Dissolved ADT created for improved labeling. Updated from ADT_COMP_2024Annual Average Daily Traffic volumes (AADT) is a product of IDOT’s Traffic Count Program. Counts from this program range in duration from data continuously recorded at permanent count stations to thousands of coverage count locations that are counted for a 24-hour period throughout the year. More information about IDOT’s Traffic Count Program can be found at the Illinois Travel Statistics site.

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/).

Annual Average Daily Traffic volumes (AADT) is a product of IDOT’s Traffic Count Program. Counts from this program range in duration from data continuously recorded at permanent count stations to thousands of coverage count locations that are counted for a 24-hour period throughout the year. More information about IDOT’s Traffic Count Program can be found at the Illinois Travel Statistics site.

Annual Average Daily Traffic volumes (AADT) is a product of IDOT’s Traffic Count Program. Counts from this program range in duration from data continuously recorded at permanent count stations to thousands of coverage count locations that are counted for a 24-hour period throughout the year. More information about IDOT’s Traffic Count Program can be found at the Illinois Travel Statistics site.

This dataset accompanies the paper "STREETS: A Novel Camera Network Dataset for Traffic Flow" at Neural Information Processing Systems (NeurIPS) 2019. Included are: *Over four million still images form publicly accessible cameras in Lake County, IL. The images were collected across 2.5 months in 2018 and 2019. *Directed graphs describing the camera network structure in two communities in Lake County. *Documented non-recurring traffic incidents in Lake County coinciding with the 2018 data. *Traffic counts for each day of images in the dataset. These counts track the volume of traffic in each community. *Other annotations and files useful for computer vision systems. Refer to the accompanying "readme.txt" or "readme.pdf" for further details.

This dataset details traffic counts in the Chicago Southland from 2010 thru 1998. This dataset is a mashup of IDOT, County, and CMAP traffic counts

Annual Average Daily Traffic volumes (AADT) is a product of IDOT’s Traffic Count Program. Counts from this program range in duration from data continuously recorded at permanent count stations to thousands of coverage count locations that are counted for a 24-hour period throughout the year. More information about IDOT’s Traffic Count Program can be found at the Illinois Travel Statistics site.

2010 Annual Average Daily Traffic (AADT) volumes as well as the AM and PM peak volumes for the Illinois Tollway. The beginning and ending milepost for each segment are provided as well as the coordinates for the center of each segment.

Annual Average Daily Traffic volumes (AADT) is a product of IDOT’s Traffic Count Program. Counts from this program range in duration from data continuously recorded at permanent count stations to thousands of coverage count locations that are counted for a 24-hour period throughout the year. More information about IDOT’s Traffic Count Program can be found at the Illinois Travel Statistics site.

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Primary roads are generally divided, limited-access highways within the interstate highway system or under State management, and are distinguished by the presence of interchanges. These highways are accessible by ramps and may include some toll highways. The MAF/TIGER Feature Classification Code (MTFCC) is S1100 for primary roads. Secondary roads are main arteries, usually in the U.S. Highway, State Highway, and/or County Highway system. These roads have one or more lanes of traffic in each direction, may or may not bedivided, and usually have at-grade intersections with many other roads and driveways. They usually have both a local name and a route number. The MAF/TIGER Feature Classification Code (MTFCC) is S1200 for secondary roads.

Annual Average Daily Traffic volumes (AADT) is a product of IDOT’s Traffic Count Program. Counts from this program range in duration from data continuously recorded at permanent count stations to thousands of coverage count locations that are counted for a 24-hour period throughout the year. More information about IDOT’s Traffic Count Program can be found at the Illinois Travel Statistics site.

This dataset contains information about vehicles (or units as they are identified in crash reports) involved in a traffic crash. This dataset should be used in conjunction with the traffic Crash and People dataset available in the portal. “Vehicle” information includes motor vehicle and non-motor vehicle modes of transportation, such as bicycles and pedestrians. Each mode of transportation involved in a crash is a “unit” and get one entry here. Each vehicle, each pedestrian, each motorcyclist, and each bicyclist is considered an independent unit that can have a trajectory separate from the other units. However, people inside a vehicle including the driver do not have a trajectory separate from the vehicle in which they are travelling and hence only the vehicle they are travelling in get any entry here. This type of identification of “units” is needed to determine how each movement affected the crash. Data for occupants who do not make up an independent unit, typically drivers and passengers, are available in the People table. Many of the fields are coded to denote the type and location of damage on the vehicle. Vehicle information can be linked back to Crash data using the “CRASH_RECORD_ID” field. Since this dataset is a combination of vehicles, pedestrians, and pedal cyclists not all columns are applicable to each record. Look at the Unit Type field to determine what additional data may be available for that record.

