceptions to this rule. These stations all measure the traffic just south of the Baltimore Beltway in order lessen the influence of traffic specific to Baltimore. AADT Average Annual Daily Traffic (2007 – 2023) and AAWDT Average Annual Weekday Daily Traffic (2007 – 2023) are included. Count Type denotes when the location was last counted. West Virginia does not report AAWDT, so the AADT values were increased by 5% to arrive at AAWDT estimates in West Virginia.

Annual average daily traffic is the total volume for the year divided by 365 days. The traffic count year is from October 1st through September 30th. Very few locations in California are actually counted continuously. Traffic Counting is generally performed by electronic counting instruments moved from location throughout the State in a program of continuous traffic count sampling. The resulting counts are adjusted to an estimate of annual average daily traffic by compensating for seasonal influence, weekly variation and other variables which may be present. Annual ADT is necessary for presenting a statewide picture of traffic flow, evaluating traffic trends, computing accident rates. planning and designing highways and other purposes.Traffic Census Program Page

In 2024, most of the global website traffic was still generated by humans, but bot traffic is constantly growing. Fraudulent traffic through bad bot actors accounted for 37 percent of global web traffic in the most recently measured period, representing an increase of 12 percent from the previous year. Sophistication of Bad Bots on the rise The complexity of malicious bot activity has dramatically increased in recent years. Advanced bad bots have doubled in prevalence over the past 2 years, indicating a surge in the sophistication of cyber threats. Simultaneously, the share of simple bad bots drastically increased over the last years, suggesting a shift in the landscape of automated threats. Meanwhile, areas like food and groceries, sports, gambling, and entertainment faced the highest amount of advanced bad bots, with more than 70 percent of their bot traffic affected by evasive applications. Good and bad bots across industries The impact of bot traffic varies across different sectors. Bad bots accounted for over 50 percent of the telecom and ISPs, community and society, and computing and IT segments web traffic. However, not all bot traffic is considered bad. Some of these applications help index websites for search engines or monitor website performance, assisting users throughout their online search. Therefore, areas like entertainment, food and groceries, and even areas targeted by bad bots themselves experienced notable levels of good bot traffic, demonstrating the diverse applications of benign automated systems across different sectors.

As of April 2020, it was estimated that the web traffic could increase by up to 25 percent in Argentina and 20 percent in Brazil, compared to the average prior to the COVID-19 outbreak. In Colombia and Ecuador, fixed-line internet traffic was expected to increase by 40 and 30 percent, respectively.

AADT represents current (most recent) Annual Average Daily Traffic on sampled road systems. This information is displayed using the Traffic Count Locations Active feature class as of the annual HPMS freeze in January. Historical AADT is found in another table. Please note that updates to this dataset are on an annual basis, therefore the data may not match ground conditions or may not be available for new roadways. Resource Contact: Christy Prentice, Traffic Forecasting & Analysis (TFA), http://www.dot.state.mn.us/tda/contacts.html#TFA

Check other metadata records in this package for more information on Annual Average Daily Traffic Locations Information.


Link to ESRI Feature Service:

Annual Average Daily Traffic Locations in Minnesota: Annual Average Daily Traffic Locations

This dataset is historical. For recent data, we recommend using https://chicagotraffictracker.com. -- Average Daily Traffic (ADT) counts are analogous to a census count of vehicles on city streets. These counts provide a close approximation to the actual number of vehicles passing through a given location on an average weekday. Since it is not possible to count every vehicle on every city street, sample counts are taken along larger streets to get an estimate of traffic on half-mile or one-mile street segments. ADT counts are used by city planners, transportation engineers, real-estate developers, marketers and many others for myriad planning and operational purposes. Data Owner: Transportation. Time Period: 2006. Frequency: A citywide count is taken approximately every 10 years. A limited number of traffic counts will be taken and added to the list periodically. Related Applications: Traffic Information Interactive Map (http://webapps.cityofchicago.org/traffic/).

The census count of vehicles on city streets is normally reported in the form of Average Daily Traffic (ADT) counts. These counts provide a good estimate for the actual number of vehicles on an average weekday at select street segments. Specific block segments are selected for a count because they are deemed as representative of a larger segment on the same roadway. ADT counts are used by transportation engineers, economists, real estate agents, planners, and others professionals for planning and operational analysis. The frequency for each count varies depending on City staff’s needs for analysis in any given area. This report covers the counts taken in our City during the past 12 years approximately.

This dataset contains estimates of the average number of vehicles that used roads throughout the City of Detroit. Each record indicates the Annual Average Daily Traffic (AADT) and Commercial Annual Average Daily Traffic (CAADT) for a road segment, where the road segment is located, and other characteristics. This data is derived from Michigan Department of Transportation's (MDOT) Open Data Portal. SEMCOG was the source for speed limits and number of lanes.

The primary measure, Annual Average Daily Traffic (AADT), is the estimated mean daily traffic volume for all types of vehicles. Commercial Annual Average Daily Traffic (CAADT) is the estimated mean daily traffic volume for commercial vehicles, a subset of vehicles included in the AADT. The Route ID is an identifier for each road in Detroit (e.g., Woodward Ave). Routes are divided into segments by features such as cross streets, and Location ID's are used to uniquely identify those segments. Along with traffic volume, each record also states the number of lanes, the posted speed limit, and the type of road (e.g., Trunkline or Ramp) based on the Federal Highway Administration (FHWA) functional classification system.

According to MDOT's Traffic Monitoring Program a commercial vehicle would be anything Class 4 and up in the FHWA vehicle classification system. This includes vehicles such as buses, semi-trucks, and personal recreational vehicles (i.e., RVs or campers). Methods used to determine traffic volume vary by site, and may rely on continuous monitoring or estimates based on short-term studies. Approaches to vehicle classification similarly vary, depending on the equipment used at a site, and may consider factors such as vehicle weight and length between axles.

For more information, please visit MDOT Traffic Monitoring Program.

This dataset contains the current estimated speed for about 1250 segments covering 300 miles of arterial roads. For a more detailed description, go to: http://bit.ly/Q9AZAD.

The Chicago Traffic Tracker estimates traffic congestion on Chicago’s arterial streets (nonfreeway streets) in real-time by continuously monitoring and analyzing GPS traces received from Chicago Transit Authority (CTA) buses. Two types of congestion estimates are produced every ten minutes: 1) by Traffic Segments and 2) by Traffic Regions or Zones. Congestion estimate by traffic segments gives the observed speed typically for one-half mile of a street in one direction of traffic.

Traffic Segment level congestion is available for about 300 miles of principal arterials. Congestion by Traffic Region gives the average traffic condition for all arterial street segments within a region. A traffic region is comprised of two or three community areas with comparable traffic patterns. 29 regions are created to cover the entire city (except O’Hare airport area). This dataset contains the current estimated speed for about 1250 segments covering 300 miles of arterial roads. There is much volatility in traffic segment speed. However, the congestion estimates for the traffic regions remain consistent for relatively longer period. Most volatility in arterial speed comes from the very nature of the arterials themselves. Due to a myriad of factors, including but not limited to frequent intersections, traffic signals, transit movements, availability of alternative routes, crashes, short length of the segments, etc. speed on individual arterial segments can fluctuate from heavily congested to no congestion and back in a few minutes. The segment speed and traffic region congestion estimates together may give a better understanding of the actual traffic conditions.

This database contains the Annual Average Daily Traffic (AADT) estimates reported at permanent and short term counting stations in the TPB modeled region. Please note: Interstates in Virginia are typically represented by two stations (one in each direction) while Interstates in the other states are represented by one station. Therefore, the AADT estimates displayed for the stations on Virginia Intestates will be around half of the total for the directional roadway. The AADT estimates for recent years in this file are based on counts taken at the actual count station locations that are indicated by the station points. The AADT estimates for earlier years are based on volumes reported along roadway segments that the station points currently represent. Specific data sources for each state are listed below:District of ColumbiaAADT estimates since 2006 are based on counts taken at the station locations in the file for purpose of Federal HPMS reporting.AADT estimates prior to 2006 are based on Traffic Volume maps produced by DDOT (Formerly DC DPW).MarylandAADT estimates since 2000 are based on counts taken at the station locations in the file and reported by MD SHA.AADT estimates prior to 2000 are based on volumes reported by MD SHA in the Highway Location Reference documents and matched to links in the COG/TPB highway network. The volumes are shown at the count locations that currently represent those network links.VirginiaAADT estimates since 1997 are based on counts taken at the station locations in the file and reported by VDOT.AADT estimates prior to 1997 are based on volumes reported by VDOT in the Average Daily Traffic Volumes documents and matched to links in the COG/TPB highway network. The volumes are shown at the count locations that currently represent those network links.West VirginiaAADT estimates since 1999 are based on counts taken at the station locations in the file and reported by WV DOT.