The Chicago Police Department reports crashes on IL Traffic Crash Reporting form SR1050. The crash data published on the Chicago data portal mostly follows the data elements in SR1050 form. The current version of the SR1050 instructions manual with detailed information on each data elements is available here.

Change 11/21/2023: We have removed the RD_NO (Chicago Police Department report number) for privacy reasons.

Crash data shows information about each traffic crash on city streets within the City of Chicago limits and under the jurisdiction of Chicago Police Department (CPD). Data are shown as is from the electronic crash reporting system (E-Crash) at CPD, excluding any personally identifiable information. Records are added to the data portal when a crash report is finalized or when amendments are made to an existing report in E-Crash. Data from E-Crash are available for some police districts in 2015, but citywide data are not available until September 2017. About half of all crash reports, mostly minor crashes, are self-reported at the police district by the driver(s) involved and the other half are recorded at the scene by the police officer responding to the crash. Many of the crash parameters, including street condition data, weather condition, and posted speed limits, are recorded by the reporting officer based on best available information at the time, but many of these may disagree with posted information or other assessments on road conditions. If any new or updated information on a crash is received, the reporting officer may amend the crash report at a later time. A traffic crash within the city limits for which CPD is not the responding police agency, typically crashes on interstate highways, freeway ramps, and on local roads along the City boundary, are excluded from this dataset.

All crashes are recorded as per the format specified in the Traffic Crash Report, SR1050, of the Illinois Department of Transportation. As per Illinois statute, only crashes with a property damage value of $1,500 or more or involving bodily injury to any person(s) and that happen on a public roadway and that involve at least one moving vehicle, except bike dooring, are considered reportable crashes. However, CPD records every reported traffic crash event, regardless of the statute of limitations, and hence any formal Chicago crash dataset released by Illinois Department of Transportation may not include all the crashes listed here.

This coverage contains a highway Annual Average Daily Traffic (AADT) subset of the information included in the IDOT Illinois Highway Information System (IHIS) -- Illinois Roadway Information System (IRIS). Information is collected for all public highways as defined in Illinois Compiled Statutes (605 ILCS 5/2-202).

Annual Average Daily Traffic volumes (AADT) is a product of IDOT’s Traffic Count Program. Counts from this program range in duration from data continuously recorded at permanent count stations to thousands of coverage count locations that are counted for a 24-hour period throughout the year. More information about IDOT’s Traffic Count Program can be found at the Illinois Travel Statistics site.

Context:

On a typical day in the United States, police officers make more than 50,000 traffic stops. The Stanford Open Policing Project team is gathering, analyzing, and releasing records from millions of traffic stops by law enforcement agencies across the country. Their goal is to help researchers, journalists, and policymakers investigate and improve interactions between police and the public.

If you'd like to see data regarding other states, please go to https://www.kaggle.com/stanford-open-policing.

Content:

This dataset includes over 1 gb of stop data from Illinois, covering all of 2010 onwards. Please see the data readme for the full details of the available fields.

Acknowledgements:

This dataset was kindly made available by the Stanford Open Policing Project. If you use it for a research publication, please cite their working paper: E. Pierson, C. Simoiu, J. Overgoor, S. Corbett-Davies, V. Ramachandran, C. Phillips, S. Goel. (2017) “A large-scale analysis of racial disparities in police stops across the United States”.

Inspiration:

• How predictable are the stop rates? Are there times and places that reliably generate stops?
• Concerns have been raised about jurisdictions using civil forfeiture as a funding mechanism rather than to properly fight drug trafficking. Can you identify any jurisdictions that may be exhibiting this behavior?

Context

This data set is a collection of augmented random screenshots from traffic cameras in Chicago, IL. In the data, all vehicles are labeled in a single category called car. Labels consist of bounding boxes and are stored in YOLOv5 PyTorch format.

This data is a derivative work based on the data used by the STREETS project by Corey Snyder and Minh N. Do. The source data is publicly available. The source data was obtained on 9/2/2021. At the time of retrieval, the source data was licensed CC0. The research paper resulting from the STREETS project is also available.