Linear network representing the estimated traffic flows for roads and highways managed by the Ministry of Transport and Sustainable Mobility (MTMD). These flows are obtained using a statistical estimation method applied to data from more than 4,500 collection sites spread over the main roads of Quebec. It includes DJMA (annual average daily flow), DJME (summer average daily flow), DJME (summer average daily flow (June, July, August, September) and DJMH (average daily winter flow (December, January, February, March) as well as other traffic data. It is important to note that these values are calculated for total traffic directions. Interactive map: Some files are accessible by querying a section of traffic à la carte with a click (the file links are displayed in the descriptive table that is displayed when clicking): • Historical aggregated data (PDF) • Annual reports for permanent sites (PDF and Excel) • Hourly data (hourly average per weekday per month) (Excel) • Annual reports for permanent sites (PDF and Excel) • Hourly data (hourly average per weekday per month) (Excel)**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

This dataset contains the current estimated speed for about 1250 segments covering 300 miles of arterial roads. For a more detailed description, go to: http://bit.ly/Q9AZAD.

The Chicago Traffic Tracker estimates traffic congestion on Chicago’s arterial streets (nonfreeway streets) in real-time by continuously monitoring and analyzing GPS traces received from Chicago Transit Authority (CTA) buses. Two types of congestion estimates are produced every ten minutes: 1) by Traffic Segments and 2) by Traffic Regions or Zones. Congestion estimate by traffic segments gives the observed speed typically for one-half mile of a street in one direction of traffic.

Traffic Segment level congestion is available for about 300 miles of principal arterials. Congestion by Traffic Region gives the average traffic condition for all arterial street segments within a region. A traffic region is comprised of two or three community areas with comparable traffic patterns. 29 regions are created to cover the entire city (except O’Hare airport area). This dataset contains the current estimated speed for about 1250 segments covering 300 miles of arterial roads. There is much volatility in traffic segment speed. However, the congestion estimates for the traffic regions remain consistent for relatively longer period. Most volatility in arterial speed comes from the very nature of the arterials themselves. Due to a myriad of factors, including but not limited to frequent intersections, traffic signals, transit movements, availability of alternative routes, crashes, short length of the segments, etc. speed on individual arterial segments can fluctuate from heavily congested to no congestion and back in a few minutes. The segment speed and traffic region congestion estimates together may give a better understanding of the actual traffic conditions.

This dataset contains estimates of the average number of vehicles that used roads throughout the City of Detroit. Each record indicates the Annual Average Daily Traffic (AADT) and Commercial Annual Average Daily Traffic (CAADT) for a road segment, where the road segment is located, and other characteristics. This data is derived from Michigan Department of Transportation's (MDOT) Open Data Portal. SEMCOG was the source for speed limits and number of lanes.

The primary measure, Annual Average Daily Traffic (AADT), is the estimated mean daily traffic volume for all types of vehicles. Commercial Annual Average Daily Traffic (CAADT) is the estimated mean daily traffic volume for commercial vehicles, a subset of vehicles included in the AADT. The Route ID is an identifier for each road in Detroit (e.g., Woodward Ave). Routes are divided into segments by features such as cross streets, and Location ID's are used to uniquely identify those segments. Along with traffic volume, each record also states the number of lanes, the posted speed limit, and the type of road (e.g., Trunkline or Ramp) based on the Federal Highway Administration (FHWA) functional classification system.

According to MDOT's Traffic Monitoring Program a commercial vehicle would be anything Class 4 and up in the FHWA vehicle classification system. This includes vehicles such as buses, semi-trucks, and personal recreational vehicles (i.e., RVs or campers). Methods used to determine traffic volume vary by site, and may rely on continuous monitoring or estimates based on short-term studies. Approaches to vehicle classification similarly vary, depending on the equipment used at a site, and may consider factors such as vehicle weight and length between axles.