Content

traffic

• test: a testing data set
  • images: image files in jpg format
  • labels: label files in YOLOv5 format - [category_id, bbox_center_y, bbox_center_x, bbox_width, bbox_height]
• train: a training data set
  • images: image files in jpg format
  • labels: label files in YOLOv5 format - [category_id, bbox_center_y, bbox_center_x, bbox_width, bbox_height]
• valid: a validation data set
  • images: image files in jpg format
  • labels: label files in YOLOv5 format - [category_id, bbox_center_y, bbox_center_x, bbox_width, bbox_height]
• data.yaml: data set and category identification

Acknowledgements

• Snyder, Corey; Do, Minh (2019): Data for STREETS: A Novel Camera Network Dataset for Traffic Flow. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-3671567_V1

This data contains information about people involved in a crash and if any injuries were sustained. This dataset should be used in combination with the traffic Crash and Vehicle dataset. Each record corresponds to an occupant in a vehicle listed in the Crash dataset. Some people involved in a crash may not have been an occupant in a motor vehicle, but may have been a pedestrian, bicyclist, or using another non-motor vehicle mode of transportation. Injuries reported are reported by the responding police officer. Fatalities that occur after the initial reports are typically updated in these records up to 30 days after the date of the crash. Person data can be linked with the Crash and Vehicle dataset using the “CRASH_RECORD_ID” field. A vehicle can have multiple occupants and hence have a one to many relationship between Vehicle and Person dataset. However, a pedestrian is a “unit” by itself and have a one to one relationship between the Vehicle and Person table.

The Chicago Police Department reports crashes on IL Traffic Crash Reporting form SR1050. The crash data published on the Chicago data portal mostly follows the data elements in SR1050 form. The current version of the SR1050 instructions manual with detailed information on each data elements is available here.

Change 11/21/2023: We have removed the RD_NO (Chicago Police Department report number) for privacy reasons.

Traffic fatalities within the City of Chicago that are included in Vision Zero Chicago (VZC) statistics. Vision Zero is Chicago’s commitment to eliminating fatalities and serious injuries from traffic crashes. The VZC Traffic Fatality List is compiled by the Chicago Department of Transportation (CDOT) after monthly reviews of fatal traffic crash information provided by Chicago Police Department’s Major Accident Investigation Unit (MAIU). CDOT uses a standardized process – sometimes differing from other sources and everyday use of the term -- to determine whether a death is a “traffic fatality.” Therefore, the traffic fatalities included in this list may differ from the fatal crashes reported in the full Traffic Crashes dataset (https://data.cityofchicago.org/d/85ca-t3if). Official traffic crash data are published by the Illinois Department of Transportation (IDOT) on an annual basis. This VZC Traffic Fatality List is updated monthly. Once IDOT publishes its crash data for a year, this dataset is edited to reflect IDOT’s findings. VZC Traffic Fatalities can be linked with other traffic crash datasets using the “Person_ID” field. State of Illinois considers a “traffic fatality” as any death caused by a traffic crash involving a motor vehicle, within 30 days of the crash. Fatalities that meet this definition are included in this VZC Traffic Fatality List unless excluded by any criteria below. There may be records in this dataset that do not appear as fatalities in the other datasets. The following criteria exclude a death from being considered a "traffic fatality," and are derived from Federal and State reporting standards. The Medical Examiner determined that the primary cause of the fatality was not the traffic crash, including: a. The fatality was reported as a suicide based on a police investigation. b. The fatality was reported as a homicide in which the "party at fault" intentionally inflicted serious bodily harm that caused the victim's death. c. The fatality was caused directly and exclusively by a medical condition or the fatality was not attributable to road user movement on a public roadway. (Note: If a person driving suffers a medical emergency and consequently hits and kills another road user, the other road user is included, although the driver suffering a medical emergency is excluded.) The crash did not occur within a trafficway. The crash involved a train or other such mode of transport within the rail dedicated right-of-way. The fatality was on a roadway not under Chicago Police Department jurisdiction, including: a. The fatality was occurred on an expressway. The City of Chicago does not have oversight on the expressway system. However, a fatality on expressway ramps occurring within the City jurisdiction will be counted in VZC Traffic Fatality List. b. The fatality occurred outside City limits. Crashes on streets along the City boundary may be assigned to another jurisdiction after the investigation if it is determined that the crash started or substantially occurred on the side of the street that is outside the City limits. Jurisdiction of streets along the City boundary are split between City and neighboring jurisdictions along the street centerline. The fatality is not a person (e.g., an animal). Change 12/7/2023: We have removed the RD_NO (Chicago Police Department report number) for privacy reasons.

Israel IL: Container Port Traffic: TEU (20 Foot Equivalent Units) data was reported at 2,856,028.000 TEU in 2017. This records an increase from the previous number of 2,522,000.000 TEU for 2016. Israel IL: Container Port Traffic: TEU (20 Foot Equivalent Units) data is updated yearly, averaging 2,089,900.000 TEU from Dec 2001 (Median) to 2017, with 17 observations. The data reached an all-time high of 2,856,028.000 TEU in 2017 and a record low of 1,378,259.000 TEU in 2001. Israel IL: 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 Israel – Table IL.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;