For more information, please visit MDOT Traffic Monitoring Program.

This dataset contains estimates of the average number of vehicles that used roads throughout the City of Detroit. Each record indicates the Annual Average Daily Traffic (AADT) and Commercial Annual Average Daily Traffic (CAADT) for a road segment, where the road segment is located, and other characteristics. This data is derived from Michigan Department of Transportation's (MDOT) Open Data Portal. SEMCOG was the source for speed limits and number of lanes.

The primary measure, Annual Average Daily Traffic (AADT), is the estimated mean daily traffic volume for all types of vehicles. Commercial Annual Average Daily Traffic (CAADT) is the estimated mean daily traffic volume for commercial vehicles, a subset of vehicles included in the AADT. The Route ID is an identifier for each road in Detroit (e.g., Woodward Ave). Routes are divided into segments by features such as cross streets, and Location ID's are used to uniquely identify those segments. Along with traffic volume, each record also states the number of lanes, the posted speed limit, and the type of road (e.g., Trunkline or Ramp) based on the Federal Highway Administration (FHWA) functional classification system.

According to MDOT's Traffic Monitoring Program a commercial vehicle would be anything Class 4 and up in the FHWA vehicle classification system. This includes vehicles such as buses, semi-trucks, and personal recreational vehicles (i.e., RVs or campers). Methods used to determine traffic volume vary by site, and may rely on continuous monitoring or estimates based on short-term studies. Approaches to vehicle classification similarly vary, depending on the equipment used at a site, and may consider factors such as vehicle weight and length between axles.

For more information, please visit MDOT Traffic Monitoring Program.

Level of Traffic Stress (LTS) is a road classification technique based on the comfort of bicyclists in the traffic stream. One commonly used LTS framework ranges from LTS 1 to LTS 4, classifying road segments that would be comfortable for any bicyclist to segments that only the fearless would brave on a bicycle, respectively. Over the past several years, a variety of papers have been written about different methods for assigning LTS values to road segments and how these LTS values have been used to inform planning and infrastructure decisions through connectivity analysis. Since demand modeling for bicycling is absent from many regional travel demand models (including DVRPC’s), a measure of the potential use of a bicycle facility is difficult to obtain. Instead of focusing on demand, bicycle network connectivity is often used as an accessibility metric. Much of the connectivity analysis in prior research compared existing conditions to a “bike-plan buildout” scenario, or similar, to compare project merits. This project, instead, provides an example of a different type of LTS and network connectivity application. For detailed information about the data in this layer please go to the DVRPC Bicycle LTS and Connectivity Analysis Documentation Explore and view analyze results using the Bicycle Level of Traffic Stress (LTS) and Connectivity Analysis Tool - This regional screening tool was developed to help identify and rank roads where bicycle facility improvements would have the greatest local and regional connectivity benefit to the low-stress bicycle network. LTS is a road classification scheme based on the estimated comfort of bicyclists in the traffic stream. DVRPC’s LTS assignment is based on the number of lanes, effective vehicle speed, and the presence and type of bicycle facility on the road segment. attribute description data type possible values/ ranges gid unique identifier Long length segment length double totnumlane Total number of lanes long 14-Jan speed_lts estimated vehicle travel speed long 0-75 typeno roadway type from DVRPC's regional travel demand model text linklts level of traffic stress factor used to calculate shortest paths double slope_perc percent slope of segment double slopefac multiplier used to account for slope when calculating shortest paths double 0, .37, 1.2, or 3.24 lts_score Assigned level of traffic stress text 1, 2, 3, 4 bikefacili type of bicycle facility on segment text Bike Lane/ Bike Route/ Buffered Bike Lane/ No Accomodation/ Off-road Trail/Path / Protected Bike Lane/ Sharrows main_results indicates if a segment is part of the top 50 percent of LTS 3 segments in terms of the number of low stress paths it could enable if improved text Y = yes or

This dataset contains estimates of the average number of vehicles that used roads throughout the City of Detroit. Each record indicates the Annual Average Daily Traffic (AADT) and Commercial Annual Average Daily Traffic (CAADT) for a road segment, where the road segment is located, and other characteristics. This data is derived from Michigan Department of Transportation's (MDOT) Open Data Portal. SEMCOG was the source for speed limits and number of lanes.

The primary measure, Annual Average Daily Traffic (AADT), is the estimated mean daily traffic volume for all types of vehicles. Commercial Annual Average Daily Traffic (CAADT) is the estimated mean daily traffic volume for commercial vehicles, a subset of vehicles included in the AADT. The Route ID is an identifier for each road in Detroit (e.g., Woodward Ave). Routes are divided into segments by features such as cross streets, and Location ID's are used to uniquely identify those segments. Along with traffic volume, each record also states the number of lanes, the posted speed limit, and the type of road (e.g., Trunkline or Ramp) based on the Federal Highway Administration (FHWA) functional classification system.

According to MDOT's Traffic Monitoring Program a commercial vehicle would be anything Class 4 and up in the FHWA vehicle classification system. This includes vehicles such as buses, semi-trucks, and personal recreational vehicles (i.e., RVs or campers). Methods used to determine traffic volume vary by site, and may rely on continuous monitoring or estimates based on short-term studies. Approaches to vehicle classification similarly vary, depending on the equipment used at a site, and may consider factors such as vehicle weight and length between axles.

For more information, please visit MDOT Traffic Monitoring Program.

This dataset contains estimates of the average number of vehicles that used roads throughout the City of Detroit in 2022. Each record indicates the Annual Average Daily Traffic (AADT) and Commercial Annual Average Daily Traffic (CAADT) for a road segment, where the road segment is located, and other characteristics. This data is derived from Michigan Department of Transportation's (MDOT) Open Data Portal. SEMCOG was the source for speed limits and number of lanes.The primary measure, Annual Average Daily Traffic (AADT), is the estimated mean daily traffic volume for all types of vehicles. Commercial Annual Average Daily Traffic (CAADT) is the estimated mean daily traffic volume for commercial vehicles, a subset of vehicles included in the AADT. The Route ID is an identifier for each road in Detroit (e.g., Woodward Ave). Routes are divided into segments by features such as cross streets, and Location ID's are used to uniquely identify those segments. Along with traffic volume, each record also states the number of lanes, the posted speed limit, and the type of road (e.g., Trunkline or Ramp) based on the Federal Highway Administration (FHWA) functional classification system.According to MDOT's Traffic Monitoring Program a commercial vehicle would be anything Class 4 and up in the FHWA vehicle classification system. This includes vehicles such as buses, semi-trucks, and personal recreational vehicles (i.e., RVs or campers). Methods used to determine traffic volume vary by site, and may rely on continuous monitoring or estimates based on short-term studies. Approaches to vehicle classification similarly vary, depending on the equipment used at a site, and may consider factors such as vehicle weight and length between axles.For more information, please visit MDOT Traffic Monitoring Program.

This dataset contains estimates of the average number of vehicles that used roads throughout the City of Detroit. Each record indicates the Annual Average Daily Traffic (AADT) and Commercial Annual Average Daily Traffic (CAADT) for a road segment, where the road segment is located, and other characteristics. This data is derived from Michigan Department of Transportation's (MDOT) Open Data Portal. SEMCOG was the source for speed limits and number of lanes.

The primary measure, Annual Average Daily Traffic (AADT), is the estimated mean daily traffic volume for all types of vehicles. Commercial Annual Average Daily Traffic (CAADT) is the estimated mean daily traffic volume for commercial vehicles, a subset of vehicles included in the AADT. The Route ID is an identifier for each road in Detroit (e.g., Woodward Ave). Routes are divided into segments by features such as cross streets, and Location ID's are used to uniquely identify those segments. Along with traffic volume, each record also states the number of lanes, the posted speed limit, and the type of road (e.g., Trunkline or Ramp) based on the Federal Highway Administration (FHWA) functional classification system.

According to MDOT's Traffic Monitoring Program a commercial vehicle would be anything Class 4 and up in the FHWA vehicle classification system. This includes vehicles such as buses, semi-trucks, and personal recreational vehicles (i.e., RVs or campers). Methods used to determine traffic volume vary by site, and may rely on continuous monitoring or estimates based on short-term studies. Approaches to vehicle classification similarly vary, depending on the equipment used at a site, and may consider factors such as vehicle weight and length between axles.

For more information, please visit MDOT Traffic Monitoring Program.